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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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Spears C, Xu M, Shoben A, Dason S, Toland AE, Byrne L. Clinical features of prostate cancer by polygenic risk score. Fam Cancer 2024:10.1007/s10689-024-00369-0. [PMID: 38619781 DOI: 10.1007/s10689-024-00369-0] [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: 11/09/2023] [Accepted: 02/25/2024] [Indexed: 04/16/2024]
Abstract
Genome-wide association studies have identified more than 290 single nucleotide variants (SNVs) associated with prostate cancer. These SNVs can be combined to generate a Polygenic Risk Score (PRS), which estimates an individual's risk to develop prostate cancer. Identifying individuals at higher risk for prostate cancer using PRS could allow for personalized screening recommendations, improve current screening tools, and potentially result in improved survival rates, but more research is needed before incorporating them into clinical use. Our study aimed to investigate associations between PRS and clinical factors in affected individuals, including age of diagnosis, metastases, histology, International Society of Urological Pathology (ISUP) Grade Group (GG) and family history of prostate cancer, while taking into account germline genetic testing in known prostate cancer related genes. To evaluate the relationship between these clinical factors and PRS, a quantitative retrospective chart review of 250 individuals of European ancestry diagnosed with prostate cancer who received genetic counseling services at The Ohio State University's Genitourinary Cancer Genetics Clinic and a 72-SNV PRS through Ambry Genetics, was performed. We found significant associations between higher PRS and younger age of diagnosis (p = 0.002), lower frequency of metastases (p = 0.006), and having a first-degree relative diagnosed with prostate cancer (p = 0.024). We did not observe significant associations between PRS and ISUP GG, histology or a having a second-degree relative with prostate cancer. These findings provide insights into features associated with higher PRS, but larger multi-ancestral studies using PRS that are informative across populations are needed to understand its clinical utility.
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Affiliation(s)
- Christina Spears
- Division of Human Genetics, Department of Internal Medicine, College of Medicine, The Ohio State University, 2012 Kenny Road, Columbus, OH, 43212, USA.
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.
| | - Menglin Xu
- Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Abigail Shoben
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Shawn Dason
- Division of Urologic Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Amanda Ewart Toland
- Division of Human Genetics, Department of Internal Medicine, College of Medicine, The Ohio State University, 2012 Kenny Road, Columbus, OH, 43212, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Cancer Biology and Genetics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Lindsey Byrne
- Division of Human Genetics, Department of Internal Medicine, College of Medicine, The Ohio State University, 2012 Kenny Road, Columbus, OH, 43212, USA
- Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
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Duijn M, de Reijke TM, Barwari K, Hagens MJ, Rynja SP, Immerzeel J, Barentsz JO, Jager A. The association between patient and disease characteristics, and the risk of disease progression in patients with prostate cancer on active surveillance. World J Urol 2024; 42:87. [PMID: 38372786 DOI: 10.1007/s00345-024-04805-9] [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: 09/10/2023] [Accepted: 01/16/2024] [Indexed: 02/20/2024] Open
Abstract
PURPOSE The objective of this study was to identify and assess patient and disease characteristics associated with an increased risk of disease progression in men with prostate cancer on active surveillance. METHODS We studied patients with low-risk (ISUP GG1) or favorable intermediate-risk (ISUP GG2) PCa. All patients had at least one repeat biopsy. Disease progression was the primary outcome of this study, based on pathological upgrading. Univariate and multivariate Cox proportional hazard analyses were used to evaluate the association between covariates and disease progression. RESULTS In total, 240 men were included, of whom 198 (82.5%) were diagnosed with low-risk PCa and 42 (17.5%) with favorable intermediate-risk PCa. Disease progression was observed in 42.9% (103/240) of men. Index lesion > 10 mm (HR = 2.85; 95% CI 1.74-4.68; p < 0.001), MRI (m)T-stage 2b/2c (HR = 2.52; 95% CI 1.16-5.50; p = 0.02), highest PI-RADS score of 5 (HR 3.05; 95% CI 1.48-6.28; p = 0.002) and a higher PSA level (HR 1.06; 95% CI 1.01-1.11; p = 0.014) at baseline were associated with disease progression on univariate analysis. Multivariate analysis showed no significant baseline predictors of disease progression. CONCLUSION In AS patients with low-risk or favorable intermediate-risk PCa, diameter of index lesion, MRI (m)T-stage, height of the PI-RADS score and the PSA level at baseline are significant predictors of disease progression to first repeat biopsy.
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Affiliation(s)
- Matthijs Duijn
- Department of Urology, OLVG, PO Box 95500, 1090 HM, Amsterdam, The Netherlands.
