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Miyahira AK, Kamran SC, Jamaspishvili T, Marshall CH, Maxwell KN, Parolia A, Zorko NA, Pienta KJ, Soule HR. Disrupting prostate cancer research: Challenge accepted; report from the 2023 Coffey-Holden Prostate Cancer Academy Meeting. Prostate 2024; 84:993-1015. [PMID: 38682886 DOI: 10.1002/pros.24721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 04/16/2024] [Indexed: 05/01/2024]
Abstract
INTRODUCTION The 2023 Coffey-Holden Prostate Cancer Academy (CHPCA) Meeting, themed "Disrupting Prostate Cancer Research: Challenge Accepted," was convened at the University of California, Los Angeles, Luskin Conference Center, in Los Angeles, CA, from June 22 to 25, 2023. METHODS The 2023 marked the 10th Annual CHPCA Meeting, a discussion-oriented scientific think-tank conference convened annually by the Prostate Cancer Foundation, which centers on innovative and emerging research topics deemed pivotal for advancing critical unmet needs in prostate cancer research and clinical care. The 2023 CHPCA Meeting was attended by 81 academic investigators and included 40 talks across 8 sessions. RESULTS The central topic areas covered at the meeting included: targeting transcription factor neo-enhancesomes in cancer, AR as a pro-differentiation and oncogenic transcription factor, why few are cured with androgen deprivation therapy and how to change dogma to cure metastatic prostate cancer without castration, reducing prostate cancer morbidity and mortality with genetics, opportunities for radiation to enhance therapeutic benefit in oligometastatic prostate cancer, novel immunotherapeutic approaches, and the new era of artificial intelligence-driven precision medicine. DISCUSSION This article provides an overview of the scientific presentations delivered at the 2023 CHPCA Meeting, such that this knowledge can help in facilitating the advancement of prostate cancer research worldwide.
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Affiliation(s)
- Andrea K Miyahira
- Science Department, Prostate Cancer Foundation, Santa Monica, California, USA
| | - Sophia C Kamran
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Tamara Jamaspishvili
- Department of Pathology and Laboratory Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Catherine H Marshall
- Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kara N Maxwell
- Department of Medicine-Hematology/Oncology and Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Medicine Service, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA
| | - Abhijit Parolia
- Department of Pathology, Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, USA
| | - Nicholas A Zorko
- Division of Hematology, Oncology and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
- University of Minnesota Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Kenneth J Pienta
- The James Buchanan Brady Urological Institute, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Howard R Soule
- Science Department, Prostate Cancer Foundation, Santa Monica, California, USA
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He J, Perera D, Wen W, Ping J, Li Q, Lyu L, Chen Z, Shu X, Long J, Cai Q, Shu XO, Zheng W, Long Q, Guo X. Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.10.23295443. [PMID: 37873299 PMCID: PMC10593059 DOI: 10.1101/2023.10.10.23295443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-located variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-located variants to enhance model building. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these models to large GWAS datasets for breast, prostate, and lung cancers. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene prediction models and identifying disease-associated genes, as evidenced by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.
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Ben S, Ding Z, Xin J, Li F, Cheng Y, Chen S, Fan L, Zhang Q, Li S, Du M, Zhang Z, Wei GH, Cheng G, Wang M. piRNA PROPER Suppresses DUSP1 Translation by Targeting N 6-Methyladenosine-Mediated RNA Circularization to Promote Oncogenesis of Prostate Cancer. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2402954. [PMID: 38962952 DOI: 10.1002/advs.202402954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 06/19/2024] [Indexed: 07/05/2024]
Abstract
Genetic and epigenetic alterations occur in many physiological and pathological processes. The existing knowledge regarding the association of PIWI-interacting RNAs (piRNAs) and their genetic variants on risk and progression of prostate cancer (PCa) is limited. In this study, three genome-wide association study datasets are combined, including 85,707 PCa cases and 166,247 controls, to uncover genetic variants in piRNAs. Functional investigations involved manipulating piRNA expression in cellular and mouse models to study its oncogenetic role in PCa. A specific genetic variant, rs17201241 is identified, associated with increased expression of PROPER (piRNA overexpressed in prostate cancer) in tumors and are located within the gene, conferring an increased risk and malignant progression of PCa. Mechanistically, PROPER coupled with YTHDF2 to recognize N6-methyladenosine (m6A) and facilitated RNA-binding protein interactions between EIF2S3 at 5'-untranslated region (UTR) and YTHDF2/YBX3 at 3'-UTR to promote DUSP1 circularization. This m6A-dependent mRNA-looping pattern enhanced DUSP1 degradation and inhibited DUSP1 translation, ultimately reducing DUSP1 expression and promoting PCa metastasis via the p38 mitogen-activated protein kinase (MAPK) signaling pathway. Inhibition of PROPER expression using antagoPROPER effectively suppressed xenograft growth, suggesting its potential as a therapeutic target. Thus, targeting piRNA PROPER-mediated genetic and epigenetic fine control is a promising strategy for the concurrent prevention and treatment of PCa.
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Affiliation(s)
- Shuai Ben
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Ophthalmology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200080, China
| | - Zhutao Ding
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Junyi Xin
- Department of Bioinformatic, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Feng Li
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211100, China
| | - Yifei Cheng
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Silu Chen
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Lulu Fan
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Qin Zhang
- Disease Networks Research Unit, Faculty of Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, 90220, Finland
| | - Shuwei Li
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Mulong Du
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Zhengdong Zhang
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Gong-Hong Wei
- Disease Networks Research Unit, Faculty of Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, 90220, Finland
- Fudan University Shanghai Cancer Center & MOE Key Laboratory of Metabolism and Molecular Medicine and Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Gong Cheng
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province People's Hospital, Nanjing, 210029, China
| | - Meilin Wang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China
- Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
- Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
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Plym A, Zhang Y, Stopsack KH, Ugalde-Morales E, Seibert TM, Conti DV, Haiman CA, Baras A, Stocks T, Drake I, Penney KL, Giovannucci E, Kibel AS, Wiklund F, Mucci LA. Early Prostate Cancer Deaths Among Men With Higher vs Lower Genetic Risk. JAMA Netw Open 2024; 7:e2420034. [PMID: 38958976 PMCID: PMC11222990 DOI: 10.1001/jamanetworkopen.2024.20034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 04/23/2024] [Indexed: 07/04/2024] Open
Abstract
Importance Prostate cancer, a leading cause of cancer death among men, urgently requires new prevention strategies, which may involve targeting men with an underlying genetic susceptibility. Objective To explore differences in risk of early prostate cancer death among men with higher vs lower genetic risk to inform prevention efforts. Design, Setting, and Participants This cohort study used a combined analysis of genotyped men without prostate cancer at inclusion and with lifestyle data in 2 prospective cohort studies in Sweden and the US, the Malmö Diet and Cancer Study (MDCS) and the Health Professionals Follow-Up Study (HPFS), followed up from 1991 to 2019. Data were analyzed between April 2023 and April 2024. Exposures Men were categorized according to modifiable lifestyle behaviors and genetic risk. A polygenic risk score above the median or a family history of cancer defined men at higher genetic risk (67% of the study population); the remaining men were categorized as being at lower genetic risk. Main Outcomes and Measures Prostate cancer death analyzed using time-to-event analysis estimating hazard ratios (HR), absolute risks, and preventable deaths by age. Results Among the 19 607 men included for analysis, the median (IQR) age at inclusion was 59.0 (53.0-64.7) years (MDCS) and 65.1 (58.0-71.8) years (HPFS). During follow-up, 107 early (by age 75 years) and 337 late (after age 75 years) prostate cancer deaths were observed. Compared with men at lower genetic risk, men at higher genetic risk had increased rates of both early (HR, 3.26; 95% CI, 1.82-5.84) and late (HR, 2.26; 95% CI, 1.70-3.01) prostate cancer death, and higher lifetime risks of prostate cancer death (3.1% vs 1.3% [MDCS] and 2.3% vs 0.6% [HPFS]). Men at higher genetic risk accounted for 94 of 107 early prostate cancer deaths (88%), of which 36% (95% CI, 12%-60%) were estimated to be preventable through adherence to behaviors associated with a healthy lifestyle (not smoking, healthy weight, high physical activity, and a healthy diet). Conclusions and Relevance In this 20-year follow-up study, men with a genetic predisposition accounted for the vast majority of early prostate cancer deaths, of which one-third were estimated to be preventable. This suggests that men at increased genetic risk should be targeted in prostate cancer prevention strategies.
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Affiliation(s)
- Anna Plym
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Department of Urology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Yiwen Zhang
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Konrad H. Stopsack
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston
| | - Emilio Ugalde-Morales
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tyler M. Seibert
- Department of Radiation Medicine and Applied Sciences, Department of Radiology, and Department of Bioengineering, University of California San Diego, La Jolla
| | - David V. Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, New York
| | - Tanja Stocks
- Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Isabel Drake
- Department of Clinical Sciences in Malmö, Lund University, Malmö, Sweden
- Skåne University Hospital, Malmö, Sweden
| | - Kathryn L. Penney
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Edward Giovannucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Adam S. Kibel
- Department of Urology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Lorelei A. Mucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
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Layne TM, Rothstein JH, Song X, Andersen SW, Benn EKT, Sieh W, Klein RJ. Variants in Vitamin D-related Genes and Prostate Cancer Risk in Black Men. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.29.24309698. [PMID: 38978663 PMCID: PMC11230321 DOI: 10.1101/2024.06.29.24309698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
BACKGROUND The relationship between vitamin D and prostate cancer has primarily been characterized among White men. However, Black men have higher prostate cancer incidence and mortality rates, chronically low circulating vitamin D levels, and ancestry-specific genetic variants in vitamin D-related genes. Here, we examine six critical genes in the vitamin D pathway and prostate cancer risk in Black men. METHODS We assessed a total of 69 candidate variants in six genes ( GC, CYP27A1, CYP27B1, CYP24A1, VDR , and RXRA ) including functional variants previously associated with prostate cancer and circulating 25(OHD) in White men. Associations with prostate cancer risk were examined using genome-wide association study data for approximately 10,000 prostate cancer cases and 10,000 controls among Black men and over 85,000 cases and 91,000 controls among White men. A statistical significance threshold of 0.000724 was used to account for the 69 variants tested. RESULTS None of the variants examined were significantly associated with prostate cancer risk among Black men after multiple comparison adjustment. Four variants tested P<0.05 in Black men, including two in RXRA (rs41400444 OR=1.09, 95% CI: 1.01-1.17, P = 0.024 and rs10881574 OR = 0.93, 0.87-1.00, P = 0.046) and two in VDR (rs2853563 OR = 1.07, 1.01-1.13, P = 0.017 and rs1156882 OR = 1.06, 1.00-1.12, P = 0.045). Two variants in VDR were also positively associated with risk in White men (rs11568820 OR = 1.04, 1.02-1.06, P = 0.00024 and rs4516035 OR = 1.03, 1.01-1.04, P = 0.00055). CONCLUSION We observed suggestive non-significant associations between genetic variants in RXRA and VDR and prostate cancer risk in Black men. Future research exploring the relationship of vitamin D with cancer risk in Black men will need larger sample sizes to identify ancestry-specific variants relevant to risk in this population.
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Kaushal JB, Raut P, Muniyan S, Siddiqui JA, Alsafwani ZW, Seshacharyulu P, Nair SS, Tewari AK, Batra SK. Racial disparity in prostate cancer: an outlook in genetic and molecular landscape. Cancer Metastasis Rev 2024:10.1007/s10555-024-10193-8. [PMID: 38902476 DOI: 10.1007/s10555-024-10193-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 06/04/2024] [Indexed: 06/22/2024]
Abstract
Prostate cancer (PCa) incidence, morbidity, and mortality rates are significantly impacted by racial disparities. Despite innovative therapeutic approaches and advancements in prevention, men of African American (AA) ancestry are at a higher risk of developing PCa and have a more aggressive and metastatic form of the disease at the time of initial PCa diagnosis than other races. Research on PCa has underlined the biological and molecular basis of racial disparity and emphasized the genetic aspect as the fundamental component of racial inequality. Furthermore, the lower enrollment rate, limited access to national-level cancer facilities, and deferred treatment of AA men and other minorities are hurdles in improving the outcomes of PCa patients. This review provides the most up-to-date information on various biological and molecular contributing factors, such as the single nucleotide polymorphisms (SNPs), mutational spectrum, altered chromosomal loci, differential gene expression, transcriptome analysis, epigenetic factors, tumor microenvironment (TME), and immune modulation of PCa racial disparities. This review also highlights future research avenues to explore the underlying biological factors contributing to PCa disparities, particularly in men of African ancestry.
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Affiliation(s)
- Jyoti B Kaushal
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE-68198, USA
| | - Pratima Raut
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE-68198, USA
| | - Sakthivel Muniyan
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE-68198, USA
| | - Jawed A Siddiqui
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE-68198, USA
- Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE-68198, USA
| | - Zahraa W Alsafwani
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE-68198, USA
| | - Parthasarathy Seshacharyulu
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE-68198, USA
- Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE-68198, USA
| | - Sujit S Nair
- Department of Urology and the Tisch Cancer Institute at the Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ashutosh K Tewari
- Department of Urology and the Tisch Cancer Institute at the Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Surinder K Batra
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE-68198, USA.
- Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE-68198, USA.
- Division of Urology, Department of Surgery, University of Nebraska Medical Center, Omaha, NE-68198, USA.
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, NE-68198, USA.
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Jiang L, Shen J, Darst BF, Haiman CA, Mancuso N, Conti DV. Hierarchical joint analysis of marginal summary statistics-Part II: High-dimensional instrumental analysis of omics data. Genet Epidemiol 2024. [PMID: 38887957 DOI: 10.1002/gepi.22577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 04/04/2024] [Accepted: 05/15/2024] [Indexed: 06/20/2024]
Abstract
Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes.
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Affiliation(s)
- Lai Jiang
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Jiayi Shen
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Burcu F Darst
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Nicholas Mancuso
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - David V Conti
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
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Jee YH, Thibord F, Dominguez A, Sept C, Boulier K, Venkateswaran V, Ding Y, Cherlin T, Verma SS, Faro VL, Bartz TM, Boland A, Brody JA, Deleuze JF, Emmerich J, Germain M, Johnson AD, Kooperberg C, Morange PE, Pankratz N, Psaty BM, Reiner AP, Smadja DM, Sitlani CM, Suchon P, Tang W, Trégouët DA, Zöllner S, Pasaniuc B, Damrauer SM, Sanna S, Snieder H, Kabrhel C, Smith NL, Kraft P. Multi-ancestry polygenic risk scores for venous thromboembolism. Hum Mol Genet 2024:ddae097. [PMID: 38879759 DOI: 10.1093/hmg/ddae097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Revised: 05/29/2024] [Accepted: 06/03/2024] [Indexed: 06/25/2024] Open
Abstract
Venous thromboembolism (VTE) is a significant contributor to morbidity and mortality, with large disparities in incidence rates between Black and White Americans. Polygenic risk scores (PRSs) limited to variants discovered in genome-wide association studies in European-ancestry samples can identify European-ancestry individuals at high risk of VTE. However, there is limited evidence on whether high-dimensional PRS constructed using more sophisticated methods and more diverse training data can enhance the predictive ability and their utility across diverse populations. We developed PRSs for VTE using summary statistics from the International Network against Venous Thrombosis (INVENT) consortium genome-wide association studies meta-analyses of European- (71 771 cases and 1 059 740 controls) and African-ancestry samples (7482 cases and 129 975 controls). We used LDpred2 and PRS-CSx to construct ancestry-specific and multi-ancestry PRSs and evaluated their performance in an independent European- (6781 cases and 103 016 controls) and African-ancestry sample (1385 cases and 12 569 controls). Multi-ancestry PRSs with weights tuned in European-ancestry samples slightly outperformed ancestry-specific PRSs in European-ancestry test samples (e.g. the area under the receiver operating curve [AUC] was 0.609 for PRS-CSx_combinedEUR and 0.608 for PRS-CSxEUR [P = 0.00029]). Multi-ancestry PRSs with weights tuned in African-ancestry samples also outperformed ancestry-specific PRSs in African-ancestry test samples (PRS-CSxAFR: AUC = 0.58, PRS-CSx_combined AFR: AUC = 0.59), although this difference was not statistically significant (P = 0.34). The highest fifth percentile of the best-performing PRS was associated with 1.9-fold and 1.68-fold increased risk for VTE among European- and African-ancestry subjects, respectively, relative to those in the middle stratum. These findings suggest that the multi-ancestry PRS might be used to improve performance across diverse populations to identify individuals at highest risk for VTE.
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Affiliation(s)
- Yon Ho Jee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, United States
| | - Florian Thibord
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, 31 Center Drive, Bethesda, MD 20892, United States
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, 73 Mt. Wayte Ave, Suite #2, Framingham, MA 01702, United States
| | - Alicia Dominguez
- Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Corriene Sept
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, United States
| | - Kristin Boulier
- Bioinformatics Interdepartmental Program, University of California Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095-1570, United States
| | - Vidhya Venkateswaran
- Department of Oral Biology, University of California Los Angeles School of Dentistry, 13-089 CHS, Box 951668, Box 951570, Los Angeles, CA 90095-1668, United States
| | - Yi Ding
- Bioinformatics Interdepartmental Program, University of California Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095-1570, United States
| | - Tess Cherlin
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St. Philadelphia, PA 19104-4238, United States
| | - Shefali Setia Verma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St. Philadelphia, PA 19104-4238, United States
| | - Valeria Lo Faro
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Dag Hammarskjölds väg 20751 85 Uppsala, Sweden
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Biostatistics and Medicine, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
| | - Anne Boland
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, 91057 Evry, France
- Laboratory of Excellence in Medical Genomics, GENMED, F-91057 Evry, France
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
| | - Jean-Francois Deleuze
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, 91057 Evry, France
- Laboratory of Excellence in Medical Genomics, GENMED, F-91057 Evry, France
- Centre d'Etude du Polymorphisme Humain, Fondation Jean Dausset, 27 rue Juliette Dodu, 75010 Paris, France
| | - Joseph Emmerich
- Department of Vascular Medicine, Paris Saint-Joseph Hospital Group, University of Paris, 75014 Paris, France
- INSERM CRESS UMR 1153, F-75005, Paris, France
| | - Marine Germain
- Bordeaux Population Health Research Center, University of Bordeaux, INSERM, UMR 1219, Bordeaux, France
| | - Andrew D Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, 31 Center Drive, Bethesda, MD 20892, United States
- Framingham Heart Study, Boston University and National Heart, Lung, and Blood Institute, Framingham, 73 Mt. Wayte Ave, Suite #2, Framingham, MA 01702, United States
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinbson Cancer Center, PO Box 19024, Seattle, WA 98109, United States
| | - Pierre-Emmanuel Morange
- Aix-Marseille University, INSERM, INRAE, Centre de Recherche en CardioVasculaire et Nutrition, Laboratory of Haematology, CRB Assistance Publique - Hôpitaux de Marseille, HemoVasc, 27, boulevard Jean Moulin, 13005 Marseille, France
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN 55455, United States
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
- Department of Epidemiology, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
- Department of Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinbson Cancer Center, PO Box 19024, Seattle, WA 98109, United States
- Department of Epidemiology, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
| | - David M Smadja
- Innovative Therapies in Hemostasis, Université de Paris, INSERM, F-75006, Paris, France
- Hematology Department and Biosurgical Research Lab (Carpentier Foundation), Assistance Publique Hôpitaux de Paris, Centre-Université de Paris (APHP-CUP), F-75015, Paris, France
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
| | - Pierre Suchon
- Aix-Marseille University, INSERM, INRAE, Centre de Recherche en CardioVasculaire et Nutrition, Laboratory of Haematology, CRB Assistance Publique - Hôpitaux de Marseille, HemoVasc, 27, boulevard Jean Moulin, 13005 Marseille, France
| | - Weihong Tang
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, 1300 S. 2nd St., Minneapolis, MN 55454, United States
| | - David-Alexandre Trégouët
- Bordeaux Population Health Research Center, University of Bordeaux, INSERM, UMR 1219, Bordeaux, France
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Bogdan Pasaniuc
- Department of Oral Biology, University of California Los Angeles School of Dentistry, 13-089 CHS, Box 951668, Box 951570, Los Angeles, CA 90095-1668, United States
| | - Scott M Damrauer
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, 415 Curie Blvd, Philadelphia, PA 19104, United States
- Department of Surgery, Department of Genetics, and Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Building 421, Philadelphia, PA 19104, United States
- Department of Surgery, Corporal Michael Crescenz VA Medical Center, 3900 Woodland Ave, Philadelphia, PA 19104, United States
| | - Serena Sanna
- Department of Genetics, University of Groningen, University Medical Center Groningen (UMCG), PO Box 30.001, 9700 RB Groningen, The Netherlands
- Institute for Genetics and Biomedical Research, National Research Council, SS 554 Km 4,500, 09042 Monserrato CA, Italy
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands
| | - Christopher Kabrhel
- Center for Vascular Emergencies, Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, United States
| | - Nicholas L Smith
- Department of Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave, Seattle, WA 98195, United States
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, 1730 Minor Ave, Seattle, WA 98101, United States
- Department of Veterans Affairs Office of Research and Development, Seattle Epidemiologic Research and Information Center, 1660 S Columbian Way, S-152-E, Seattle, WA 98108, United States
| | - Peter Kraft
- Transdivisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Dr, Rockville, MD 20850, United States
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9
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Desai TA, Hedman ÅK, Dimitriou M, Koprulu M, Figiel S, Yin W, Johansson M, Watts EL, Atkins JR, Sokolov AV, Schiöth HB, Gunter MJ, Tsilidis KK, Martin RM, Pietzner M, Langenberg C, Mills IG, Lamb AD, Mälarstig A, Key TJ, Travis RC, Smith-Byrne K. Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics. EBioMedicine 2024; 105:105168. [PMID: 38878676 DOI: 10.1016/j.ebiom.2024.105168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 05/09/2024] [Accepted: 05/10/2024] [Indexed: 06/25/2024] Open
Abstract
BACKGROUND Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. METHODS We investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. FINDINGS We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. INTERPRETATION Our findings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer. FUNDING This work was supported by Cancer Research UK (grant no. C8221/A29017).
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Affiliation(s)
- Trishna A Desai
- Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom.
| | - Åsa K Hedman
- External Science and Innovation, Pfizer Worldwide Research, Development and Medical, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Marios Dimitriou
- External Science and Innovation, Pfizer Worldwide Research, Development and Medical, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mine Koprulu
- MRC Epidemiology Unit, University of Cambridge, United Kingdom
| | - Sandy Figiel
- University of Oxford, Nuffield Department of Surgical Sciences, Oxford, United Kingdom
| | - Wencheng Yin
- University of Oxford, Nuffield Department of Surgical Sciences, Oxford, United Kingdom
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Eleanor L Watts
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Joshua R Atkins
- Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom
| | - Aleksandr V Sokolov
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience Uppsala University, 75124, Uppsala, Sweden
| | - Helgi B Schiöth
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience Uppsala University, 75124, Uppsala, Sweden
| | - Marc J Gunter
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, United Kingdom
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, United Kingdom; Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Richard M Martin
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; NIHR Bristol Biomedical Research Centre, Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, United Kingdom
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, United Kingdom; Computational Medicine, Berlin Institute of HealthHealth (BIH) at Charité - Univeritätsmedizin- Universitätsmedizin Berlin, Berlin, Germany; Precision Healthcare University Research Institute, Queen Mary University of London, London, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, United Kingdom; Computational Medicine, Berlin Institute of HealthHealth (BIH) at Charité - Univeritätsmedizin- Universitätsmedizin Berlin, Berlin, Germany; Precision Healthcare University Research Institute, Queen Mary University of London, London, United Kingdom
| | - Ian G Mills
- University of Oxford, Nuffield Department of Surgical Sciences, Oxford, United Kingdom
| | - Alastair D Lamb
- University of Oxford, Nuffield Department of Surgical Sciences, Oxford, United Kingdom
| | - Anders Mälarstig
- External Science and Innovation, Pfizer Worldwide Research, Development and Medical, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tim J Key
- Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom
| | - Ruth C Travis
- Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom
| | - Karl Smith-Byrne
- Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom
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10
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Bellavance J, Wang L, Gagliano Taliun SA. Eight quick tips for including chromosome X in genome-wide association studies. PLoS Comput Biol 2024; 20:e1012160. [PMID: 38843110 PMCID: PMC11156303 DOI: 10.1371/journal.pcbi.1012160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024] Open
Affiliation(s)
- Justin Bellavance
- Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
| | - Linda Wang
- Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
| | - Sarah A. Gagliano Taliun
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
- Department of Neurosciences, Faculty of Medicine, Université de Montréal, Montréal, Québec, Canada
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11
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Li Q, Song Q, Chen Z, Choi J, Moreno V, Ping J, Wen W, Li C, Shu X, Yan J, Shu XO, Cai Q, Long J, Huyghe JR, Pai R, Gruber SB, Casey G, Wang X, Toriola AT, Li L, Singh B, Lau KS, Zhou L, Wu C, Peters U, Zheng W, Long Q, Yin Z, Guo X. Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention and intervention. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.29.24308170. [PMID: 38853880 PMCID: PMC11160851 DOI: 10.1101/2024.05.29.24308170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we uncover five drugs (Haloperidol, Trazodone, Tranexamic Acid, Haloperidol, and Captopril) associated with increased cancer risk and two drugs (Caffeine and Acetazolamide) linked to reduced colorectal cancer risk. This study offers novel insights into therapeutic drugs targeting risk proteins for cancer prevention and intervention.
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12
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Capalbo A, de Wert G, Mertes H, Klausner L, Coonen E, Spinella F, Van de Velde H, Viville S, Sermon K, Vermeulen N, Lencz T, Carmi S. Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations. Hum Reprod Update 2024:dmae012. [PMID: 38805697 DOI: 10.1093/humupd/dmae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/25/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing. OBJECTIVE AND RATIONALE This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom. SEARCH METHODS We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant. OUTCOMES The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling. WIDER IMPLICATIONS The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.
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Affiliation(s)
- Antonio Capalbo
- Juno Genetics, Department of Reproductive Genetics, Rome, Italy
- Center for Advanced Studies and Technology (CAST), Department of Medical Genetics, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Guido de Wert
- Department of Health, Ethics & Society, CAPHRI-School for Public Health and Primary Care and GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Heidi Mertes
- Department of Philosophy and Moral Sciences, Ghent University, Ghent, Belgium
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Liraz Klausner
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Edith Coonen
- Departments of Clinical Genetics and Reproductive Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
- School for Oncology and Developmental Biology, GROW, Maastricht University, Maastricht, The Netherlands
| | - Francesca Spinella
- Eurofins GENOMA Group Srl, Molecular Genetics Laboratories, Department of Scientific Communication, Rome, Italy
| | - Hilde Van de Velde
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
- Brussels IVF, UZ Brussel, Brussel, Belgium
| | - Stephane Viville
- Laboratoire de Génétique Médicale LGM, Institut de Génétique Médicale d'Alsace IGMA, INSERM UMR 1112, Université de Strasbourg, France
- Laboratoire de Diagnostic Génétique, Unité de Génétique de l'infertilité (UF3472), Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Karen Sermon
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
| | | | - Todd Lencz
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Departments of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
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13
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Pagadala MS, Lui AJ, Zhong AY, Lynch JA, Karunamuni R, Lee KM, Plym A, Rose BS, Carter HK, Kibel AS, DuVall SL, Gaziano JM, Panizzon MS, Hauger RL, Seibert TM. Agent orange exposure and prostate cancer risk in the million veteran program. Acta Oncol 2024; 63:373-378. [PMID: 38779869 DOI: 10.2340/1651-226x.2024.25053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 02/29/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND The US government considers veterans to have been exposed to Agent Orange if they served in Vietnam while the carcinogen was in use, and these veterans are often deemed at high risk of prostate cancer (PCa). Here, we assess whether presumed Agent Orange exposure is independently associated with increased risk of any metastatic or fatal PCa in a diverse Veteran cohort still alive in the modern era (at least 2011), when accounting for race/ethnicity, family history, and genetic risk. PATIENTS AND METHODS Participants in the Million Veteran Program (MVP; enrollment began in 2011) who were on active duty during the Vietnam War era (August 1964-April 1975) were included (n = 301,470). Agent Orange exposure was determined using the US government definition. Genetic risk was assessed via a validated polygenic hazard score. Associations with age at diagnosis of any PCa, metastatic PCa, and death from PCa were assessed via Cox proportional hazards models. RESULTS AND INTERPRETATION On univariable analysis, exposure to Agent Orange was not associated with increased PCa (hazard ratio [HR]: 1.02, 95% confidence interval [CI]: 1.00-1.04, p = 0.06), metastatic PCa (HR: 0.98, 95% CI: 0.91-1.05, p = 0.55), or fatal PCa (HR: 0.94, 95% CI: 0.79-1.09, p = 0.41). When accounting for race/ethnicity and family history, Agent Orange exposure was independently associated with slightly increased risk of PCa (HR: 1.06, 95% CI: 1.04-1.09, <10-6) but not with metastatic PCa (HR: 1.07, 95% CI: 0.98-1.15, p = 0.10) or PCa death (HR: 1.02, 95% CI: 0.83-1.23, p = 0.09). Similar results were found when accounting for genetic risk. Agent Orange exposure history may not improve modern PCa risk stratification.
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Affiliation(s)
- Meghana S Pagadala
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA; Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA; Biomedical Science Program, University of California San Diego, La Jolla, CA, USA
| | - Asona J Lui
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA
| | - Allison Y Zhong
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Health Care System, Salt Lake City, UT, USA; Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Roshan Karunamuni
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA
| | - Kyung Min Lee
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Health Care System, Salt Lake City, UT, USA; Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Anna Plym
- Division of Urology, Brigham and Women's Hospital, Boston, MA, USA; Epidemiology, TH Chan School of Public Health, Harvard University, Boston, MA, USA; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Brent S Rose
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA; Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA
| | - Hannah K Carter
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Adam S Kibel
- Division of Urology, Brigham and Women's Hospital, Boston, MA, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Health Care System, Salt Lake City, UT, USA; Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Matthew S Panizzon
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA; Center for Behavioral Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Richard L Hauger
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA; Center for Behavioral Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Center of Excellence for Stress and Mental Health (CESAMH), VA San Diego Healthcare System, San Diego, CA, USA
| | - Tyler M Seibert
- Research Service, VA San Diego Healthcare System, San Diego, CA, USA; Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
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14
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Hung SC, Chang LW, Hsiao TH, Lin GC, Wang SS, Li JR, Chen IC. Polygenic risk score predicting susceptibility and outcome of benign prostatic hyperplasia in the Han Chinese. Hum Genomics 2024; 18:49. [PMID: 38778357 PMCID: PMC11110300 DOI: 10.1186/s40246-024-00619-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 05/08/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Given the high prevalence of BPH among elderly men, pinpointing those at elevated risk can aid in early intervention and effective management. This study aimed to explore that polygenic risk score (PRS) is effective in predicting benign prostatic hyperplasia (BPH) incidence, prognosis and risk of operation in Han Chinese. METHODS A retrospective cohort study included 12,474 male participants (6,237 with BPH and 6,237 non-BPH controls) from the Taiwan Precision Medicine Initiative (TPMI). Genotyping was performed using the Affymetrix Genome-Wide TWB 2.0 SNP Array. PRS was calculated using PGS001865, comprising 1,712 single nucleotide polymorphisms. Logistic regression models assessed the association between PRS and BPH incidence, adjusting for age and prostate-specific antigen (PSA) levels. The study also examined the relationship between PSA, prostate volume, and response to 5-α-reductase inhibitor (5ARI) treatment, as well as the association between PRS and the risk of TURP. RESULTS Individuals in the highest PRS quartile (Q4) had a significantly higher risk of BPH compared to the lowest quartile (Q1) (OR = 1.51, 95% CI = 1.274-1.783, p < 0.0001), after adjusting for PSA level. The Q4 group exhibited larger prostate volumes and a smaller volume reduction after 5ARI treatment. The Q1 group had a lower cumulative TURP probability at 3, 5, and 10 years compared to the Q4 group. PRS Q4 was an independent risk factor for TURP. CONCLUSIONS In this Han Chinese cohort, higher PRS was associated with an increased susceptibility to BPH, larger prostate volumes, poorer response to 5ARI treatment, and a higher risk of TURP. Larger prospective studies with longer follow-up are warranted to further validate these findings.