- Andros Clinics, Arnhem, The Netherlands.
| | - Theo M de Reijke
- Andros Clinics, Arnhem, The Netherlands
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Kurdo Barwari
- Andros Clinics, Arnhem, The Netherlands
- Department of Urology, Netherlands Cancer Institute (NCI), Amsterdam, The Netherlands
| | - Marias J Hagens
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Department of Urology, Netherlands Cancer Institute (NCI), Amsterdam, The Netherlands
- Prostate Cancer Network the Netherlands, Amsterdam, The Netherlands
| | - Sybren P Rynja
- Department of Urology, Spaarne Gasthuis, Hoofddorp, The Netherlands
| | | | | | - Auke Jager
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
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Rebbeck T, Janivara R, Chen W, Hazra U, Baichoo S, Agalliu I, Kachambwa P, Simonti C, Brown L, Tambe S, Kim M, Harlemon M, Jalloh M, Muzondiwa D, Naidoo D, Ajayi O, Snyper N, Niang L, Diop H, Ndoye M, Mensah J, Darkwa-Abrahams A, Biritwum R, Adjei A, Adebiyi A, Shittu O, Ogunbiyi O, Adebayo S, Nwegbu M, Ajibola H, Oluwole O, Jamda M, Pentz A, Haiman C, Spies P, Van der Merwe A, Cook M, Chanock SJ, Berndt SI, Watya S, Lubwama A, Muchengeti M, Doherty S, Smyth N, Lounsbury D, Fortier B, Rohan T, Jacobson J, Neugut A, Hsing A, Gusev A, Aisuodionoe-Shadrach O, Joffe M, Adusei B, Gueye S, Fernandez P, McBride J, Andrews C, Petersen L, Lachance J. Heterogeneous genetic architectures and evolutionary genomics of prostate cancer in Sub-Saharan Africa. RESEARCH SQUARE 2023:rs.3.rs-3378303. [PMID: 37886553 PMCID: PMC10602179 DOI: 10.21203/rs.3.rs-3378303/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Men of African descent have the highest prostate cancer (CaP) incidence and mortality rates, yet the genetic basis of CaP in African men has been understudied. We used genomic data from 3,963 CaP cases and 3,509 controls recruited in Ghana, Nigeria, Senegal, South Africa, and Uganda, to infer ancestry-specific genetic architectures and fine-mapped disease associations. Fifteen independent associations at 8q24.21, 6q22.1, and 11q13.3 reached genome-wide significance, including four novel associations. Intriguingly, multiple lead SNPs are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of CaP differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African CaP associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Maxwell Nwegbu
- University of Abuja Teaching Hospital and Cancer Science Center
| | - Hafees Ajibola
- University of Abuja Teaching Hospital and Cancer Science Center
| | - Olabode Oluwole
- University of Abuja and University of Abuja Teaching Hospital
| | - Mustapha Jamda
- University of Abuja Teaching Hospital and Cancer Science Center
| | | | | | | | | | | | | | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda
| | | | | | - Mazvita Muchengeti
- National Institute for Communicable Diseases a Division of the National Health Laboratory Service
| | | | | | | | | | | | | | | | - Ann Hsing
- Stanford University School of Medicine
| | | | | | | | | | | | | | - Jo McBride
- Centre for Proteomic and Genomic Research
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5
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Koch S, Schmidtke J, Krawczak M, Caliebe A. Clinical utility of polygenic risk scores: a critical 2023 appraisal. J Community Genet 2023; 14:471-487. [PMID: 37133683 PMCID: PMC10576695 DOI: 10.1007/s12687-023-00645-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 03/31/2023] [Indexed: 05/04/2023] Open
Abstract
Since their first appearance in the context of schizophrenia and bipolar disorder in 2009, polygenic risk scores (PRSs) have been described for a large number of common complex diseases. However, the clinical utility of PRSs in disease risk assessment or therapeutic decision making is likely limited because PRSs usually only account for the heritable component of a trait and ignore the etiological role of environment and lifestyle. We surveyed the current state of PRSs for various diseases, including breast cancer, diabetes, prostate cancer, coronary artery disease, and Parkinson disease, with an extra focus upon the potential improvement of clinical scores by their combination with PRSs. We observed that the diagnostic and prognostic performance of PRSs alone is consistently low, as expected. Moreover, combining a PRS with a clinical score at best led to moderate improvement of the power of either risk marker. Despite the large number of PRSs reported in the scientific literature, prospective studies of their clinical utility, particularly of the PRS-associated improvement of standard screening or therapeutic procedures, are still rare. In conclusion, the benefit to individual patients or the health care system in general of PRS-based extensions of existing diagnostic or treatment regimens is still difficult to judge.
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Affiliation(s)
- Sebastian Koch
- Institut für Medizinische Informatik und Statistik, Christian-Albrechts-Universität zu Kiel, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel, Germany
| | - Jörg Schmidtke
- Amedes MVZ Wagnerstibbe, Hannover, Germany
- Institut für Humangenetik, Medizinische Hochschule Hannover, Hannover, Germany
| | - Michael Krawczak
- Institut für Medizinische Informatik und Statistik, Christian-Albrechts-Universität zu Kiel, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel, Germany
| | - Amke Caliebe
- Institut für Medizinische Informatik und Statistik, Christian-Albrechts-Universität zu Kiel, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel, Germany.