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Affiliation(s)
- Sheng-Chun Hung
- Division of Urology, Department of Surgery, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Li-Wen Chang
- Division of Urology, Department of Surgery, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Tzu-Hung Hsiao
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Public Health, Fu Jen Catholic University, New Taipei City, Taiwan
- Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung, Taiwan
| | - Guan-Cheng Lin
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Shian-Shiang Wang
- Division of Urology, Department of Surgery, Taichung Veterans General Hospital, Taichung, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
- Department of Applied Chemistry, National Chi Nan University, Nantou, Taiwan
| | - Jian-Ri Li
- Division of Urology, Department of Surgery, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
- Department of Medicine and Nursing, Hungkuang University, Taichung, Taiwan
| | - I-Chieh Chen
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan.
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15
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Lu B, Liu Y, Yao Y, Yang T, Zhang H, Yang X, Huang R, Zhou W, Pan X, Cui X. Advances in sequencing and omics studies in prostate cancer: unveiling molecular pathogenesis and clinical applications. Front Oncol 2024; 14:1355551. [PMID: 38800374 PMCID: PMC11116611 DOI: 10.3389/fonc.2024.1355551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/16/2024] [Indexed: 05/29/2024] Open
Abstract
Background Prostate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field. Methods We assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field. Results 3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, 'the molecular pathogenesis of PCa' and 'the clinical application of sequencing and omics studies in PCa' were summarized as two research hotspots in the field. Conclusion Sequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.
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Affiliation(s)
- Bingnan Lu
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yifan Liu
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuntao Yao
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianyue Yang
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haoyu Zhang
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyue Yang
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Runzhi Huang
- Department of Burn Surgery, The First Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Wang Zhou
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiuwu Pan
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xingang Cui
- Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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16
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Mitchell J, Camacho N, Shea P, Stopsack KH, Joseph V, Burren O, Dhindsa R, Nag A, Berchuck JE, O'Neill A, Abbasi A, Zoghbi AW, Alegre-Díaz J, Kuri-Morales P, Berumen J, Tapia-Conyer R, Emberson J, Torres JM, Collins R, Wang Q, Goldstein D, Matakidou A, Haefliger C, Anderson-Dring L, March R, Jobanputra V, Dougherty B, Carss K, Petrovski S, Kantoff PW, Offit K, Mucci LA, Pomerantz M, Fabre MA. Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.10.24307164. [PMID: 38766261 PMCID: PMC11100931 DOI: 10.1101/2024.05.10.24307164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway (BRCA2, ATM and CHEK2) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes (HOXB13, CHEK2, BIK) significantly associated with increased risk of overall prostate cancer and in four genes (ANO7, SPDL1, AR, TERT) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.
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Affiliation(s)
- Jonathan Mitchell
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Niedzica Camacho
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Patrick Shea
- Institute for Genomic Medicine, Columbia University, New York, New York, USA
| | - Konrad H Stopsack
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Vijai Joseph
- Cancer Biology and Genetics Program, Sloan Kettering Institute, New York, New York, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Medicine, Weill Cornell Medical College, New York, New York, USA
| | - Oliver Burren
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ryan Dhindsa
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Abhishek Nag
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | | | - Amanda O'Neill
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ali Abbasi
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Anthony W Zoghbi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Jesus Alegre-Díaz
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, Ciudad de México, Mexico
| | - Pablo Kuri-Morales
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, Ciudad de México, Mexico
- Instituto Tecnológico y de Estudios Superiores de Monterrey, Tecnológico, Monterrey, Nuevo León, Mexico
| | - Jaime Berumen
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, Ciudad de México, Mexico
| | - Roberto Tapia-Conyer
- Faculty of Medicine, National Autonomous University of Mexico, Copilco Universidad, Coyoacán, Ciudad de México, Mexico
| | - Jonathan Emberson
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jason M Torres
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Quanli Wang
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, Massachusetts, USA
| | - David Goldstein
- Institute for Genomic Medicine, Columbia University, New York, New York, USA
| | - Athena Matakidou
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Carolina Haefliger
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Lauren Anderson-Dring
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Ruth March
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Vaidehi Jobanputra
- Institute for Genomic Medicine, Columbia University, New York, New York, USA
| | | | - Keren Carss
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Slavé Petrovski
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Philip W Kantoff
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Convergent Therapeutics, Cambridge, Massachusetts, USA
| | - Kenneth Offit
- Cancer Biology and Genetics Program, Sloan Kettering Institute, New York, New York, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Medicine, Weill Cornell Medical College, New York, New York, USA
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
- American Cancer Society, Boston, Massachusetts, USA
| | - Mark Pomerantz
- Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Margarete A Fabre
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
- Department of Haematology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Haematology, University of Cambridge, Cambridge, UK
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17
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Vince RA, Sun H, Singhal U, Schumacher FR, Trapl E, Rose J, Cullen J, Zaorsky N, Shoag J, Hartman H, Jia AY, Spratt DE, Fritsche LG, Morgan TM. Assessing the Clinical Utility of Published Prostate Cancer Polygenic Risk Scores in a Large Biobank Data Set. Eur Urol Oncol 2024:S2588-9311(24)00111-1. [PMID: 38734542 DOI: 10.1016/j.euo.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 03/26/2024] [Accepted: 04/22/2024] [Indexed: 05/13/2024]
Abstract
BACKGROUND AND OBJECTIVE Polygenic risk scores (PRSs) have been developed to identify men with the highest risk of prostate cancer. Our aim was to compare the performance of 16 PRSs in identifying men at risk of developing prostate cancer and then to evaluate the performance of the top-performing PRSs in differentiating individuals at risk of aggressive prostate cancer. METHODS For this case-control study we downloaded 16 published PRSs from the Polygenic Score Catalog on May 28, 2021 and applied them to Michigan Genomics Initiative (MGI) patients. Cases were matched to the Michigan Urological Surgery Improvement Collaborative (MUSIC) registry to obtain granular clinical and pathological data. MGI prospectively enrolls patients undergoing surgery at the University of Michigan, and MUSIC is a multi-institutional registry that prospectively tracks demographic, treatment, and clinical variables. The predictive performance of each PRS was evaluated using the area under the covariate-adjusted receiver operating characteristic curve (aAUC), and the association between PRS and disease aggressiveness according to prostate biopsy data was measured using logistic regression. KEY FINDINGS AND LIMITATIONS We included 18 050 patients in the analysis, of whom 15 310 were control subjects and 2740 were prostate cancer cases. The median age was 66.1 yr (interquartile range 59.9-71.6) for cases and 56.6 yr (interquartile range 42.6-66.7) for control subjects. The PRS performance in predicting the risk of developing prostate cancer according to aAUC ranged from 0.51 (95% confidence interval 0.51-0.53) to 0.67 (95% confidence interval 0.66-0.68). By contrast, there was no association between PRS and disease aggressiveness. CONCLUSIONS AND CLINICAL IMPLICATIONS Prostate cancer PRSs have modest real-world performance in identifying patients at higher risk of developing prostate cancer; however, they are limited in distinguishing patients with indolent versus aggressive disease. PATIENT SUMMARY Risk scores using data for multiple genes (called polygenic risk scores) can identify men at higher risk of developing prostate cancer. However, these scores need to be refined to be able to identify men with the highest risk for clinically significant prostate cancer.
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Affiliation(s)
- Randy A Vince
- Department of Urology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH, USA.
| | - Helen Sun
- Department of Urology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH, USA
| | - Udit Singhal
- Department of Urology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Fredrick R Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Erika Trapl
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Johnie Rose
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Jennifer Cullen
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Nicholas Zaorsky
- Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH, USA
| | - Johnathan Shoag
- Department of Urology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH, USA
| | - Holly Hartman
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Angela Y Jia
- Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH, USA
| | - Daniel E Spratt
- Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH, USA
| | - Lars G Fritsche
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Todd M Morgan
- Department of Urology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
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18
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Lee KM, Nelson TJ, Bryant A, Teerlink CC, Gulati R, Pagadala MS, Tcheandjieu C, Pridgen KM, DuVall SL, Yamoah K, Vassy JL, Seibert TM, Hauger RL, Rose BS, Lynch JA. Genetic risk and likelihood of prostate cancer detection on first biopsy by ancestry. J Natl Cancer Inst 2024; 116:753-757. [PMID: 38212986 PMCID: PMC11077300 DOI: 10.1093/jnci/djae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/03/2023] [Accepted: 12/23/2023] [Indexed: 01/13/2024] Open
Abstract
Despite differences in prostate cancer risk across ancestry groups, relative performance of prostate cancer genetic risks scores (GRS) for positive biopsy prediction in different ancestry groups is unknown. This cross-sectional retrospective analysis examines the association between a polygenic hazard score (PHS290) and risk of prostate cancer diagnosis upon first biopsy in male veterans using 2-sided tests. Our analysis included 36 717 veterans (10 297 of African ancestry). Unadjusted rates of positive first prostate biopsy increased with higher genetic risk (low risk: 34%, high risk: 58%; P < .001). Among men of African ancestry, higher genetic risk was associated with increased prostate cancer detection on first biopsy (odds ratio = 2.18, 95% confidence interval = 1.93 to 2.47), but the effect was stronger among men of European descent (odds ratio = 3.89, 95% confidence interval = 3.62 to 4.18). These findings suggest that incorporating genetic risk into prediction models could better personalize biopsy decisions, although further study is needed to achieve equitable genetic risk stratification among ancestry groups.
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Affiliation(s)
- Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Tyler J Nelson
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Alex Bryant
- Department of Radiation Oncology, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | - Craig C Teerlink
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Roman Gulati
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Meghana S Pagadala
- VA San Diego Healthcare System, San Diego, CA, USA
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA
- Biomedical Science Program, University of California San Diego, La Jolla, CA, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Kathryn M Pridgen
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Kosj Yamoah
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA
- James A. Haley Veterans’ Hospital, Tampa, FL, USA
| | - Jason L Vassy
- Section of General Internal Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Tyler M Seibert
- VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Richard L Hauger
- VA San Diego Healthcare System, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Brent S Rose
- VA San Diego Healthcare System, San Diego, CA, USA
- Department of Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, UT, USA
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19
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Brown KK, Thomas SP, Brothers RM, Liao Y. "Lord Knows What's Being Done with My Blood!": Black Women's Perceptions of Biospecimen Donation for Clinical Research in the United States. J Racial Ethn Health Disparities 2024:10.1007/s40615-024-02015-y. [PMID: 38714639 DOI: 10.1007/s40615-024-02015-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 04/06/2024] [Accepted: 04/28/2024] [Indexed: 05/10/2024]
Abstract
PURPOSE Black women are underrepresented in clinical research and clinical trials. Knowledge gaps lead to biased clinical practice and care. There is a small but growing body of literature on Black women's perceptions about participation when biospecimen donation is sought by researchers. This is the first known study to investigate willingness to participate in clinical research involving biospecimen donation among Black women of reproductive age in the United States. METHODS This cross-sectional study recruited 496 Black women (ages 18-49) from a research crowdsourcing platform. Participants completed a 46-item online survey which asked about their willingness to provide blood samples for clinical health research and reasons for their willingness or for any unwillingness. Descriptive statistics and thematic analysis method were used to analyze the data. RESULTS Less than half (44%) of participants reported willingness to provide blood samples for clinical research. The most common concerns of those expressing unwillingness to provide samples were "fear of blood sample being misused" and "distrust with the health researchers handling the samples." We identified six qualitative themes from the analysis of participants' open-ended responses. The most important factors include a desire for integrity and transparency in research, institutional racism contributing to mistrust, and adequate compensation and clearly defined benefits to participation. CONCLUSIONS The recruitment and engagement of Black women in clinical biospecimen research should involve transparent, trustworthy, and anti-racist practices and informed respect for Black women's autonomy. There is a need to address Black women's concerns about exploitative profits and mistrust of academic and medical institutions.
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Affiliation(s)
- Kyrah K Brown
- Department of Kinesiology, University of Texas at Arlington, 500 W. Nedderman Drive, Arlington, TX, 76019, USA.
| | | | - R Mathew Brothers
- Department of Kinesiology, University of Texas at Arlington, 500 W. Nedderman Drive, Arlington, TX, 76019, USA
| | - Yue Liao
- Department of Kinesiology, University of Texas at Arlington, 500 W. Nedderman Drive, Arlington, TX, 76019, USA
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20
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Gu J, Chery L, González GMN, Huff C, Strom S, Jones JA, Griffith DP, Canfield SE, Wang X, Huang X, Roberson P, Meng QH, Troncoso P, Ittmann M, Covinsky M, Scheurer M, Irizarry Ramirez M, Pettaway CA. A west African ancestry-associated SNP on 8q24 predicts a positive biopsy in African American men with suspected prostate cancer following PSA screening. Prostate 2024; 84:694-705. [PMID: 38477020 DOI: 10.1002/pros.24686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/28/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND African American (AA) men have the highest incidence and mortality rates of prostate cancer (PCa) among all racial groups in the United States. While race is a social construct, for AA men, this overlaps with west African ancestry. Many of the PCa susceptibility variants exhibit distinct allele frequencies and risk estimates across different races and contribute substantially to the large disparities of PCa incidence among races. We previously reported that a single-nucleotide polymorphism (SNP) in 8q24, rs7824364, was strongly associated with west African ancestry and increased risks of PCa in both AA and Puerto Rican men. In this study, we determined whether this SNP can predict biopsy positivity and detection of clinically significant disease (Gleason score [GS] ≥ 7) in a cohort of AA men with suspected PCa. METHODS SNP rs7824364 was genotyped in 199 AA men with elevated total prostate-specific antigen (PSA) (>2.5 ng/mL) or abnormal digital rectal exam (DRE) and the associations of different genotypes with biopsy positivity and clinically significant disease were analyzed. RESULTS The variant allele carriers were significantly over-represented in the biopsy-positive group compared to the biopsy-negative group (44% vs. 25.7%, p = 0.011). In the multivariate logistic regression analyses, variant allele carriers were at a more than a twofold increased risk of a positive biopsy (odds ratio [OR] = 2.14, 95% confidence interval [CI] = 1.06-4.32). Moreover, the variant allele was a predictor (OR = 2.26, 95% CI = 1.06-4.84) of a positive biopsy in the subgroup of patients with PSA < 10 ng/mL and normal DRE. The variant allele carriers were also more prevalent in cases with GS ≥ 7 compared to cases with GS < 7 and benign biopsy. CONCLUSIONS This study demonstrated that the west African ancestry-specific SNP rs7824364 on 8q24 independently predicted a positive prostate biopsy in AA men who were candidates for prostate biopsy subsequent to PCa screening.
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Affiliation(s)
- Jian Gu
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Lisly Chery
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Chad Huff
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Sara Strom
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jeffrey A Jones
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
- Department of Urology, Baylor College of Medicine, Houston, Texas, USA
- Urology Section, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
| | - Donald P Griffith
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - Steven E Canfield
- Division of Urology, UTHealth McGovern Medical School, Houston, Texas, USA
| | - Xuemei Wang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Xuelin Huang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Pamela Roberson
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Qing H Meng
- Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Patricia Troncoso
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Michael Ittmann
- Department of Pathology, Baylor College of Medicine, Houston, Texas, USA
| | - Michael Covinsky
- Division of Pathology, UTHealth McGovern Medical School, Houston, Texas, USA
| | - Michael Scheurer
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Margarita Irizarry Ramirez
- Department of Graduate Studies, Clinical Laboratory Sciences, School of Health Professions, University of Puerto Rico, San Juan, Puerto Rico
| | - Curtis A Pettaway
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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21
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Gong J, Kim DM, Freeman MR, Kim H, Ellis L, Smith B, Theodorescu D, Posadas E, Figlin R, Bhowmick N, Freedland SJ. Genetic and biological drivers of prostate cancer disparities in Black men. Nat Rev Urol 2024; 21:274-289. [PMID: 37964070 DOI: 10.1038/s41585-023-00828-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2023] [Indexed: 11/16/2023]
Abstract
Black men with prostate cancer have historically had worse outcomes than white men with prostate cancer. The causes of this disparity in outcomes are multi-factorial, but a potential basis is that prostate cancers in Black men are biologically distinct from prostate cancers in white men. Evidence suggests that genetic and ancestral factors, molecular pathways involving androgen and non-androgen receptor signalling, inflammation, epigenetics, the tumour microenvironment and tumour metabolism are contributing factors to the racial disparities observed. Key genetic and molecular pathways linked to prostate cancer risk and aggressiveness have potential clinical relevance. Describing biological drivers of prostate cancer disparities could inform efforts to improve outcomes for Black men with prostate cancer.