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6
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Ito S, Liu X, Ishikawa Y, Conti DD, Otomo N, Kote-Jarai Z, Suetsugu H, Eeles RA, Koike Y, Hikino K, Yoshino S, Tomizuka K, Horikoshi M, Ito K, Uchio Y, Momozawa Y, Kubo M, Kamatani Y, Matsuda K, Haiman CA, Ikegawa S, Nakagawa H, Terao C. Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects. Nat Commun 2023; 14:4863. [PMID: 37612283 PMCID: PMC10447511 DOI: 10.1038/s41467-023-39858-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 06/27/2023] [Indexed: 08/25/2023] Open
Abstract
Prostate cancer (PrCa) is the second most common cancer worldwide in males. While strongly warranted, the prediction of mortality risk due to PrCa, especially before its development, is challenging. Here, we address this issue by maximizing the statistical power of genetic data with multi-ancestry meta-analysis and focusing on binding sites of the androgen receptor (AR), which has a critical role in PrCa. Taking advantage of large Japanese samples ever, a multi-ancestry meta-analysis comprising more than 300,000 subjects in total identifies 9 unreported loci including ZFHX3, a tumor suppressor gene, and successfully narrows down the statistically finemapped variants compared to European-only studies, and these variants strongly enrich in AR binding sites. A polygenic risk scores (PRS) analysis restricting to statistically finemapped variants in AR binding sites shows among cancer-free subjects, individuals with a PRS in the top 10% have a strongly higher risk of the future death of PrCa (HR: 5.57, P = 4.2 × 10-10). Our findings demonstrate the potential utility of leveraging large-scale genetic data and advanced analytical methods in predicting the mortality of PrCa.
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Affiliation(s)
- Shuji Ito
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Bone and Joint Diseases, Yokohama, Japan
- Department of Orthopedic Surgery, Shimane University, Izumo, Japan
| | - Xiaoxi Liu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Yuki Ishikawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - David D Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Nao Otomo
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- Department of Orthopedic Surgery, School of Medicine, Keio University, Tokyo, Japan
| | | | - Hiroyuki Suetsugu
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- Department of Orthopedic Surgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Rosalind A Eeles
- The Institute of Cancer Research, London, UK
- Royal Marsden NHS Foundation Trust, London, UK
| | - Yoshinao Koike
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Keiko Hikino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Pharmacogenomics, Yokohama, Japan
| | - Soichiro Yoshino
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
- Department of Orthopedic Surgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kohei Tomizuka
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan
| | - Momoko Horikoshi
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Genomics of Diabetes and Metabolism, Yokohama, Japan
| | - Kaoru Ito
- RIKEN Center for Integrative Medical Sciences, The Cardiovascular Genomics and Informatics, Yokohama, Japan
| | - Yuji Uchio
- Department of Orthopedic Surgery, Shimane University, Izumo, Japan
| | - Yukihide Momozawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Genotyping Development, Yokohama, Japan
| | | | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Koichi Matsuda
- Institute of Medical Science, The University of Tokyo, Laboratory of Genome Technology, Human Genome Center, Tokyo, Japan
- Graduate School of Frontier Sciences, The University of Tokyo, Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Tokyo, Japan
| | - 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
| | - Shiro Ikegawa
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Bone and Joint Diseases, Yokohama, Japan
| | - Hidewaki Nakagawa
- RIKEN Center for Integrative Medical Sciences, Laboratory for Cancer Genomics, Yokohama, Japan
| | - Chikashi Terao
- RIKEN Center for Integrative Medical Sciences, The Laboratory for Statistical and Translational Genetics, Yokohama, Japan.
- Shizuoka General Hospital, The Clinical Research Center, Shizuoka, Japan.
- School of Pharmaceutical Sciences, University of Shizuoka, The Department of Applied Genetics, Shizuoka, Japan.
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7
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Mroczek M, Liu J, Sypniewski M, Pieńkowski T, Itrych B, Stojak J, Pronobis-Szczylik B, Stępień M, Kaja E, Dąbrowski M, Suchocki T, Wojtaszewska M, Zawadzki P, Mach A, Sztromwasser P, Król ZJ, Szyda J, Dobosz P. The cancer-risk variant frequency among Polish population reported by the first national whole-genome sequencing study. Front Oncol 2023; 13:1045817. [PMID: 36845707 PMCID: PMC9950741 DOI: 10.3389/fonc.2023.1045817] [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: 09/16/2022] [Accepted: 01/20/2023] [Indexed: 02/12/2023] Open
Abstract
Introduction Population-based cancer screening has raised many controversies in recent years, not only regarding the costs but also regarding the ethical nature and issues related to variant interpretation. Nowadays, genetic cancer screening standards are different in every country and usually encompass only individuals with a personal or family history of relevant cancer. Methods Here we performed a broad genetic screening for cancer-related rare germline variants on population data from the Thousand Polish Genomes database based on 1076 Polish unrelated individuals that underwent whole genome sequencing (WGS). Results We identified 19 551 rare variants in 806 genes related to oncological diseases, among them 89% have been located in non-coding regions. The combined BRCA1/BRCA2 pathogenic/likely pathogenic according to ClinVar allele frequency in the unselected population of 1076 Poles was 0.42%, corresponding to nine carriers. Discussion Altogether, on the population level, we found especially problematic the assessment of the pathogenicity of variants and the relation of ACMG guidelines to the population frequency. Some of the variants may be overinterpreted as disease-causing due to their rarity or lack of annotation in the databases. On the other hand, some relevant variants may have been overseen given that there is little pooled population whole genome data on oncology. Before population WGS screening will become a standard, further studies are needed to assess the frequency of the variants suspected to be pathogenic on the population level and with reporting of likely benign variants.
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Affiliation(s)
- Magdalena Mroczek
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland,*Correspondence: Magdalena Mroczek,
| | - Jakub Liu
- Biostatistics Group, Wrocław University of Environmental and Life Sciences, Wrocław, Poland
| | - Mateusz Sypniewski
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
| | - Tadeusz Pieńkowski
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland,Postgraduate Medical Education Center, Warsaw, Poland
| | - Bartosz Itrych
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
| | - Joanna Stojak
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland,Department of Experimental Embryology, Institute of Genetics and Animal Biotechnology, Polish Academy of Science, Jastrzębiec, Poland
| | | | - Maria Stępień
- Department of Sports Medicine, Doctoral School, Medical University of Lublin, Lublin, Poland
| | - Elżbieta Kaja
- Department of Medical Chemistry and Laboratory Medicine, Poznan University of Medical Sciences, Poznan, Poland
| | | | - Tomasz Suchocki
- Biostatistics Group, Wrocław University of Environmental and Life Sciences, Wrocław, Poland,National Research Institute of Animal Production, Balice, Poland
| | - Marzena Wojtaszewska
- Department of Haematology, Institute of Medical Sciences, College of Medical Sciences, University of Rzeszów, Rzeszów, Poland,Department of Haematology, Frederic Chopin Provincial Specialist Hospital, Rzeszów, Poland
| | | | - Anna Mach
- Department of Psychiatry, Medical University of Warsaw, Warsaw, Poland
| | | | - Zbigniew J. Król
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
| | - Joanna Szyda
- Biostatistics Group, Wrocław University of Environmental and Life Sciences, Wrocław, Poland,National Research Institute of Animal Production, Balice, Poland
| | - Paula Dobosz
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
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8
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Polygenic risk score for tumor aggressiveness and early-onset prostate cancer in Asians. Sci Rep 2023; 13:798. [PMID: 36646726 PMCID: PMC9842611 DOI: 10.1038/s41598-022-17515-2] [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: 05/26/2022] [Accepted: 07/26/2022] [Indexed: 01/18/2023] Open
Abstract
We attempted to assess the performance of an ethnic-specific polygenic risk score (PRS) designed from a Korean population to predict aggressive prostate cancer (PCa) and early-onset (age < 60). A PRS score comprised of 22 SNPs was computed in 3695 patients gathered from one of 4 tertiary centers in Korea. Males with biopsy or radical prostatectomy-proven PCa were included for analysis, collecting additional clinical parameters such as age, BMI, PSA, Gleason Group (GG), and staging. Patients were divided into 4 groups of PRS quartiles. Intergroup differences were assessed, as well as risk ratio and predictive performance based on GG using logistic regression analysis and AUC. No significant intergroup differences were observed for BMI, PSA, and rate of ≥ T3a tumors on pathology. Rate of GG ≥ 2, GG ≥ 3, and GG ≥ 4 showed a significant pattern of increase by PRS quartile (p < 0.001, < 0.001, and 0.039, respectively). With the lowest PRS quartile as reference, higher PRS groups showed sequentially escalating risk for GG ≥ 2 and GG ≥ 3 pathology, with a 4.6-fold rise in GG ≥ 2 (p < 0.001) and 2.0-fold rise in GG ≥ 3 (p < 0.001) for the highest PRS quartiles. Combining PRS with PSA improved prediction of early onset csPCa (AUC 0.759) compared to PRS (AUC 0.627) and PSA alone (AUC 0.736). To conclude, an ethnic-specific PRS was found to predict susceptibility of aggressive PCa in addition to improving detection of csPCa when combined with PSA in early onset populations. PRS may have a role as a risk-stratification model in actual practice. Large scale, multi-ethnic trials are required to validate our results.