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Affiliation(s)
- Jun Gong
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Daniel M Kim
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Michael R Freeman
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Hyung Kim
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Leigh Ellis
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Bethany Smith
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Dan Theodorescu
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Edwin Posadas
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Robert Figlin
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Neil Bhowmick
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Stephen J Freedland
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Section of Urology, Durham VA Medical Center, Durham, NC, USA
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22
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Akamatsu S, Naito Y, Nagayama J, Sano Y, Inoue S, Matsuo K, Sano T, Ishida S, Matsukawa Y, Kato M. Treatment escalation and de-escalation of de-novo metastatic castration-sensitive prostate cancer. NAGOYA JOURNAL OF MEDICAL SCIENCE 2024; 86:169-180. [PMID: 38962407 PMCID: PMC11219222 DOI: 10.18999/nagjms.86.2.169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 09/21/2023] [Indexed: 07/05/2024]
Abstract
Androgen receptor signaling inhibitors combined with androgen deprivation therapy have become the standard of care for metastatic castration-sensitive prostate cancer (mCSPC), regardless of tumor volume or risk. However, survival of approximately one-third of these patients has not improved, necessitating further treatment escalation. On the other hand, for patients with oligometastatic mCSPC, there is an emerging role for local radiation therapy. Although data remain scarce, it is expected that treatment of both primary tumor as well as metastasis-directed therapy may improve survival outcomes. In these patients, systemic therapy may be de-escalated to intermittent therapy. However, precise risk stratification is necessary for risk-based treatment escalation or de-escalation. In addition to risk stratification based on clinical parameters, research has been conducted to incorporate genomic and/or transcriptomic data into risk stratification. In future, an integrated risk model is expected to precisely stratify patients and guide treatment strategies. Here, we first review the transition of the standard treatment for mCSPC over the last decade and further discuss the newest concept of escalating or de-escalating treatment using a multi-modal approach based on the currently available literature.
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Affiliation(s)
- Shusuke Akamatsu
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yushi Naito
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Jun Nagayama
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yuta Sano
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Satoshi Inoue
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuna Matsuo
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Tomoyasu Sano
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Shohei Ishida
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yoshihisa Matsukawa
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Masashi Kato
- Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan
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23
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Garraway IP, Carlsson SV, Nyame YA, Vassy JL, Chilov M, Fleming M, Frencher SK, George DJ, Kibel AS, King SA, Kittles R, Mahal BA, Pettaway CA, Rebbeck T, Rose B, Vince R, Winn RA, Yamoah K, Oh WK. Prostate Cancer Foundation Screening Guidelines for Black Men in the United States. NEJM EVIDENCE 2024; 3:EVIDoa2300289. [PMID: 38815168 DOI: 10.1056/evidoa2300289] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
BACKGROUND In the United States, Black men are at highest risk for being diagnosed with and dying from prostate cancer. Given this disparity, we examined relevant data to establish clinical prostate-specific antigen (PSA) screening guidelines for Black men in the United States. METHODS A comprehensive literature search identified 1848 unique publications for screening. Of those screened, 287 studies were selected for full-text review, and 264 were considered relevant and form the basis for these guidelines. The numbers were reported according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS Three randomized controlled trials provided Level 1 evidence that regular PSA screening of men 50 to 74 years of age of average risk reduced metastasis and prostate cancer death at 16 to 22 years of follow-up. The best available evidence specifically for Black men comes from observational and modeling studies that consider age to obtain a baseline PSA, frequency of testing, and age when screening should end. Cohort studies suggest that discussions about baseline PSA testing between Black men and their clinicians should begin in the early 40s, and data from modeling studies indicate prostate cancer develops 3 to 9 years earlier in Black men compared with non-Black men. Lowering the age for baseline PSA testing to 40 to 45 years of age from 50 to 55 years of age, followed by regular screening until 70 years of age (informed by PSA values and health factors), could reduce prostate cancer mortality in Black men (approximately 30% relative risk reduction) without substantially increasing overdiagnosis. CONCLUSIONS These guidelines recommend that Black men should obtain information about PSA screening for prostate cancer. Among Black men who elect screening, baseline PSA testing should occur between ages 40 and 45. Depending on PSA value and health status, annual screening should be strongly considered. (Supported by the Prostate Cancer Foundation.).
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Affiliation(s)
- Isla P Garraway
- Department of Urology, David Geffen School of Medicine, University of California and Department of Surgical and Perioperative Care, VA Greater Los Angeles Healthcare System, Los Angeles
| | - Sigrid V Carlsson
- Departments of Surgery and Epidemiology and Biostatistics, Urology Service, Memorial Sloan Kettering Cancer Center, New York
- Department of Urology, Sahlgrenska Academy at Gothenburg University, Gothenburg, and Department of Translational Medicine, Division of Urological Cancers, Medical Faculty, Lund University, Lund, Sweden
| | - Yaw A Nyame
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle
- Department of Urology, University of Washington, Seattle
| | - Jason L Vassy
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Health Administration, Bedford and Boston
- Harvard Medical School and Brigham and Women's Hospital, Boston
| | - Marina Chilov
- Medical Library, Memorial Sloan Kettering Cancer Center, New York
| | - Mark Fleming
- Virginia Oncology Associates, US Oncology Network, Norfolk, VA
| | - Stanley K Frencher
- Martin Luther King Jr. Community Hospital and University of California, Los Angeles
| | - Daniel J George
- Duke Cancer Institute Center for Prostate and Urologic Cancers, Duke University, Durham, NC
| | - Adam S Kibel
- Department of Urology, Brigham and Women's Hospital, Harvard Medical School, Boston
| | - Sherita A King
- Section of Urology, Medical College of Georgia at Augusta University and Charlie Norwood Veterans Affairs Medical Center, Augusta, GA
| | - Rick Kittles
- Morehouse School of Medicine, Community Health and Preventive Medicine, Atlanta
| | - Brandon A Mahal
- Sylvester Comprehensive Cancer Center, Miami
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami
| | - Curtis A Pettaway
- Department of Urology, The University of Texas MD Anderson Cancer Center, Houston
| | - Timothy Rebbeck
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston
- Harvard T.H. Chan School of Public Health, Boston
| | - Brent Rose
- Department of Radiation Oncology, University of California, San Diego
- Veterans Affairs San Diego Healthcare System, San Diego, CA
| | - Randy Vince
- Department of Urology, University of Michigan, Ann Arbor
| | - Robert A Winn
- Massey Cancer Center, Virginia Commonwealth University, Richmond
- Department of Internal Medicine, Virginia Commonwealth University, Richmond
| | - Kosj Yamoah
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL
- James A. Haley Veterans' Hospital, Tampa, FL
| | - William K Oh
- Prostate Cancer Foundation, Santa Monica, CA
- Division of Hematology and Medical Oncology, Tisch Cancer Institute at Mount Sinai, New York
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24
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Cheng Y, Wu L, Xin J, Ben S, Chen S, Li H, Zhao L, Wang M, Cheng G, Du M. An early-onset specific polygenic risk score optimizes age-based risk estimate and stratification of prostate cancer: population-based cohort study. J Transl Med 2024; 22:366. [PMID: 38632662 PMCID: PMC11025178 DOI: 10.1186/s12967-024-05190-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 04/11/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Early-onset prostate cancer (EOPC, ≤ 55 years) has a unique clinical entity harboring high genetic risk, but the majority of EOPC patients still substantial opportunity to be early-detected thus suffering an unfavorable prognosis. A refined understanding of age-based polygenic risk score (PRS) for prostate cancer (PCa) would be essential for personalized risk stratification. METHODS We included 167,517 male participants [4882 cases including 205 EOPC and 4677 late-onset PCa (LOPC)] from UK Biobank. A General-, an EOPC- and an LOPC-PRS were derived from age-specific genome-wide association studies. Weighted Cox proportional hazard models were applied to estimate the risk of PCa associated with PRSs. The discriminatory capability of PRSs were validated using time-dependent receiver operating characteristic (ROC) curves with additional 4238 males from PLCO and TCGA. Phenome-wide association studies underlying Mendelian Randomization were conducted to discover EOPC linking phenotypes. RESULTS The 269-PRS calculated via well-established risk variants was more strongly associated with risk of EOPC [hazard ratio (HR) = 2.35, 95% confidence interval (CI) 1.99-2.78] than LOPC (HR = 1.95, 95% CI 1.89-2.01; I2 = 79%). EOPC-PRS was dramatically related to EOPC risk (HR = 4.70, 95% CI 3.98-5.54) but not to LOPC (HR = 0.98, 95% CI 0.96-1.01), while LOPC-PRS had similar risk estimates for EOPC and LOPC (I2 = 0%). Particularly, EOPC-PRS performed optimal discriminatory capability for EOPC (area under the ROC = 0.613). Among the phenomic factors to PCa deposited in the platform of ProAP (Prostate cancer Age-based PheWAS; https://mulongdu.shinyapps.io/proap ), EOPC was preferentially associated with PCa family history while LOPC was prone to environmental and lifestyles exposures. CONCLUSIONS This study comprehensively profiled the distinct genetic and phenotypic architecture of EOPC. The EOPC-PRS may optimize risk estimate of PCa in young males, particularly those without family history, thus providing guidance for precision population stratification.
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Affiliation(s)
- Yifei Cheng
- Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Department of Environmental Genomics, School of Public Health, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
- The Key Laboratory of Modern Toxicology of Ministry of Education, Department of Genetic Toxicology, School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Junyi Xin
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Shuai Ben
- Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Department of Environmental Genomics, School of Public Health, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
- The Key Laboratory of Modern Toxicology of Ministry of Education, Department of Genetic Toxicology, School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, China
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Silu Chen
- Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Department of Environmental Genomics, School of Public Health, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
- The Key Laboratory of Modern Toxicology of Ministry of Education, Department of Genetic Toxicology, School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Huiqin Li
- Department of Biostatistics, School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Lingyan Zhao
- Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Department of Environmental Genomics, School of Public Health, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
- The Key Laboratory of Modern Toxicology of Ministry of Education, Department of Genetic Toxicology, School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Meilin Wang
- Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Department of Environmental Genomics, School of Public Health, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
- The Key Laboratory of Modern Toxicology of Ministry of Education, Department of Genetic Toxicology, School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, China
- Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Nanjing Medical University, Suzhou, China
| | - Gong Cheng
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province People's Hospital, 300 Guangzhou Road, Nanjing, 210029, China.
| | - Mulong Du
- Department of Biostatistics, School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, China.
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, 655 Huntington Avenue, Boston, MA, 02115, USA.
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25
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Lu Z, Wang X, Carr M, Kim A, Gazal S, Mohammadi P, Wu L, Gusev A, Pirruccello J, Kachuri L, Mancuso N. Improved multi-ancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.15.24305836. [PMID: 38699369 PMCID: PMC11065034 DOI: 10.1101/2024.04.15.24305836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Multi-ancestry statistical fine-mapping of cis-molecular quantitative trait loci (cis-molQTL) aims to improve the precision of distinguishing causal cis-molQTLs from tagging variants. However, existing approaches fail to reflect shared genetic architectures. To solve this limitation, we present the Sum of Shared Single Effects (SuShiE) model, which leverages LD heterogeneity to improve fine-mapping precision, infer cross-ancestry effect size correlations, and estimate ancestry-specific expression prediction weights. We apply SuShiE to mRNA expression measured in PBMCs (n=956) and LCLs (n=814) together with plasma protein levels (n=854) from individuals of diverse ancestries in the TOPMed MESA and GENOA studies. We find SuShiE fine-maps cis-molQTLs for 16% more genes compared with baselines while prioritizing fewer variants with greater functional enrichment. SuShiE infers highly consistent cis-molQTL architectures across ancestries on average; however, we also find evidence of heterogeneity at genes with predicted loss-of-function intolerance, suggesting that environmental interactions may partially explain differences in cis-molQTL effect sizes across ancestries. Lastly, we leverage estimated cis-molQTL effect-sizes to perform individual-level TWAS and PWAS on six white blood cell-related traits in AOU Biobank individuals (n=86k), and identify 44 more genes compared with baselines, further highlighting its benefits in identifying genes relevant for complex disease risk. Overall, SuShiE provides new insights into the cis-genetic architecture of molecular traits.
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Affiliation(s)
- Zeyun Lu
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Xinran Wang
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Matthew Carr
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Artem Kim
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA
| | - Pejman Mohammadi
- Center for Immunity and Immunotherapies, Seattle Children’s Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa, Honolulu, HI, USA
| | - Alexander Gusev
- Harvard Medical School and Dana-Farber Cancer Institute, Boston, MA, USA
| | - James Pirruccello
- Division of Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nicholas Mancuso
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA
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26
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Shen J, Jiang L, Wang K, Wang A, Chen F, Newcombe PJ, Haiman CA, Conti DV. Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction. Genet Epidemiol 2024. [PMID: 38606643 DOI: 10.1002/gepi.22562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 02/27/2024] [Accepted: 03/27/2024] [Indexed: 04/13/2024]
Abstract
Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.
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Affiliation(s)
- Jiayi Shen
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Lai Jiang
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Kan Wang
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Anqi Wang
- Department of Population and Public Health Science, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Fei Chen
- Department of Population and Public Health Science, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Paul J Newcombe
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Christopher A Haiman
- Department of Population and Public Health Science, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - David V Conti
- Department of Population and Public Health Sciences, Division of Biostatistics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Department of Population and Public Health Science, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
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27
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Zhang Y, Lindström S, Kraft P, Liu Y. Genetic Risk, Health-Associated Lifestyle, and Risk of Early-onset Total Cancer and Breast Cancer. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.04.24305361. [PMID: 38633776 PMCID: PMC11023660 DOI: 10.1101/2024.04.04.24305361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Importance Early-onset cancer (diagnosed under 50 years of age) is associated with aggressive disease characteristics and its rising incidence is a global concern. The association between healthy lifestyle and early-onset cancer and whether it varies by common genetic variants is unknown. Objective To examine the associations between genetic risk, lifestyle, and risk of early-onset cancers. Design Setting and Participants We analyzed a prospective cohort of 66,308 white British participants who were under age 50 and free of cancer at baseline in the UK Biobank. Exposures Sex-specific composite total cancer polygenic risk scores (PRSs), a breast cancer-specific PRS, and sex-specific health-associated lifestyle scores (HLSs, which summarize smoking status, body mass index [males only], physical activity, alcohol consumption, and diet). Main Outcomes and Measures Hazard ratios (HRs) and 95% confidence intervals (CIs) for early-onset total and breast cancer. Results A total of 1,247 incident invasive early-onset cancer cases (female: 820, male: 427, breast: 386) were documented. In multivariable-adjusted analyses with 2-year latency, higher genetic risk (highest vs. lowest tertile of PRS) was associated with significantly increased risks of early-onset total cancer in females (HR, 95% CI: 1.85, 1.50-2.29) and males (1.94, 1.45-2.59) as well as early-onset breast cancer in females (3.06, 2.20-4.25). An unfavorable lifestyle (highest vs. lowest category of HLS) was associated with higher risk of total cancer and breast cancer in females across genetic risk categories; the association with total cancer was stronger in the highest genetic risk category than the lowest: HRs in females and men were 1.85 (1.02, 3.36), 3.27 (0.78, 13.72) in the highest genetic risk category and 1.15 (0.44, 2.98), 1.16 (0.39, 3.40) in the lowest. Conclusions and Relevance Both genetic and lifestyle factors were independently associated with early-onset total and breast cancer risk. Compared to those with low genetic risk, individuals with a high genetic risk may benefit more from adopting a healthy lifestyle in preventing early-onset cancer.
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Affiliation(s)
- Yin Zhang
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Peter Kraft
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yuxi Liu
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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28
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Wang L, Li X, Liu M, Zhou H, Shao J. Association between monocyte-to-lymphocyte ratio and prostate cancer in the U.S. population: a population-based study. Front Cell Dev Biol 2024; 12:1372731. [PMID: 38645410 PMCID: PMC11026607 DOI: 10.3389/fcell.2024.1372731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 03/21/2024] [Indexed: 04/23/2024] Open
Abstract
Introduction Monocyte-to-lymphocyte ratio (MLR) is a convenient and noninvasive inflammatory biomarker, and inflammation has been reported to be associated with prostate cancer (PCa). Our objective was to ascertain any possible correlation between PCa and MLR. Methods We utilized data from the 1999-2020 cycles of the National Health and Nutrition Examination Survey (NHANES) regarding MLR and PCa. The independent associations of MLR and other inflammatory biomarkers (platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), system inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)) with PCa was investigated using weighted multivariate logistic regression and generalized additive models. Receiver operating characteristic (ROC) curves were conducted to evaluate and contrast their diagnostic capabilities. Results The analysis we conducted comprised 25,367 persons in total. The mean MLR was 0.31 ± 0.14. The prevalence of PCa was 3.1%. A positive association was found between MLR and PCa (OR = 2.28; 95% CI: 1.44, 3.62). According to the interaction tests, age, body mass index (BMI), hypertension, diabetes, and smoking status did not significantly impact the relationship between MLR and PCa (all p for interaction >0.05). ROC analysis showed that MLR had a stronger discriminative ability and accuracy in predicting PCa than other inflammatory biomarkers (NLR, SII, AISI, PLR, and SIRI). Conclusion MLR might be better than other inflammatory biomarkers (NLR, SIRI, AISI, PLR, and SII) in predicting PCa. American adults who have elevated levels of MLR, NLR, PLR, SII, and AISI should be aware that they have a greater risk of PCa.
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Affiliation(s)
- Lanyu Wang
- Department of Urology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, China
| | - Xiaowan Li
- Department of Critical Care Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, China
| | - Min Liu
- Department of Critical Care Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, China
| | - Hongyi Zhou
- Department of Urology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu, China
| | - Jianfeng Shao
- Department of Urology, Wuxi No. 2 People’s Hospital (Jiangnan University Medical Center), Wuxi, Jiangsu, China
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29
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Wei GH, Dong D, Zhang P, Liu M, Wei Y, Wang Z, Xu W, Zhang Q, Zhu Y, Zhang Q, Yang X, Zhu J, Wang L. Combined SNPs sequencing and allele specific proteomics capture reveal functional causality underpinning the 2p25 prostate cancer susceptibility locus. RESEARCH SQUARE 2024:rs.3.rs-3943095. [PMID: 38645058 PMCID: PMC11030545 DOI: 10.21203/rs.3.rs-3943095/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Genome wide association studies (GWASs) have identified numerous risk loci associated with prostate cancer, yet unraveling their functional significance remains elusive. Leveraging our high-throughput SNPs-seq method, we pinpointed rs4519489 within the multi-ancestry GWAS-discovered 2p25 locus as a potential functional SNP due to its significant allelic differences in protein binding. Here, we conduct a comprehensive analysis of rs4519489 and its associated gene, NOL10, employing diverse cohort data and experimental models. Clinical findings reveal a synergistic effect between rs4519489 genotype and NOL10 expression on prostate cancer prognosis and severity. Through unbiased proteomics screening, we reveal that the risk allele A of rs4519489 exhibits enhanced binding to USF1, a novel oncogenic transcription factor (TF) implicated in prostate cancer progression and prognosis, resulting in elevated NOL10 expression. Furthermore, we elucidate that NOL10 regulates cell cycle pathways, fostering prostate cancer progression. The concurrent expression of NOL10 and USF1 correlates with aggressive prostate cancer characteristics and poorer prognosis. Collectively, our study offers a robust strategy for functional SNP screening and TF identification through high-throughput SNPs-seq and unbiased proteomics, highlighting the rs4519489-USF1-NOL10 regulatory axis as a promising biomarker or therapeutic target for clinical diagnosis and treatment of prostate cancer.
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Affiliation(s)
- Gong-Hong Wei
- Fudan University Shanghai Cancer Center & MOE Key Laboratory of Metabolism and Molecular Medicine and Department of Biochemistry and Molecular Biology of School Basic Medical Sciences, Shanghai Medi
| | - Dandan Dong
- Shanghai Medical College of Fudan University
| | - Peng Zhang
- Shanghai Medical College of Fudan University
| | - Mengqi Liu
- Shanghai Medical College of Fudan University
| | - Yu Wei
- Fudan Unversity Shanghai Cancer Center
| | - Zixian Wang
- Shanghai Medical College of Fudan University
| | - Wenjie Xu
- Shanghai Medical College of Fudan University
| | | | - Yao Zhu
- Fudan University Shanghai Cancer Center
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30
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Grinde KE, Browning BL, Reiner AP, Thornton TA, Browning SR. Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587682. [PMID: 38617337 PMCID: PMC11014513 DOI: 10.1101/2024.04.02.587682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/24/2024]
Abstract
Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.
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Affiliation(s)
- Kelsey E. Grinde
- Department of Mathematics, Statistics, and Computer Science, Macalester College, Saint Paul, Minnesota, 55105, USA
| | - Brian L. Browning
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington, 98195, USA
| | - Alexander P. Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, 98109, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, 98195, USA
| | - Timothy A. Thornton
- Regeneron Genetics Center, Tarrytown, New York, 10591, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, 98195, USA
| | - Sharon R. Browning
- Department of Biostatistics, University of Washington, Seattle, Washington, 98195, USA
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31
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Delgado D, Gillard M, Tong L, Demanelis K, Oliva M, Gleason KJ, Chernoff M, Chen L, Paner GP, Vander Griend D, Pierce BL. The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men. Cancer Epidemiol Biomarkers Prev 2024; 33:557-566. [PMID: 38294689 PMCID: PMC10990789 DOI: 10.1158/1055-9965.epi-23-0849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/29/2023] [Accepted: 01/29/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND American men of African ancestry (AA) have higher prostate cancer incidence and mortality rates compared with American men of European ancestry (EA). Differences in genetic susceptibility mechanisms may contribute to this disparity. METHODS To gain insights into the regulatory mechanisms of prostate cancer susceptibility variants, we tested the association between SNPs and DNA methylation (DNAm) at nearby CpG sites across the genome in benign and cancer prostate tissue from 74 AA and 74 EA men. Genome-wide SNP data (from benign tissue) and DNAm were generated using Illumina arrays. RESULTS Among AA men, we identified 6,298 and 2,641 cis-methylation QTLs (meQTL; FDR of 0.05) in benign and tumor tissue, respectively, with 6,960 and 1,700 detected in EA men. We leveraged genome-wide association study (GWAS) summary statistics to identify previously reported prostate cancer GWAS signals likely to share a common causal variant with a detected meQTL. We identified nine GWAS-meQTL pairs with strong evidence of colocalization (four in EA benign, three in EA tumor, two in AA benign, and three in AA tumor). Among these colocalized GWAS-meQTL pairs, we identified colocalizing expression quantitative trait loci (eQTL) impacting four eGenes with known roles in tumorigenesis. CONCLUSIONS These findings highlight epigenetic regulatory mechanisms by which prostate cancer-risk SNPs can modify local DNAm and/or gene expression in prostate tissue. IMPACT Overall, our findings showed general consistency in the meQTL landscape of AA and EA men, but meQTLs often differ by tissue type (normal vs. cancer). Ancestry-based linkage disequilibrium differences and lack of AA representation in GWAS decrease statistical power to detect colocalization for some regions.
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Affiliation(s)
- Dayana Delgado
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Marc Gillard
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Lin Tong
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Kathryn Demanelis
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15261
- UPMC Hillman Cancer Center, Pittsburgh, PA 15232
| | - Meritxell Oliva
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
- Genomics Research Center, AbbVie, North Chicago, IL 60064
| | | | - Meytal Chernoff
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
- Interdisciplinary Scientist Training Program, University of Chicago, Chicago, IL, USA
- University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | - Lin Chen
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
| | - Gladell P. Paner
- Department of Pathology, University of Chicago, Chicago, IL 60637
| | - Donald Vander Griend
- Department of Pathology, University of Illinois at Chicago, Chicago, IL 60607
- The University of Illinois Cancer Center, Chicago, IL
| | - Brandon L. Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637
- Department of Human Genetics, University of Chicago, Chicago, IL 60615
- Comprehensive Cancer Center, University of Chicago, Chicago, IL 60637
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32
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Saunders EJ, Dadaev T, Brook MN, Wakerell S, Govindasami K, Rageevakumar R, Hussain N, Osborne A, Keating D, Lophatananon A, Muir KR, Darst BF, Conti DV, Haiman CA, Antoniou AC, Eeles RA, Kote-Jarai Z. Identification of Genes with Rare Loss of Function Variants Associated with Aggressive Prostate Cancer and Survival. Eur Urol Oncol 2024; 7:248-257. [PMID: 38458890 DOI: 10.1016/j.euo.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/10/2024] [Accepted: 02/09/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Prostate cancer (PrCa) is a substantial cause of mortality among men globally. Rare germline mutations in BRCA2 have been validated robustly as increasing risk of aggressive forms with a poorer prognosis; however, evidence remains less definitive for other genes. OBJECTIVE To detect genes associated with PrCa aggressiveness, through a pooled analysis of rare variant sequencing data from six previously reported studies in the UK Genetic Prostate Cancer Study (UKGPCS). DESIGN, SETTING, AND PARTICIPANTS We accumulated a cohort of 6805 PrCa cases, in which a set of ten candidate genes had been sequenced in all samples. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS We examined the association between rare putative loss of function (pLOF) variants in each gene and aggressive classification (defined as any of death from PrCa, metastatic disease, stage T4, or both stage T3 and Gleason score ≥8). Secondary analyses examined staging phenotypes individually. Cox proportional hazards modelling and Kaplan-Meier survival analyses were used to further examine the relationship between mutation status and survival. RESULTS AND LIMITATIONS We observed associations between PrCa aggressiveness and pLOF mutations in ATM, BRCA2, MSH2, and NBN (odds ratio = 2.67-18.9). These four genes and MLH1 were additionally associated with one or more secondary analysis phenotype. Carriers of germline mutations in these genes experienced shorter PrCa-specific survival (hazard ratio = 2.15, 95% confidence interval 1.79-2.59, p = 4 × 10-16) than noncarriers. CONCLUSIONS This study provides further support that rare pLOF variants in specific genes are likely to increase aggressive PrCa risk and may help define the panel of informative genes for screening and treatment considerations. PATIENT SUMMARY By combining data from several previous studies, we have been able to enhance knowledge regarding genes in which inherited mutations would be expected to increase the risk of more aggressive PrCa. This may, in the future, aid in the identification of men at an elevated risk of dying from PrCa.
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Affiliation(s)
- Edward J Saunders
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Tokhir Dadaev
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Mark N Brook
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Sarah Wakerell
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Koveela Govindasami
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Reshma Rageevakumar
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Nafisa Hussain
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Andrea Osborne
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Diana Keating
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | | | - Kenneth R Muir
- Division of Population Health, University of Manchester, Manchester, UK
| | - Burcu F Darst
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA; Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - David V Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Antonis C Antoniou
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Rosalind A Eeles
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
| | - Zsofia Kote-Jarai
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.
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33
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Timmins IR, Dudbridge F. Bayesian approach to assessing population differences in genetic risk of disease with application to prostate cancer. PLoS Genet 2024; 20:e1011212. [PMID: 38630784 PMCID: PMC11023298 DOI: 10.1371/journal.pgen.1011212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 03/07/2024] [Indexed: 04/19/2024] Open
Abstract
Population differences in risk of disease are common, but the potential genetic basis for these differences is not well understood. A standard approach is to compare genetic risk across populations by testing for mean differences in polygenic scores, but existing studies that use this approach do not account for statistical noise in effect estimates (i.e., the GWAS betas) that arise due to the finite sample size of GWAS training data. Here, we show using Bayesian polygenic score methods that the level of uncertainty in estimates of genetic risk differences across populations is highly dependent on the GWAS training sample size, the polygenicity (number of causal variants), and genetic distance (FST) between the populations considered. We derive a Wald test for formally assessing the difference in genetic risk across populations, which we show to have calibrated type 1 error rates under a simplified assumption that all SNPs are independent, which we achieve in practise using linkage disequilibrium (LD) pruning. We further provide closed-form expressions for assessing the uncertainty in estimates of relative genetic risk across populations under the special case of an infinitesimal genetic architecture. We suggest that for many complex traits and diseases, particularly those with more polygenic architectures, current GWAS sample sizes are insufficient to detect moderate differences in genetic risk across populations, though more substantial differences in relative genetic risk (relative risk > 1.5) can be detected. We show that conventional approaches that do not account for sampling error from the training sample, such as using a simple t-test, have very high type 1 error rates. When applying our approach to prostate cancer, we demonstrate a higher genetic risk in African Ancestry men, with lower risk in men of European followed by East Asian ancestry.
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Affiliation(s)
- Iain R. Timmins
- Department of Population Health Sciences, University of Leicester, Leicester, United Kingdom
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom
- Statistical Innovation, AstraZeneca, Cambridge, United Kingdom
| | | | - Frank Dudbridge
- Department of Population Health Sciences, University of Leicester, Leicester, United Kingdom
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34
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Liu Y, Ritchie SC, Teo SM, Ruuskanen MO, Kambur O, Zhu Q, Sanders J, Vázquez-Baeza Y, Verspoor K, Jousilahti P, Lahti L, Niiranen T, Salomaa V, Havulinna AS, Knight R, Méric G, Inouye M. Integration of polygenic and gut metagenomic risk prediction for common diseases. NATURE AGING 2024; 4:584-594. [PMID: 38528230 PMCID: PMC11031402 DOI: 10.1038/s43587-024-00590-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 02/13/2024] [Indexed: 03/27/2024]
Abstract
Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.
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Affiliation(s)
- Yang Liu
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Scott C Ritchie
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cambridge Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Shu Mei Teo
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Matti O Ruuskanen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Computing, University of Turku, Turku, Finland
| | - Oleg Kambur
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Qiyun Zhu
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA
| | - Jon Sanders
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
| | - Karin Verspoor
- School of Computing Technologies, RMIT University, Melbourne, Victoria, Australia
- School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland
| | - Teemu Niiranen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Division of Medicine, Turku University Hospital and University of Turku, Turku, Finland
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Aki S Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, University of Helsinki, Helsinki, Finland
| | - Rob Knight
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Guillaume Méric
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Cardiometabolic Health, University of Melbourne, Melbourne, Victoria, Australia
- Department of Cardiovascular Research, Translation and Implementation, La Trobe University, Melbourne, Victoria, Australia
- Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, Sweden
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia.
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- British Heart Foundation Cambridge Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
- The Alan Turing Institute, London, UK.
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Bau DT, Tsai CW, Chang WS, Yang JS, Liu TY, Lu HF, Wang YW, Tsai FJ. Genetic susceptibility to prostate cancer in Taiwan: A genome-wide association study. Mol Carcinog 2024; 63:617-628. [PMID: 38390760 DOI: 10.1002/mc.23676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/02/2023] [Accepted: 12/15/2023] [Indexed: 02/24/2024]
Abstract
We conducted the first genome-wide association study (GWAS) of prostate cancer (PCa) in Taiwan with 1844 cases and 80,709 controls. Thirteen independent single-nucleotide polymorphisms (SNPs) reached genome-wide significance (p < 5 × 10-8 ). Among these, three were distinct from previously identified loci: rs76072851 in CORO2B gene (15q23), odds ratio (OR) = 1.54, 95% confidence interval (CI), 1.36-1.76, p = 5.30 × 10-11 ; rs7837051, near two long noncoding RNA (lncRNA) genes, PRNCR1 and PCAT2 (8q24.21), OR = 1.41 (95% CI, 1.31-1.51), p = 8.77 × 10-21 ; and rs56339048, near an lncRNA gene, CASC8 (8q24.21), OR = 1.25 (95% CI, 1.16-1.35), p = 2.14 × 10-8 . We refined the lead SNPs for two previously identified SNPs in Taiwanese: rs13255059 (near CASC8), p = 9.02 × 10-43 , and rs1456315 (inside PRNCR1), p = 4.33 × 10-42 . We confirmed 35 out of 49 GWAS-identified East Asian PCa susceptibility SNPs. In addition, we identified two SNPs more specific to Taiwanese than East Asians: rs34295433 in LAMC1 (1q25.3) and rs6853490 in PDLIM5 (4q22.3). A weighted genetic risk score (GRS) was developed using the 40 validated SNPs and the area under the receiver-operating characteristic curve for the GRS to predict PCa was 0.67 (95% CI, 0.63-0.71). These identified SNPs provide valuable insights into the molecular mechanisms of prostate carcinogenesis in Taiwan and underscore the significant role of genetic susceptibility in regional differences in PCa incidence.