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9
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Varma A, Maharjan J, Garikipati A, Hurtado M, Shokouhi S, Mao Q. Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records. Cancer Med 2023; 12:379-386. [PMID: 35751453 PMCID: PMC9844630 DOI: 10.1002/cam4.4934] [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: 01/31/2022] [Revised: 03/04/2022] [Accepted: 05/24/2022] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Prostate cancer (PCa) screening is not routinely conducted in men aged 55 and younger, although this age group accounts for more than 10% of cases. Polygenic risk scores (PRSs) and patient data applied toward early prediction of PCa may lead to earlier interventions and increased survival. We have developed machine learning (ML) models to predict PCa risk in men 55 and under using PRSs combined with patient data. METHODS We conducted a retrospective study on 91,106 male patients aged 35-55 using the UK Biobank database. Five gradient boosting models were developed and validated utilizing routine screening data, PRSs, additional clinical data, or combinations of the three. RESULTS Combinations of PRSs and patient data outperformed models that utilized PRS or patient data only, and the highest performing models achieved an area under the receiver operating characteristic curve of 0.788. Our models demonstrated a substantially lower false positive rate (35.4%) in comparison to standard screening using prostate-specific antigen (60%-67%). CONCLUSION This study provides the first preliminary evidence for the use of PRSs with patient data in a ML algorithm for PCa risk prediction in men aged 55 and under for whom screening is not standard practice.
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Affiliation(s)
| | | | | | | | | | - Qingqing Mao
- Dascena Inc.HoustonTexasUSA
- Montera Inc.San FranciscoCAUSA
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10
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Siltari A, Lönnerbro R, Pang K, Shiranov K, Asiimwe A, Evans-Axelsson S, Franks B, Kiran A, Murtola TJ, Schalken J, Steinbeisser C, Bjartell A, Auvinen A, Smith E, N'Dow J, Plass K, Ribal M, Mottet N, Moris L, Lardas M, Van den Broeck T, Willemse PP, Gandaglia G, Campi R, Greco I, Gacci M, Serni S, Briganti A, Crosti D, Meoni M, Garzonio R, Bangma R, Roobol M, Remmers S, Tilki D, Visakorpi T, Talala K, Tammela T, van Hemelrijck M, Bayer K, Lejeune S, Taxiarchopoulou G, van Diggelen F, Senthilkumar K, Schutte S, Byrne S, Fialho L, Cardone A, Gono P, De Vetter M, Ceke K, De Meulder B, Auffray C, Balaur IA, Taibi N, Power S, Kermani NZ, van Bochove K, Cavelaars M, Moinat M, Voss E, Bernini C, Horgan D, Fullwood L, Holtorf M, Lancet D, Bernstein G, Omar I, MacLennan S, Maclennan S, Healey J, Huber J, Wirth M, Froehner M, Brenner B, Borkowetz A, Thomas C, Horn F, Reiche K, Kreux M, Josefsson A, Tandefekt DG, Hugosson J, Huisman H, Hofmacher T, Lindgren P, Andersson E, Fridhammar A, Vizcaya D, Verholen F, Zong J, Butler-Ransohoff JE, Williamson T, Chandrawansa K, Dlamini D, waldeck R, Molnar M, Bruno A, Herrera R, Jiang S, Nevedomskaya E, Fatoba S, Constantinovici N, Maass M, Torremante P, Voss M, Devecseri Z, Cuperus G, Abott T, Dau C, Papineni K, Wang-Silvanto J, Hass S, Snijder R, Doye V, Wang X, Garnham A, Lambrecht M, Wolfinger R, Rogiers S, Servan A, Lefresne F, Caseriego J, Samir M, Lawson J, Pacoe K, Robinson P, Jaton B, Bakkard D, Turunen H, Kilkku O, Pohjanjousi P, Voima O, Nevalaita L, Reich C, Araujo S, Longden-Chapman E, Burke D, Agapow P, Derkits S, Licour M, McCrea C, Payne S, Yong A, Thompson L, Lujan F, Bussmann M, Köhler I. How well do polygenic risk scores identify men at high risk for prostate cancer? Systematic review and meta-analysis. Clin Genitourin Cancer 2022; 21:316.e1-316.e11. [PMID: 36243664 DOI: 10.1016/j.clgc.2022.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/01/2022] [Accepted: 09/06/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVES Genome-wide association studies have revealed over 200 genetic susceptibility loci for prostate cancer (PCa). By combining them, polygenic risk scores (PRS) can be generated to predict risk of PCa. We summarize the published evidence and conduct meta-analyses of PRS as a predictor of PCa risk in Caucasian men. PATIENTS AND METHODS Data were extracted from 59 studies, with 16 studies including 17 separate analyses used in the main meta-analysis with a total of 20,786 cases and 69,106 controls identified through a systematic search of ten databases. Random effects meta-analysis was used to obtain pooled estimates of area under the receiver-operating characteristic curve (AUC). Meta-regression was used to assess the impact of number of single-nucleotide polymorphisms (SNPs) incorporated in PRS on AUC. Heterogeneity is expressed as I2 scores. Publication bias was evaluated using funnel plots and Egger tests. RESULTS The ability of PRS to identify men with PCa was modest (pooled AUC 0.63, 95% CI 0.62-0.64) with moderate consistency (I2 64%). Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81). Meta-regression showed only negligible increase in AUC for adding incremental SNPs. Despite moderate heterogeneity, publication bias was not evident. CONCLUSION Typically, PRS accuracy is comparable to PSA or family history with a pooled AUC value 0.63 indicating mediocre performance for PRS alone.