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Affiliation(s)
- Da-Tian Bau
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
- Terry Fox Cancer Research Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan
| | - Chia-Wen Tsai
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
- Terry Fox Cancer Research Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Wen-Shin Chang
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan
- Terry Fox Cancer Research Laboratory, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Jai-Sing Yang
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Ting-Yuan Liu
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Hsing-Fang Lu
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Yu-Wen Wang
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Fuu-Jen Tsai
- Human Genetics Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan
- Department of Medical Genetics, China Medical University Hospital, Taichung, Taiwan
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36
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Shah Y, Kulm S, Nauseef JT, Chen Z, Elemento O, Kensler KH, Sharaf RN. Benchmarking multi-ancestry prostate cancer polygenic risk scores in a real-world cohort. PLoS Comput Biol 2024; 20:e1011990. [PMID: 38598551 PMCID: PMC11034641 DOI: 10.1371/journal.pcbi.1011990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 04/22/2024] [Accepted: 03/11/2024] [Indexed: 04/12/2024] Open
Abstract
Prostate cancer is a heritable disease with ancestry-biased incidence and mortality. Polygenic risk scores (PRSs) offer promising advancements in predicting disease risk, including prostate cancer. While their accuracy continues to improve, research aimed at enhancing their effectiveness within African and Asian populations remains key for equitable use. Recent algorithmic developments for PRS derivation have resulted in improved pan-ancestral risk prediction for several diseases. In this study, we benchmark the predictive power of six widely used PRS derivation algorithms, including four of which adjust for ancestry, against prostate cancer cases and controls from the UK Biobank and All of Us cohorts. We find modest improvement in discriminatory ability when compared with a simple method that prioritizes variants, clumping, and published polygenic risk scores. Our findings underscore the importance of improving upon risk prediction algorithms and the sampling of diverse cohorts.
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Affiliation(s)
- Yajas Shah
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York City, New York, United States of America
| | - Scott Kulm
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York City, New York, United States of America
| | - Jones T. Nauseef
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Medicine—Hematology and Medical Oncology, Weill Cornell Medicine, New York City, New York, United States of America
| | - Zhengming Chen
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, New York, United States of America
| | - Olivier Elemento
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York City, New York, United States of America
| | - Kevin H. Kensler
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, New York, United States of America
| | - Ravi N. Sharaf
- Englander Institute for Precision Medicine, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, New York, United States of America
- Department of Medicine–Gastroenterology and Hepatology, Weill Cornell Medicine, New York City, New York, United States of America
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Schwarzerova J, Hurta M, Barton V, Lexa M, Walther D, Provaznik V, Weckwerth W. A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools. Brief Bioinform 2024; 25:bbae240. [PMID: 38770718 PMCID: PMC11106636 DOI: 10.1093/bib/bbae240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 04/14/2024] [Accepted: 05/03/2024] [Indexed: 05/22/2024] Open
Abstract
Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.
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Affiliation(s)
- Jana Schwarzerova
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria
| | - Martin Hurta
- Department of Computer Systems, Faculty of Information Technology, Brno University of Technology, Brno 612 00, Czechia
| | - Vojtech Barton
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, Brno 62500, Czech Republic
| | - Matej Lexa
- Faculty of Informatics, Masaryk University, Botanicka 68a, Brno 60200, Czech Republic
| | - Dirk Walther
- Max-Planck-Institute of Molecular Plant Physiology, Potsdam 14476, Germany
| | - Valentine Provaznik
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 10, Brno 61600, Czechia
- Department of Physiology, Faculty of Medicine, Masaryk University, Brno 62500, Czech Republic
| | - Wolfram Weckwerth
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, University of Vienna, Vienna 1010, Austria
- Vienna Metabolomics Center (VIME), University of Vienna, Vienna 1010, Austria
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Chen Q, Zhu X, Hu Y, Chen Y, Dai R, Li J, Zhuang J, Lin Y, Zeng Y, You L, Zeng Y, Huang Q. A study on the impact of marital status on the survival status of prostate cancer patients based on propensity score matching. Sci Rep 2024; 14:6162. [PMID: 38485743 PMCID: PMC10940582 DOI: 10.1038/s41598-024-56145-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 03/01/2024] [Indexed: 03/18/2024] Open
Abstract
Marital status is an independent prognostic factor for survival in many types of cancers, but its prognostic impact on patients with prostate cancer (PCa) has not been established. The aim of this study was to explore the independent prognostic factors of PCa and to investigate the effect of marital status on survival outcomes in patients with different stratified by PCa. Using the surveillance, epidemiology, and end results (SEER) database, we collected data on 584,655 PCa patients diagnosed between 1975 and 2019. Marital status was classified as married, divorced, widowed, and single. We used the Kaplan-Meier analysis and single multivariate Cox proportional hazards regression analysis to determine the effect of marital status on overall survival (OS) and cancer-specific survival (CSS). In addition, we performed subgroup analyses for different ages, Gleason score and PSA values, and performed a 1:1 propensity score matching (PSM) to reduce the impact of confounding factors to obtain more accurate matching results. According to our findings, marital status was an independent prognostic factor for the survival of PCa patients and a better prognosis of married patients. Moreover, we also found that factors such as age, TNM stage, Gleason score, and PSA concentration were also considered as important predictors for the prognosis of PCa. The above findings can facilitate early detection and treatment of high-risk PCa patients, prolong their life and reduce family burden.
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Affiliation(s)
- Qingquan Chen
- The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China
- The School of Public Health, Fujian Medical University, Fuzhou, 350108, Fujian, China
| | - Xi Zhu
- The School of Public Health, Fujian Medical University, Fuzhou, 350108, Fujian, China
| | - Yiming Hu
- The School of Public Health, Fujian Medical University, Fuzhou, 350108, Fujian, China
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Yao Chen
- The School of Public Health, Fujian Medical University, Fuzhou, 350108, Fujian, China
| | - Rongrong Dai
- The School of Public Health, Fujian Medical University, Fuzhou, 350108, Fujian, China
| | - Jiaxin Li
- Anyang University, Anyang, 455000, Henan, China
| | - Jiajing Zhuang
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, 350108, Fujian, China
| | - Yifei Lin
- The School of Clinical Medicine, Fujian Medical University, Fuzhou, 350108, Fujian, China
| | - Yifu Zeng
- Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China
| | - Liuxia You
- The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China
| | - Yanyu Zeng
- The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China.
| | - Qian Huang
- The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China.
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39
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Barnes DR, Tyrer JP, Dennis J, Leslie G, Bolla MK, Lush M, Aeilts AM, Aittomäki K, Andrieu N, Andrulis IL, Anton-Culver H, Arason A, Arun BK, Balmaña J, Bandera EV, Barkardottir RB, Berger LP, de Gonzalez AB, Berthet P, Białkowska K, Bjørge L, Blanco AM, Blok MJ, Bobolis KA, Bogdanova NV, Brenton JD, Butz H, Buys SS, Caligo MA, Campbell I, Castillo C, Claes KB, Colonna SV, Cook LS, Daly MB, Dansonka-Mieszkowska A, de la Hoya M, deFazio A, DePersia A, Ding YC, Domchek SM, Dörk T, Einbeigi Z, Engel C, Evans DG, Foretova L, Fortner RT, Fostira F, Foti MC, Friedman E, Frone MN, Ganz PA, Gentry-Maharaj A, Glendon G, Godwin AK, González-Neira A, Greene MH, Gronwald J, Guerrieri-Gonzaga A, Hamann U, Hansen TV, Harris HR, Hauke J, Heitz F, Hogervorst FB, Hooning MJ, Hopper JL, Huff CD, Huntsman DG, Imyanitov EN, Izatt L, Jakubowska A, James PA, Janavicius R, John EM, Kar S, Karlan BY, Kennedy CJ, Kiemeney LA, Konstantopoulou I, Kupryjanczyk J, Laitman Y, Lavie O, Lawrenson K, Lester J, Lesueur F, Lopez-Pleguezuelos C, Mai PL, Manoukian S, May T, McNeish IA, Menon U, Milne RL, Modugno F, Mongiovi JM, Montagna M, Moysich KB, Neuhausen SL, Nielsen FC, Noguès C, Oláh E, Olopade OI, Osorio A, Papi L, Pathak H, Pearce CL, Pedersen IS, Peixoto A, Pejovic T, Peng PC, Peshkin BN, Peterlongo P, Powell CB, Prokofyeva D, Pujana MA, Radice P, Rashid MU, Rennert G, Richenberg G, Sandler DP, Sasamoto N, Setiawan VW, Sharma P, Sieh W, Singer CF, Snape K, Sokolenko AP, Soucy P, Southey MC, Stoppa-Lyonnet D, Sutphen R, Sutter C, Teixeira MR, Terry KL, Thomsen LCV, Tischkowitz M, Toland AE, Van Gorp T, Vega A, Velez Edwards DR, Webb PM, Weitzel JN, Wentzensen N, Whittemore AS, Winham SJ, Wu AH, Yadav S, Yu Y, Ziogas A, Berchuck A, Couch FJ, Goode EL, Goodman MT, Monteiro AN, Offit K, Ramus SJ, Risch HA, Schildkraut JM, Thomassen M, Simard J, Easton DF, Jones MR, Chenevix-Trench G, Gayther SA, Antoniou AC, Pharoah PD. Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.29.24303243. [PMID: 38496424 PMCID: PMC10942532 DOI: 10.1101/2024.02.29.24303243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Background Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). Methods We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. Results Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). Conclusions This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.
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Affiliation(s)
- Daniel R. Barnes
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jonathan P. Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Goska Leslie
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Amber M. Aeilts
- Department of Internal Medicine, Division of Human Genetics, The Ohio State University, Columbus, OH, USA
| | - Kristiina Aittomäki
- Department of Clinical Genetics, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Nadine Andrieu
- Inserm U900, Paris, France
- Institut Curie, Paris, France
- Mines ParisTech, Fontainebleau, France
- PSL Research University, Paris, France
| | - Irene L. Andrulis
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
| | - Hoda Anton-Culver
- Department of Epidemiology, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Adalgeir Arason
- Department of Pathology, Landspitali - the National University Hospital of Iceland, Reykjavik, Iceland
- BMC (Biomedical Centre), Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Banu K. Arun
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Judith Balmaña
- Hereditary Cancer Genetics Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain
- Department of Medical Oncology, University Hospital of Vall d’Hebron, Barcelona, Spain
| | - Elisa V. Bandera
- Cancer Prevention and Control Program, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Rosa B. Barkardottir
- Department of Pathology, Landspitali - the National University Hospital of Iceland, Reykjavik, Iceland
- BMC (Biomedical Centre), Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Lieke P.V. Berger
- University Medical Center Groningen, Department of Genetics, University of Groningen, Groningen, The Netherlands
| | | | - Pascaline Berthet
- Département de Biopathologie, Centre François Baclesse, Caen, France
| | - Katarzyna Białkowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Line Bjørge
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Amie M. Blanco
- Cancer Genetics and Prevention Program, University of California San Francisco, San Francisco, CA, USA
| | - Marinus J. Blok
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Kristie A. Bobolis
- City of Hope Clinical Cancer Genetics Community Research Network, Duarte, CA, USA
| | - Natalia V. Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - James D. Brenton
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Henriett Butz
- Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary
- National Tumour Biology Laboratory, National Institute of Oncology, Budapest, Hungary
- Department of Oncology Biobank, National Institute of Oncology, Budapest, Hungary
| | - Saundra S. Buys
- Department of Medicine, Huntsman Cancer Institute, University of Utah Health, Salt Lake City, UT, USA
| | | | - Ian Campbell
- Cancer Genetics Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Carmen Castillo
- Hereditary Cancer Program, IDIBELL (Bellvitge Biomedical Research Institute), Catalan Institute of Oncology, Barcelona, Spain
| | - Kathleen B.M. Claes
- Centre for Medical Genetics, Ghent University, Gent, Belgium
- Department of Biomolecular Medicine, University of Ghent, Ghent, Belgium
- Cancer Research Institute Ghent, Ghent, Belgium
| | | | - EMBRACE Collaborators
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Sarah V. Colonna
- Department of Internal Medicine, Huntsman Cancer Institute, University of Utah Health, Salt Lake City, UT, USA
| | - Linda S. Cook
- Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, CO, USA
| | - Mary B. Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Agnieszka Dansonka-Mieszkowska
- Department of Pathology and Laboratory Medicine, Institute of Oncology and Maria Sklodowska-Curie Cancer Center, Warsaw, Poland
| | - Miguel de la Hoya
- Molecular Oncology Laboratory, CIBERONC, Hospital Clinico San Carlos, IdISSC (Instituto de Investigación Sanitaria del Hospital Clínico San Carlos), Madrid, Spain
| | - Anna deFazio
- Centre for Cancer Research, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia
- Department of Gynaecological Oncology, Westmead Hospital, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, New South Wales, Australia
| | - Allison DePersia
- Center for Medical Genetics, NorthShore University HealthSystem, Evanston, IL, USA
- The University of Chicago Pritzker School of Medicine, Chicago, IL, USA
| | - Yuan Chun Ding
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Susan M. Domchek
- Basser Center for BRCA, Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Zakaria Einbeigi
- Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
| | - D. Gareth Evans
- Genomic Medicine, Division of Evolution and Genomic Sciences, The University of Manchester, Manchester Academic Health Science Centre, Manchester Universities Foundation Trust, St. Mary’s Hospital, Manchester, UK
- Genomic Medicine, North West Genomics hub, Manchester Academic Health Science Centre, Manchester Universities Foundation Trust, St. Mary’s Hospital, Manchester, UK
| | - Lenka Foretova
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Renée T. Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway
| | - Florentia Fostira
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research ‘Demokritos’, Athens, Greece
| | | | - Eitan Friedman
- Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel
- The Susanne Levy Gertner Oncogenetics Unit, Chaim Sheba Medical Center, Ramat Gan, Israel
- Assuta Medical Center, Tel-Aviv, Israel
| | - Megan N. Frone
- National Cancer Institute, Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Patricia A. Ganz
- Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research, Jonsson Comprehensive Cancer Centre, UCLA, Los Angeles, CA, USA
| | - Aleksandra Gentry-Maharaj
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, UK
| | - Gord Glendon
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
| | - Andrew K. Godwin
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS, USA
| | - Anna González-Neira
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre, Madrid, Spain
- Spanish Network on Rare Diseases, Madrid, Spain
| | - Mark H. Greene
- National Cancer Institute, Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA
| | - Jacek Gronwald
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Aliana Guerrieri-Gonzaga
- Division of Cancer Prevention and Genetics, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Thomas v.O. Hansen
- Department of Clinical Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Holly R. Harris
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Jan Hauke
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Florian Heitz
- Department of Gynecology and Gynecologic Oncology, Kliniken Essen-Mitte, Essen, Germany
| | - Frans B.L. Hogervorst
- Family Cancer Clinic, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, The Netherlands
| | - Maartje J. Hooning
- Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Chad D Huff
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - David G. Huntsman
- British Columbia’s Ovarian Cancer Research (OVCARE) Program, BC Cancer, Vancouver General Hospital, and University of British Columbia, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Obstetrics and Gynecology, University of British Columbia, Vancouver, BC, Canada
- Department of Molecular Oncology, BC Cancer Research Centre, Vancouver, BC, Canada
| | - Evgeny N. Imyanitov
- Department of Tumor Growth Biology, N.N. Petrov Institute of Oncology, St. Petersburg, Russia
| | - kConFab Investigators
- Peter MacCallum Cancer Center, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Louise Izatt
- Clinical Genetics, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
- Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland
| | - Paul A. James
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Center and the Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Ramunas Janavicius
- State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania
- Hematology, Oncology and Transfusion Medicine Center, Oncogenetics Unit, Vilnius University Hospital Santaros Clinics, Vilnius, Lithuania
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Vilnius, Lithuania
| | - Esther M. John
- Department of Epidemiology & Population Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
- Department of Medicine (Oncology), Stanford University School of Medicine, Stanford University, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Siddhartha Kar
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Beth Y. Karlan
- David Geffen School of Medicine, Department of Obstetrics and Gynecology, University of California at Los Angeles, Los Angeles, CA, USA
- Women’s Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Catherine J. Kennedy
- Centre for Cancer Research, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia
- Department of Gynaecological Oncology, Westmead Hospital, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | | | - Irene Konstantopoulou
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research ‘Demokritos’, Athens, Greece
| | - Jolanta Kupryjanczyk
- Department of Pathology and Laboratory Medicine, Institute of Oncology and Maria Sklodowska-Curie Cancer Center, Warsaw, Poland
| | - Yael Laitman
- The Susanne Levy Gertner Oncogenetics Unit, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Ofer Lavie
- Technion-Israel Institute of Technology, Haifa, Israel
- Carmel Medical Center, Haifa, Israel
| | - Kate Lawrenson
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Women’s Cancer Program at the Samuel Oschin Cancer Institute Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jenny Lester
- David Geffen School of Medicine, Department of Obstetrics and Gynecology, University of California at Los Angeles, Los Angeles, CA, USA
- Women’s Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Fabienne Lesueur
- Inserm U900, Paris, France
- Institut Curie, Paris, France
- Mines ParisTech, Fontainebleau, France
- PSL Research University, Paris, France
| | - Carlos Lopez-Pleguezuelos
- Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain
- Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
- Escola de Doutoramento Internacional, Universidade de Santiago, Santiago de Compostela, Spain
| | - Phuong L. Mai
- Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Siranoush Manoukian
- Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Taymaa May
- Princess Margaret Cancer Center, Toronto, Canada
| | - Iain A. McNeish
- Division of Cancer and Ovarian Cancer Action Research Centre, Department Surgery & Cancer, Imperial College London, London, UK
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Usha Menon
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London, UK
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Francesmary Modugno
- Womens Cancer Research Center, Magee-Womens Research Institute and Hillman Cancer Center, Pittsburgh, PA, USA
- Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jennifer M. Mongiovi
- Department of Obstetrics and Gynecology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Marco Montagna
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV - IRCCS, Padua, Italy
| | | | - Susan L. Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Finn C. Nielsen
- Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Catherine Noguès
- Département d’Anticipation et de Suivi des Cancers, Oncogénétique Clinique, Institut Paoli-Calmettes, Marseille, France
- Aix Marseille Université, INSERM, IRD, SESSTIM, Marseille, France
| | - Edit Oláh
- Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary
| | | | - Ana Osorio
- Spanish Network on Rare Diseases, Madrid, Spain
- Familial Cancer Clinical Unit, Human Cancer Genetics Programme, Madrid, Spain
| | - Laura Papi
- Department of Experimental and Clinical Biomedical Sciences ‘Mario Serio’, Medical Genetics Unit, University of Florence, Florence, Italy
| | - Harsh Pathak
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS, USA
| | - Celeste L. Pearce
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Inge S. Pedersen
- Molecular Diagnostics, Aalborg University Hospital, Aalborg, Denmark
- Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Ana Peixoto
- Department of Laboratory Genetics, Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
| | - Tanja Pejovic
- Department of Obstetrics & Gynecology, Providence Medical Center, Medford, OR, USA
- Providence Cancer Center, Medford, OR, USA
| | - Pei-Chen Peng
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Beth N. Peshkin
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
- Jess and Mildred Fisher Center for Hereditary Cancer and Clinical Genomics Research, Georgetown University, Washington, DC, USA
| | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM - the FIRC Institute of Molecular Oncology, Milan, Italy
| | - C. Bethan Powell
- Hereditary Cancer Program, Kaiser Permanente Northern California, San Francisco, CA, USA
| | | | - Miquel Angel Pujana
- ProCURE, IDIBELL (Bellvitge Biomedical Research Institute), Catalan Institute of Oncology, Barcelona, Spain
- ProCURE, IDIBGI (Girona Biomedical Research Institute), Catalan Institute of Oncology, Girona, Spain
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Muhammad U. Rashid
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Centre (SKMCH & RC), Lahore, Pakistan
| | - Gad Rennert
- Technion-Israel Institute of Technology, Haifa, Israel
- The Association for Promotion of Research in Precision Medicine, Haifa, Israel
| | - George Richenberg
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Dale P. Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Rockville, MD, USA
| | - Naoko Sasamoto
- Department of Obstetrics and Gynecology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Obstetrics, Gynecology and Reproductive Biology, Harvard Medical School, Boston, MA, USA
| | - Veronica W. Setiawan
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Priyanka Sharma
- Department of Internal Medicine, Division of Medical Oncology, University of Kansas Medical Center, Westwood, KS, USA
| | - Weiva Sieh
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Christian F. Singer
- Dept of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Katie Snape
- Medical Genetics Unit, St George’s, University of London, London, UK
| | - Anna P. Sokolenko
- Department of Tumor Growth Biology, N.N. Petrov Institute of Oncology, St. Petersburg, Russia
| | - Penny Soucy
- Genomics Center, Centre Hospitalier Universitaire de Québec – Université Laval Research Center, Québec City, QC, Canada
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Parkville, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, East Melbourne, Victoria, Australia
| | - Dominique Stoppa-Lyonnet
- Genetics Department, Institut Curie, Paris, France
- Unité INSERM U830, Paris, France
- Université Paris Cité, Paris, France
| | - Rebecca Sutphen
- Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Christian Sutter
- Institute of Human Genetics, University Hospital Heidelberg, Heidelberg, Germany
| | - Manuel R. Teixeira
- Department of Laboratory Genetics, Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
- Department of Pathology and Molecular Immunology, School of Medicine and Biomedical Sciences (ICBAS), University of Porto, Porto, Portugal
| | - Kathryn L. Terry
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Liv Cecilie V. Thomsen
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Medical Birth Registry of Norway, Norwegian Institute of Public Health, Norway
| | - Marc Tischkowitz
- Program in Cancer Genetics, Departments of Human Genetics and Oncology, McGill University, Montréal, QC, Canada
- Department of Medical Genetics, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Amanda E. Toland
- Department of Internal Medicine, Division of Human Genetics, The Ohio State University, Columbus, OH, USA
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH, USA
| | - Toon Van Gorp
- Division of Gynecologic Oncology, University Hospital Leuven, Leuven, Belgium
- Leuven Cancer Institute, University of Leuven, Leuven, Belgium
| | - Ana Vega
- Fundación Pública Galega de Medicina Xenómica, Santiago de Compostela, Spain
- Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Digna R. Velez Edwards
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Penelope M. Webb
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Alice S. Whittemore
- Department of Epidemiology & Population Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Stacey J. Winham
- Department of Quantitative Health Sciences, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Anna H. Wu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Yao Yu
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Argyrios Ziogas
- Department of Epidemiology, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Andrew Berchuck
- Department of Gynecologic Oncology, Duke University Hospital, Durham, NC, USA
| | - Fergus J. Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Ellen L. Goode
- Department of Quantitative Health Sciences, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Marc T. Goodman
- Samuel Oschin Comprehensive Cancer Institute, Cancer Prevention and Genetics Program, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alvaro N. Monteiro
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Kenneth Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
- AnaNeo Therapeutics, New York, NY, USA
| | - Susan J. Ramus
- School of Clinical Medicine, Faculty of Medicine and Health, University of NSW Sydney, Sydney, New South Wales, Australia
- Adult Cancer Program, Lowy Cancer Research Centre, University of NSW Sydney, Sydney, New South Wales, Australia
| | - Harvey A. Risch
- Chronic Disease Epidemiology, Yale School of Medicine, New Haven, CT, USA
| | | | - Mads Thomassen
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
- Clinical Genome Center, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jacques Simard
- Genomics Center, Centre Hospitalier Universitaire de Québec – Université Laval Research Center, Québec City, QC, Canada
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Québec City, QC, Canada
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Michelle R. Jones
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Georgia Chenevix-Trench
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Simon A. Gayther
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Antonis C. Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul D.P. Pharoah
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
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Chen Y, Xie Y, Ci H, Cheng Z, Kuang Y, Li S, Wang G, Qi Y, Tang J, Liu D, Li W, Yang Y. Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants. BMC Med 2024; 22:90. [PMID: 38433226 PMCID: PMC10910673 DOI: 10.1186/s12916-024-03272-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/22/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND While circulating metabolites have been increasingly linked to cancer risk, the causality underlying these associations remains largely uninterrogated. METHODS We conducted a comprehensive 2-sample Mendelian randomization (MR) study to evaluate the potential causal relationship between 913 plasma metabolites and the risk of seven cancers among European-ancestry individuals. Data on variant-metabolite associations were obtained from a genome-wide association study (GWAS) of plasma metabolites among 14,296 subjects. Data on variant-cancer associations were gathered from large-scale GWAS consortia for breast (N = 266,081), colorectal (N = 185,616), lung (N = 85,716), ovarian (N = 63,347), prostate (N = 140,306), renal cell (N = 31,190), and testicular germ cell (N = 28,135) cancers. MR analyses were performed with the inverse variance-weighted (IVW) method as the primary strategy to identify significant associations at Bonferroni-corrected P < 0.05 for each cancer type separately. Significant associations were subjected to additional scrutiny via weighted median MR, Egger regression, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and reverse MR analyses. Replication analyses were performed using an independent dataset from a plasma metabolite GWAS including 8,129 participants of European ancestry. RESULTS We identified 94 significant associations, suggesting putative causal associations between 66 distinct plasma metabolites and the risk of seven cancers. Remarkably, 68.2% (45) of these metabolites were each associated with the risk of a specific cancer. Among the 66 metabolites, O-methylcatechol sulfate and 4-vinylphenol sulfate demonstrated the most pronounced positive and negative associations with cancer risk, respectively. Genetically proxied plasma levels of these two metabolites were significantly associated with the risk of lung cancer and renal cell cancer, with an odds ratio and 95% confidence interval of 2.81 (2.33-3.37) and 0.49 (0.40-0.61), respectively. None of these 94 associations was biased by weak instruments, horizontal pleiotropy, or reverse causation. Further, 64 of these 94 were eligible for replication analyses, and 54 (84.4%) showed P < 0.05 with association patterns consistent with those shown in primary analyses. CONCLUSIONS Our study unveils plausible causal relationships between 66 plasma metabolites and cancer risk, expanding our understanding of the role of circulating metabolites in cancer genetics and etiology. These findings hold promise for enhancing cancer risk assessment and prevention strategies, meriting further exploration.
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Affiliation(s)
- Yaxin Chen
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yufang Xie
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Hang Ci
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Zhengpei Cheng
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, 560 Ray C. Hunt Dr., Rm 4408, Charlottesville, VA, USA
| | - Yongjie Kuang
- Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Shuqing Li
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Gang Wang
- Innovation Laboratory for Precision Diagnostics, Precision Medicine Research Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yawen Qi
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Jun Tang
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Dan Liu
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Weimin Li
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China.
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Yaohua Yang
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, 560 Ray C. Hunt Dr., Rm 4408, Charlottesville, VA, USA.
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Yang J, Xiong X, Zheng W, Liao X, Xu H, Yang L, Wei Q. Evaluation of Survival Outcomes Among Black and White Patients with Metastatic Castration-resistant Prostate Cancer: A Systematic Review and Meta-analysis. EUR UROL SUPPL 2024; 61:10-17. [PMID: 38384441 PMCID: PMC10879936 DOI: 10.1016/j.euros.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/12/2024] [Indexed: 02/23/2024] Open
Abstract
Context Data on racial disparities among patients with metastatic castration-resistant prostate cancer (mCRPC) are limited and there is no uniform conclusion on differences by race in this setting. Objective To provide the latest evidence on racial disparities in survival outcomes between Black and White patients receiving systemic therapies for mCRPC. Evidence acquisition Our study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. We systematically searched the PubMed, Web of Science, and Cochrane Library databases up to September 2023 to identify potentially relevant studies. Overall survival (OS) and progression-free survival (PFS) were the outcomes of interest. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were evaluated. Evidence synthesis Nine studies involving 9462 patients with mCRPC (2058 Black and 7404 White men) met the eligibility criteria and were included. Pooled estimates demonstrated significantly better OS for Black than for White men (HR 0.75, 95% CI 0.70-0.80; p < 0.0001). The results were similar in a subgroup of men receiving androgen receptor-targeted therapies (HR 0.72, 95% CI 0.66-0.78; p < 0.0001) and a subgroup of men receiving other treatments (HR 0.79, 95% CI 0.71-0.88; p < 0.0001). Likewise, significantly favorable PFS was observed for Black men receiving ARTs in comparison to their White counterparts (HR 0.84, 95% CI 0.71-0.99; p = 0.0373). Conclusions Overall, our meta-analysis of survival outcomes for men with mCRPC stratified by race revealed a significant survival benefit for Black men in comparison to their White counterparts, regardless of systemic therapeutic agent. Patient summary Both biological and nonbiological factors could account for racial differences in the efficacy of systemic treatments for metastatic prostate cancer that is resistant to hormone therapy. Our review provides the latest reliable evidence showing better survival outcomes for Black than for White men. The results will be helpful in further understanding the molecular mechanisms that might explain racial differences in this disease stage and in planning treatment.
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Affiliation(s)
| | | | | | - Xinyang Liao
- Department of Urology, Institute of Urology, Center of Biomedical Big Data and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Hang Xu
- Department of Urology, Institute of Urology, Center of Biomedical Big Data and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Lu Yang
- Department of Urology, Institute of Urology, Center of Biomedical Big Data and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Qiang Wei
- Department of Urology, Institute of Urology, Center of Biomedical Big Data and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
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Plym A, Madueke I, Naik S, Isabelle M, Conti DV, Haiman CA, Penney KL, Mucci LA, Khorasani R, Kibel AS. Combining magnetic resonance imaging with a multi-ancestry polygenic risk score to improve identification of clinically significant prostate cancer. JNCI Cancer Spectr 2024; 8:pkae014. [PMID: 38429995 PMCID: PMC10980589 DOI: 10.1093/jncics/pkae014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/06/2024] [Accepted: 02/26/2024] [Indexed: 03/03/2024] Open
Abstract
Multi-parametric magnetic resonance imaging (mpMRI) has emerged as an important tool for identifying clinically significant prostate cancer. We examined if the addition of a 400-variant multi-ancestry polygenic risk score (PRS) to mpMRI has the potential to improve identification. Based on data from 24 617 men from the Mass General Brigham Biobank, we identified 1243 men who underwent mpMRI. Men in the top PRS quartile were more likely to have clinically significant prostate cancer (47.1% vs 28.6% in the bottom PRS quartile, adjusted relative proportion 1.72 [95% CI = 1.35 to 2.19]). Both among men with a positive and a negative mpMRI, men in the top PRS quartile had the highest frequency of clinically significant cancer. In a constructed scenario for selecting men to undergo biopsy, use of the PRS lowered the frequency of missed clinically significant cancers from 9.1% to 5.9%. Our study provides initial support for using the PRS to improve identification of potentially lethal prostate cancer.
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Affiliation(s)
- Anna Plym
- Department of Urology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ikenna Madueke
- Department of Urology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sachin Naik
- Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Isabelle
- Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - David V Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kathryn L Penney
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rhamin Khorasani
- Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adam S Kibel
- Department of Urology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Lee KY, Beatson EL, Steinberg SM, Chau CH, Price DK, Figg WD. Bridging Health Disparities: a Genomics and Transcriptomics Analysis by Race in Prostate Cancer. J Racial Ethn Health Disparities 2024; 11:492-504. [PMID: 36810713 PMCID: PMC10686215 DOI: 10.1007/s40615-023-01534-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 01/28/2023] [Accepted: 02/03/2023] [Indexed: 02/23/2023]
Abstract
As the era of cancer genomics expands, disproportionate rates of prostate cancer incidence and mortality by race have demonstrated increasing relevance in clinical settings. While Black men are most particularly affected, as data has historically shown, the opposite is observed for Asian men, thus creating a basis for exploring genomic pathways potentially involved in mediating these opposing trends. Studies on racial differences are limited by sample size, but recent expanding collaborations between research institutions may improve these imbalances to enhance investigations on health disparities from the genomics front. In this study, we performed a race genomics analysis using GENIE v11, released in January 2022, to investigate mutation and copy number frequencies of select genes in both primary and metastatic patient tumor samples. Further, we investigate the TCGA race cohort to conduct an ancestry analysis and to identify differentially expressed genes highly upregulated in one race and subsequently downregulated in another. Our findings highlight pathway-oriented genetic mutation frequencies characterized by race, and further, we identify candidate gene transcripts that have differential expression between Black and Asian men.
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Affiliation(s)
- Kristi Y Lee
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Erica L Beatson
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Seth M Steinberg
- Biostatistics and Data Management Section, Office of the Clinical Director, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Cindy H Chau
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Douglas K Price
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - William D Figg
- Molecular Pharmacology Section, Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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Kensler KH, Johnson R, Morley F, Albrair M, Dickerman BA, Gulati R, Holt SK, Iyer HS, Kibel AS, Lee JR, Preston MA, Vassy JL, Wolff EM, Nyame YA, Etzioni R, Rebbeck TR. Prostate cancer screening in African American men: a review of the evidence. J Natl Cancer Inst 2024; 116:34-52. [PMID: 37713266 PMCID: PMC10777677 DOI: 10.1093/jnci/djad193] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/25/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023] Open
Abstract
BACKGROUND Prostate cancer is the most diagnosed cancer in African American men, yet prostate cancer screening regimens in this group are poorly guided by existing evidence, given underrepresentation of African American men in prostate cancer screening trials. It is critical to optimize prostate cancer screening and early detection in this high-risk group because underdiagnosis may lead to later-stage cancers at diagnosis and higher mortality while overdiagnosis may lead to unnecessary treatment. METHODS We performed a review of the literature related to prostate cancer screening and early detection specific to African American men to summarize the existing evidence available to guide health-care practice. RESULTS Limited evidence from observational and modeling studies suggests that African American men should be screened for prostate cancer. Consideration should be given to initiating screening of African American men at younger ages (eg, 45-50 years) and at more frequent intervals relative to other racial groups in the United States. Screening intervals can be optimized by using a baseline prostate-specific antigen measurement in midlife. Finally, no evidence has indicated that African American men would benefit from screening beyond 75 years of age; in fact, this group may experience higher rates of overdiagnosis at older ages. CONCLUSIONS The evidence base for prostate cancer screening in African American men is limited by the lack of large, randomized studies. Our literature search supported the need for African American men to be screened for prostate cancer, for initiating screening at younger ages (45-50 years), and perhaps screening at more frequent intervals relative to men of other racial groups in the United States.