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11
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Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies. Prostate Cancer Prostatic Dis 2022; 25:422-430. [PMID: 35347252 DOI: 10.1038/s41391-021-00458-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/25/2021] [Accepted: 09/10/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Many studies on prostate cancer (PCa) germline variants have been published in the last 15 years. This review critically assesses their clinical validity and explores their utility in prediction of PCa detection rates from prostate biopsy. METHODS An integrative review was performed to (1) critically synthesize findings on PCa germline studies from published papers since 2016, including risk-associated single nucleotide polymorphisms (SNPs), polygenic risk score methods such as genetic risk score (GRS), and rare pathogenic mutations (RPMs); (2) exemplify the findings in a large population-based cohort from the UK Biobank (UKB); (3) identify gaps for implementing inherited risk assessment in clinic based on experience from a healthcare system; (4) evaluate available GRS data on their clinical utility in predicting PCa detection rates from prostate biopsies; and (5) describe a prospective germline-based biopsy trial to address existing gaps. RESULTS SNP-based GRS and RPMs in four genes (HOXB13, BRCA2, ATM, and CHEK2) were significantly and consistently associated with PCa risk in large well-designed studies. In the UKB, positive family history, RPMs in the four implicated genes, and a high GRS (>1.5) identified 8.12%, 1.61%, and 17.38% of men to be at elevated PCa risk, respectively, with hazard ratios of 1.84, 2.74, and 2.39, respectively. Additionally, the performance of GRS for predicting PCa detection rate on prostate biopsy was consistently supported in several retrospective analyses of transrectal ultrasound (TRUS)-biopsy cohorts. Prospective studies evaluating the performance of all three inherited measures in predicting PCa detection rate from contemporary multiparametric MRI (mpMRI)-based biopsy are lacking. A multicenter germline-based biopsy trial to address these gaps is warranted. CONCLUSIONS The complementary performance of three inherited risk measures in PCa risk stratification is consistently supported. Their clinical utility in predicting PCa detection rate, if confirmed in prospective clinical trials, may improve current decision-making for prostate biopsy.
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12
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Arenas-Gallo C, Owiredu J, Weinstein I, Lewicki P, Basourakos SP, Vince R, Al Hussein Al Awamlh B, Schumacher FR, Spratt DE, Barbieri CE, Shoag JE. Race and prostate cancer: genomic landscape. Nat Rev Urol 2022; 19:547-561. [PMID: 35945369 DOI: 10.1038/s41585-022-00622-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/23/2022] [Indexed: 11/09/2022]
Abstract
In the past 20 years, new insights into the genomic pathogenesis of prostate cancer have been provided. Large-scale integrative genomics approaches enabled researchers to characterize the genetic and epigenetic landscape of prostate cancer and to define different molecular subclasses based on the combination of genetic alterations, gene expression patterns and methylation profiles. Several molecular drivers of prostate cancer have been identified, some of which are different in men of different races. However, the extent to which genomics can explain racial disparities in prostate cancer outcomes is unclear. Future collaborative genomic studies overcoming the underrepresentation of non-white patients and other minority populations are essential.
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Affiliation(s)
- Camilo Arenas-Gallo
- Department of Urology, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jude Owiredu
- Department of Urology, NewYork-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA
| | - Ilon Weinstein
- Department of Urology, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Patrick Lewicki
- Department of Urology, NewYork-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA
| | - Spyridon P Basourakos
- Department of Urology, NewYork-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA
| | - Randy Vince
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - Bashir Al Hussein Al Awamlh
- Department of Urology, NewYork-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.,Department of Urology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Fredrick R Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA.,Case Comprehensive 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 School of Medicine, Cleveland, OH, USA
| | - Christopher E Barbieri
- Department of Urology, NewYork-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA
| | - Jonathan E Shoag
- Department of Urology, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA. .,Department of Urology, NewYork-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA. .,Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA.
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13
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Polygenic risk score in prostate cancer. Curr Opin Urol 2022; 32:466-471. [PMID: 35855560 DOI: 10.1097/mou.0000000000001029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW This study was conducted in order to review the outcomes regarding polygenic risk score (PRS) in prediction of prostate cancer (PCa). With the increasing proficiency of genetic analysis, assessment of PRS for prediction of PCa has been performed in numerous studies. Genetic risk prediction models for PCa that include hundreds to thousands of independent risk-associated variants are under development. For estimation of additive effect of multiple variants, the number of risk alleles carried by an individual is summed, and each variant is weighted according to its estimated effect size for generation of a PRS. RECENT FINDINGS Currently, regarding the accuracy of PRS alone, PCa detection rate ranged from 0.56 to 0.67. A higher rate of accuracy of 0.866-0.880 was observed for other models combining PRS with established clinical markers. The results of PRS from Asian populations showed a level of accuracy that is somewhat low compared with values from Western populations (0.63-0.67); however, recent results from Asian cohorts were similar to that of Western counterparts. Here, we review current PRS literature and examine the clinical utility of PRS for prediction of PCa. SUMMARY Emerging data from several studies regarding PRS in PCa could be the solution to adding predictive value to PCa risk estimation. Although commercial markers are available, development of a large-scale, well validated PRS model should be undertaken in the near future, in order to translate hypothetical scenarios to actual clinical practice.
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14
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Jiang Y, Meyers TJ, Emeka AA, Cooley LF, Cooper PR, Lancki N, Helenowski I, Kachuri L, Lin DW, Stanford JL, Newcomb LF, Kolb S, Finelli A, Fleshner NE, Komisarenko M, Eastham JA, Ehdaie B, Benfante N, Logothetis CJ, Gregg JR, Perez CA, Garza S, Kim J, Marks LS, Delfin M, Barsa D, Vesprini D, Klotz LH, Loblaw A, Mamedov A, Goldenberg SL, Higano CS, Spillane M, Wu E, Carter HB, Pavlovich CP, Mamawala M, Landis T, Carroll PR, Chan JM, Cooperberg MR, Cowan JE, Morgan TM, Siddiqui J, Martin R, Klein EA, Brittain K, Gotwald P, Barocas DA, Dallmer JR, Gordetsky JB, Steele P, Kundu SD, Stockdale J, Roobol MJ, Venderbos LD, Sanda MG, Arnold R, Patil D, Evans CP, Dall’Era MA, Vij A, Costello AJ, Chow K, Corcoran NM, Rais-Bahrami S, Phares C, Scherr DS, Flynn T, Karnes RJ, Koch M, Dhondt CR, Nelson JB, McBride D, Cookson MS, Stratton KL, Farriester S, Hemken E, Stadler WM, Pera T, Banionyte D, Bianco FJ, Lopez IH, Loeb S, Taneja SS, Byrne N, Amling CL, Martinez A, Boileau L, Gaylis FD, Petkewicz J, Kirwen N, Helfand BT, Xu J, Scholtens DM, Catalona WJ, Witte JS. Genetic Factors Associated with Prostate Cancer Conversion from Active Surveillance to Treatment. HGG ADVANCES 2022; 3:100070. [PMID: 34993496 PMCID: PMC8725988 DOI: 10.1016/j.xhgg.2021.100070] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 11/12/2021] [Indexed: 12/18/2022] Open
Abstract
Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9×10-7 and GAB2, p = 2.0×10-6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% Confidence Interval [CI]= 0.94-1.36); whereas, decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04-1.50). These results suggest that germline genetics may help inform and individualize the decision of AS-or the intensity of monitoring on AS-versus treatment for the initial management of patients with low-risk PC.
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Affiliation(s)
- Yu Jiang
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Travis J. Meyers
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Adaeze A. Emeka
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Lauren Folgosa Cooley
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Phillip R. Cooper
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Nicola Lancki
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Irene Helenowski
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Linda Kachuri
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Daniel W. Lin
- Fred Hutchinson Cancer Research Center, Cancer Prevention Program, Public Health Sciences, Seattle, WA 98109, USA
- Department of Urology, University of Washington, Seattle, WA 98195, USA
| | - Janet L. Stanford
- Fred Hutchinson Cancer Research Center, Cancer Epidemiology Program, Public Health Sciences, Seattle, WA 98109, USA
- Department of Epidemiology, University of Washington, School of Public Health, Seattle, WA 98195, USA
| | - Lisa F. Newcomb
- Fred Hutchinson Cancer Research Center, Cancer Prevention Program, Public Health Sciences, Seattle, WA 98109, USA
- Department of Urology, University of Washington, Seattle, WA 98195, USA
| | - Suzanne Kolb
- Fred Hutchinson Cancer Research Center, Cancer Epidemiology Program, Public Health Sciences, Seattle, WA 98109, USA
- Department of Epidemiology, University of Washington, School of Public Health, Seattle, WA 98195, USA
| | - Antonio Finelli
- Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Neil E. Fleshner
- Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Maria Komisarenko
- Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - James A. Eastham
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Behfar Ehdaie
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nicole Benfante
- Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Christopher J. Logothetis
- Departments of Genitourinary Medical Oncology and Urology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Justin R. Gregg
- Departments of Genitourinary Medical Oncology and Urology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Cherie A. Perez
- Departments of Genitourinary Medical Oncology and Urology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sergio Garza
- Departments of Genitourinary Medical Oncology and Urology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jeri Kim
- Departments of Genitourinary Medical Oncology and Urology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Leonard S. Marks
- Department of Urology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Merdie Delfin
- Department of Urology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Danielle Barsa
- Department of Urology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Danny Vesprini
- Odette Cancer Centre, Sunnybrook Health and Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Laurence H. Klotz
- Odette Cancer Centre, Sunnybrook Health and Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Andrew Loblaw
- Odette Cancer Centre, Sunnybrook Health and Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Alexandre Mamedov
- Odette Cancer Centre, Sunnybrook Health and Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - S. Larry Goldenberg
- Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Celestia S. Higano
- Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Maria Spillane
- Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Eugenia Wu
- Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada
| | - H. Ballentine Carter
- Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christian P. Pavlovich
- Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Mufaddal Mamawala
- Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Tricia Landis
- Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter R. Carroll