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Affiliation(s)
- Kevin H Kensler
- Department of Population Health Sciences, Weill Cornell Medical Center, New York, NY, USA
| | - Roman Johnson
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
| | - Faith Morley
- Department of Population Health Sciences, Weill Cornell Medical Center, New York, NY, USA
| | - Mohamed Albrair
- Department of Global Health, University of Washington, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Barbra A Dickerman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Roman Gulati
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sarah K Holt
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Hari S Iyer
- Section of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Adam S Kibel
- Department of Urology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Jenney R Lee
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Mark A Preston
- Department of Urology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Jason L Vassy
- VA Boston Healthcare System, Boston, MA, USA
- Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Erika M Wolff
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Yaw A Nyame
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Ruth Etzioni
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Timothy R Rebbeck
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
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Gong J, Kim DM, De Hoedt AM, Bhowmick N, Figlin R, Kim HL, Sandler H, Theodorescu D, Posadas E, Freedland SJ. Disparities With Systemic Therapies for Black Men Having Advanced Prostate Cancer: Where Do We Stand? J Clin Oncol 2024; 42:228-236. [PMID: 37890125 PMCID: PMC10824384 DOI: 10.1200/jco.23.00949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 08/08/2023] [Accepted: 08/23/2023] [Indexed: 10/29/2023] Open
Abstract
PURPOSE Prostate cancer represents the most common cancer diagnosis in Black men and is the second leading cause of cancer death in this population. Multilevel disparities have been well-documented in Black men with prostate cancer and play a role in poorer survival outcomes when compared with White men with prostate cancer. In this review, we highlight the changing trend in disparities for systemic therapy outcomes in Black men diagnosed with metastatic prostate cancer. METHODS We reviewed data from real-world registries and prospective clinical trials with a particular focus on equal access settings to compare outcomes to systemic therapies between Black and White men with metastatic prostate cancer. RESULTS In metastatic prostate cancer, there is growing evidence to suggest that Black men may have similar, if not better, outcomes to systemic therapies than White men with advanced disease, as corroborated by prospective studies and clinical trials where health care delivery and follow-up are more likely to be standardized. CONCLUSION This review illustrates the importance of nonbiological drivers of racial disparities in Black men with advanced prostate cancer. Mitigating barriers to health care access and delivery as well as including participation in clinical trials will be pivotal to ongoing efforts to address disparities in systemic therapy outcomes for Black men with metastatic prostate cancer.
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Affiliation(s)
- Jun Gong
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Daniel M. Kim
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Amanda M. De Hoedt
- Urology Section, Department of Surgery, Veterans Affairs Health Care System, Durham, NC
| | - Neil Bhowmick
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Robert Figlin
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Hyung L. Kim
- Division of Urology, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Howard Sandler
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Dan Theodorescu
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Division of Urology, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Edwin Posadas
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Stephen J. Freedland
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Urology Section, Department of Surgery, Veterans Affairs Health Care System, Durham, NC
- Division of Urology, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA
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46
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Peters U, Tomlinson I. Utilizing Human Genetics to Develop Chemoprevention for Cancer-Too Good an Opportunity to be Missed. Cancer Prev Res (Phila) 2024; 17:7-12. [PMID: 38173394 DOI: 10.1158/1940-6207.capr-22-0523] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/20/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024]
Abstract
Large-scale genetic studies are reliably identifying many risk factors for disease in the general population. Several of these genetic risk factors encode potential drug targets, and genetics has already helped to introduce targeted agents for some diseases, an example being lipid-lowering drugs to reduce the incidence of cardiovascular disease. Multiple drugs have been developed to treat cancers based on somatic mutations and genomics, but in stark contrast, there seems to be a reluctance to use germline genetic data to develop drugs to prevent malignancy, despite the large numbers of people who could benefit, the potential for lowering cancer rates, and the widespread current use of non-pharmaceutical measures to reduce cancer risk factors such as tobacco, alcohol, and infectious diseases. We argue that concerted efforts for cancer prevention based on genetics, including genes influenced by common polymorphisms that modulate cancer risk, are urgently needed. There are enormous, yet underutilized, opportunities to develop novel targeted agents for chemoprevention of cancer based on human germline genetics. Such efforts are likely to require the support of a dedicated funding program by national and international agencies. See related commentary by Winham and Sherman, p. 13.
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Affiliation(s)
- Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Center and Department of Epidemiology, University of Washington, Seattle, Washington
| | - Ian Tomlinson
- Department of Oncology, University of Oxford, Oxford, United Kingdom
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47
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Borbiev T, Kohaar I, Petrovics G. Clinical Biofluid Assays for Prostate Cancer. Cancers (Basel) 2023; 16:165. [PMID: 38201592 PMCID: PMC10777952 DOI: 10.3390/cancers16010165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/11/2023] [Accepted: 12/25/2023] [Indexed: 01/12/2024] Open
Abstract
This mini review summarizes the currently available clinical biofluid assays for PCa. The second most prevalent cancer worldwide is PCa. PCa is a heterogeneous disease, with a large percentage of prostate tumors being indolent, and with a relatively slow metastatic potential. However, due to the high case numbers, the absolute number of PCa-related deaths is still high. In fact, it causes the second highest number of cancer deaths in American men. As a first step for the diagnosis of PCa, the PSA test has been widely used. However, it has low specificity, which results in a high number of false positives leading to overdiagnosis and overtreatment. Newer derivatives of the original PSA test, including the Food and Drug Administration (FDA)-approved 4K (four kallikreins) and the PHI (Prostate Health Index) blood tests, have higher specificities. Tissue-based PCa tests are problematic as biopsies are invasive and have limited accuracy due to prostate tumor heterogeneity. Liquid biopsies offer a minimally or non-invasive choice for the patients, while providing a more representative reflection of the spatial heterogeneity in the prostate. In addition to the abovementioned blood-based tests, urine is a promising source of PCa biomarkers, offering a supplementary avenue for early detection and improved tumor classification. Four urine-based PCa tests are either FDA- or CLIA-approved: PCA3 (PROGENSA), ExoDX Prostate Intelliscore, MiPS, and SelectMDx. We will discuss these urine-based, as well as the blood-based, clinical PCa tests in more detail. We also briefly discuss a few promising biofluid marker candidates (DNA methylation, micro-RNAs) which are not in clinical application. As no single assay is perfect, we envision that a combination of biomarkers, together with imaging, will become the preferred practice.
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Affiliation(s)
- Talaibek Borbiev
- Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD 20817, USA; (T.B.); (I.K.)
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD 20817, USA
| | - Indu Kohaar
- Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD 20817, USA; (T.B.); (I.K.)
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD 20817, USA
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA
| | - Gyorgy Petrovics
- Center for Prostate Disease Research, Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD 20817, USA; (T.B.); (I.K.)
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD 20817, USA
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48
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Zhang X, Wang Z, Huang S, He D, Yan W, Zhuang Q, Wang Z, Wang C, Tan Q, Liu Z, Yang T, Liu Y, Ren R, Li J, Butler W, Tang H, Wei GH, Li X, Wu D, Li Z. Active DHEA uptake in the prostate gland correlates with aggressive prostate cancer. J Clin Invest 2023; 133:e171199. [PMID: 38099500 PMCID: PMC10721157 DOI: 10.1172/jci171199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 10/10/2023] [Indexed: 12/18/2023] Open
Abstract
Strategies for patient stratification and early intervention are required to improve clinical benefits for patients with prostate cancer. Here, we found that active DHEA utilization in the prostate gland correlated with tumor aggressiveness at early disease stages, and 3βHSD1 inhibitors were promising for early intervention. [3H]-labeled DHEA consumption was traced in fresh prostatic biopsies ex vivo. Active DHEA utilization was more frequently found in patients with metastatic disease or therapy-resistant disease. Genetic and transcriptomic features associated with the potency of prostatic DHEA utilization were analyzed to generate clinically accessible approaches for patient stratification. UBE3D, by regulating 3βHSD1 homeostasis, was discovered to be a regulator of patient metabolic heterogeneity. Equilin suppressed DHEA utilization and inhibited tumor growth as a potent 3βHSD1 antagonist, providing a promising strategy for the early treatment of aggressive prostate cancer. Overall, our findings indicate that patients with active prostatic DHEA utilization might benefit from 3βHSD1 inhibitors as early intervention.
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Affiliation(s)
- Xuebin Zhang
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, and
| | - Zengming Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China
| | - Shengsong Huang
- Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Dongyin He
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, and
| | - Weiwei Yan
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, and
| | - Qian Zhuang
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, and
| | - Zixian Wang
- Fudan University Shanghai Cancer Center and MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, China
| | - Chenyang Wang
- Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Qilong Tan
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, and
| | - Ziqun Liu
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, and
| | - Tao Yang
- Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ying Liu
- Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Ruobing Ren
- Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Fudan University, Shanghai, China
- School of Medicine, The Chinese University of Hong Kong, Shenzhen, China
| | - Jing Li
- Department of Bioinformatics, Center for Translational Medicine, Second Military Medical University, Shanghai, China
| | - William Butler
- Department of Pathology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Gong-Hong Wei
- Fudan University Shanghai Cancer Center and MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, China
| | - Xin Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China
| | - Denglong Wu
- Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Zhenfei Li
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, and
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China
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Hughley RW, Matejcic M, Song Z, Sheng X, Wan P, Xia L, Hart SN, Hu C, Yadav S, Lubmawa A, Kiddu V, Asiimwe F, Amanya C, Mutema G, Job K, Ssebakumba MK, Ingles SA, Hamilton AS, Couch FJ, Watya S, Conti DV, Darst BF, Haiman CA. Polygenic Risk Score Modifies Prostate Cancer Risk of Pathogenic Variants in Men of African Ancestry. CANCER RESEARCH COMMUNICATIONS 2023; 3:2544-2550. [PMID: 38014910 PMCID: PMC10720390 DOI: 10.1158/2767-9764.crc-23-0022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/17/2023] [Accepted: 11/17/2023] [Indexed: 11/29/2023]
Abstract
Prostate cancer risk is influenced by rare and common germline variants. We examined the aggregate association of rare germline pathogenic/likely pathogenic/deleterious (P/LP/D) variants in ATM, BRCA2, PALB2, and NBN with a polygenic risk score (PRS) on prostate cancer risk among 1,796 prostate cancer cases (222 metastatic) and 1,424 controls of African ancestry. Relative to P/LP/D non-carriers at average genetic risk (33%-66% of PRS), men with low (0%-33%) and high (66%-100%) PRS had Odds Ratios (ORs) for overall prostate cancer of 2.08 [95% confidence interval (CI) = 0.58-7.49] and 18.06 (95% CI = 4.24-76.84) among P/LP/D carriers and 0.57 (95% CI = 0.46-0.71) and 3.02 (95% CI = 2.53-3.60) among non-carriers, respectively. The OR for metastatic prostate cancer was 2.73 (95% CI = 0.24-30.54) and 28.99 (95% CI = 4.39-191.43) among P/LP/D carriers and 0.54 (95% CI = 0.31-0.95) and 3.22 (95% CI = 2.20-4.73) among non-carriers, for men with low and high PRS, respectively. Lifetime absolute risks of overall prostate cancer increased with PRS (low to high) from 9.8% to 51.5% in P/LP/D carriers and 5.5% to 23.9% in non-carriers. Lifetime absolute risks of metastatic prostate cancer increased with PRS from 1.9% to 18.1% in P/LP/D carriers and 0.3% to 2.2% in non-carriers These findings suggest that assessment of prostate cancer risk for rare variant carriers should include PRS status. SIGNIFICANCE These findings highlight the importance of considering rare and common variants to comprehensively assess prostate cancer risk in men of African ancestry.
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Affiliation(s)
- Raymond W. Hughley
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Marco Matejcic
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Ziwei Song
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Peggy Wan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Lucy Xia
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Steven N. Hart
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Chunling Hu
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | | | - Colline Amanya
- Makerere University College of Health Sciences, Kampala, Uganda
| | | | | | | | - Sue A. Ingles
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Ann S. Hamilton
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Fergus J. Couch
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Stephen Watya
- Uro Care, Kampala, Uganda
- Makerere University College of Health Sciences, Kampala, Uganda
| | - David V. Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Burcu F. Darst
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
- Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California
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50
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Armaos A, Serra F, Núñez-Carpintero I, Seo JH, Baca SC, Gustincich S, Valencia A, Freedman ML, Cirillo D, Giambartolomei C, Tartaglia GG. The PENGUIN approach to reconstruct protein interactions at enhancer-promoter regions and its application to prostate cancer. Nat Commun 2023; 14:8084. [PMID: 38057321 PMCID: PMC10700545 DOI: 10.1038/s41467-023-43767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 11/18/2023] [Indexed: 12/08/2023] Open
Abstract
We introduce Promoter-Enhancer-Guided Interaction Networks (PENGUIN), a method for studying protein-protein interaction (PPI) networks within enhancer-promoter interactions. PENGUIN integrates H3K27ac-HiChIP data with tissue-specific PPIs to define enhancer-promoter PPI networks (EPINs). We validated PENGUIN using cancer (LNCaP) and benign (LHSAR) prostate cell lines. Our analysis detected EPIN clusters enriched with the architectural protein CTCF, a regulator of enhancer-promoter interactions. CTCF presence was coupled with the prevalence of prostate cancer (PrCa) single nucleotide polymorphisms (SNPs) within the same EPIN clusters, suggesting functional implications in PrCa. Within the EPINs displaying enrichments in both CTCF and PrCa SNPs, we also show enrichment in oncogenes. We substantiated our identified SNPs through CRISPR/Cas9 knockout and RNAi screens experiments. Here we show that PENGUIN provides insights into the intricate interplay between enhancer-promoter interactions and PPI networks, which are crucial for identifying key genes and potential intervention targets. A dedicated server is available at https://penguin.life.bsc.es/ .
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Affiliation(s)
- Alexandros Armaos
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy
| | - François Serra
- Barcelona Supercomputing Center, Plaça Eusebi Güell, 1-3, 08034, Barcelona, Spain
- Josep Carreras Leukaemia Research Institute, Ctra de Can Ruti, Camí de les Escoles, 08916, Badalona, Barcelona, Spain
| | | | - Ji-Heui Seo
- Department of Medical Oncology, The Center for Functional Cancer Epigenetics, Dana Farber Cancer Institute, Boston, MA, 02215, USA
| | - Sylvan C Baca
- Department of Medical Oncology, The Center for Functional Cancer Epigenetics, Dana Farber Cancer Institute, Boston, MA, 02215, USA
| | - Stefano Gustincich
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Plaça Eusebi Güell, 1-3, 08034, Barcelona, Spain
- ICREA - Institució Catalana de Recerca I Estudis Avançats, Pg. Lluís Companys 23, 08010, Barcelona, Spain
| | - Matthew L Freedman
- Department of Medical Oncology, The Center for Functional Cancer Epigenetics, Dana Farber Cancer Institute, Boston, MA, 02215, USA
- Eli and Edythe L. Broad Institute, 415 Main St., Cambridge, MA, 02142, USA
| | - Davide Cirillo
- Barcelona Supercomputing Center, Plaça Eusebi Güell, 1-3, 08034, Barcelona, Spain.
| | - Claudia Giambartolomei
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy.
- Health Data Science Centre, Human Technopole, Milan, Italy.
| | - Gian Gaetano Tartaglia
- Istituto Italiano di Tecnologia, CHT@Erzelli, Via Enrico Melen 83, Building B, 7th floor, 16152, Genova, Italy.
- ICREA - Institució Catalana de Recerca I Estudis Avançats, Pg. Lluís Companys 23, 08010, Barcelona, Spain.
- Istituto Italiano di Tecnologia, CNLS@Sapienza, Viale Regina Elena, 00161, Rome, Italy.
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