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
| | - June M. Chan
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
| | - Matthew R. Cooperberg
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Janet E. Cowan
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
| | - Todd M. Morgan
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - Javed Siddiqui
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Rabia Martin
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Eric A. Klein
- Glickman Urological and Kidney Institute, Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Karen Brittain
- Glickman Urological and Kidney Institute, Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Paige Gotwald
- Glickman Urological and Kidney Institute, Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Daniel A. Barocas
- Department of Urology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeremiah R. Dallmer
- Department of Urology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jennifer B. Gordetsky
- Department of Urology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Pam Steele
- Department of Urology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shilajit D. Kundu
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Jazmine Stockdale
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Monique J. Roobol
- Department of Urology, Erasmus Cancer Institute, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Lionne D.F. Venderbos
- Department of Urology, Erasmus Cancer Institute, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Martin G. Sanda
- Department of Urology, Emory University School of Medicine, Atlanta, GA, USA
| | - Rebecca Arnold
- Department of Urology, Emory University School of Medicine, Atlanta, GA, USA
| | - Dattatraya Patil
- Department of Urology, Emory University School of Medicine, Atlanta, GA, USA
| | - Christopher P. Evans
- Department of Urologic Surgery, University of California, Davis Medical Center, Sacramento, CA, USA
| | - Marc A. Dall’Era
- Department of Urologic Surgery, University of California, Davis Medical Center, Sacramento, CA, USA
| | - Anjali Vij
- Department of Urologic Surgery, University of California, Davis Medical Center, Sacramento, CA, USA
| | - Anthony J. Costello
- Department of Urology, Royal Melbourne Hospital and University of Melbourne, Melbourne, VIC, Australia
| | - Ken Chow
- Department of Urology, Royal Melbourne Hospital and University of Melbourne, Melbourne, VIC, Australia
| | - Niall M. Corcoran
- Department of Urology, Royal Melbourne Hospital and University of Melbourne, Melbourne, VIC, Australia
| | - Soroush Rais-Bahrami
- Department of Urology, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Courtney Phares
- Department of Urology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Douglas S. Scherr
- Department of Urology, Weill Cornell Medicine, New York-Presbyterian Hospital, New York, NY, USA
| | - Thomas Flynn
- Department of Urology, Weill Cornell Medicine, New York-Presbyterian Hospital, New York, NY, USA
| | | | - Michael Koch
- Department of Urology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Courtney Rose Dhondt
- Department of Urology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Joel B. Nelson
- Department of Urology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dawn McBride
- Department of Urology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Michael S. Cookson
- Department of Urology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Kelly L. Stratton
- Department of Urology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Stephen Farriester
- Department of Urology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Erin Hemken
- Department of Urology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | | | - Tuula Pera
- University of Chicago Comprehensive Cancer Center, Chicago, IL, USA
| | | | | | | | - Stacy Loeb
- Departments of Urology and Population Health, New York University Langone Health and Manhattan Veterans Affairs Medical Center, New York, NY, USA
| | - Samir S. Taneja
- Departments of Urology and Population Health, New York University Langone Health and Manhattan Veterans Affairs Medical Center, New York, NY, USA
| | - Nataliya Byrne
- Departments of Urology and Population Health, New York University Langone Health and Manhattan Veterans Affairs Medical Center, New York, NY, USA
| | | | - Ann Martinez
- Department of Urology, Oregon Health and Science University, Portland, OR, USA
| | - Luc Boileau
- Department of Urology, Oregon Health and Science University, Portland, OR, USA
| | - Franklin D. Gaylis
- Genesis Healthcare Partners, Department of Urology, University of California, San Diego, CA, USA
| | | | - Nicholas Kirwen
- Division of Urology, NorthShore University Health System, Evanston, IL, USA
| | - Brian T. Helfand
- Division of Urology, NorthShore University Health System, Evanston, IL, USA
| | - Jianfeng Xu
- Division of Urology, NorthShore University Health System, Evanston, IL, USA
| | - Denise M. Scholtens
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - William J. Catalona
- Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - John S. Witte
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Departments of Epidemiology and Population Health, Biomedical Data Science, and Genetics, Stanford University, Stanford, CA, USA
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15
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Bakshi A, Riaz M, Orchard SG, Carr PR, Joshi AD, Cao Y, Rebello R, Nguyen-Dumont T, Southey MC, Millar JL, Gately L, Gibbs P, Ford LG, Parnes HL, Chan AT, McNeil JJ, Lacaze P. A Polygenic Risk Score Predicts Incident Prostate Cancer Risk in Older Men but Does Not Select for Clinically Significant Disease. Cancers (Basel) 2021; 13:5815. [PMID: 34830967 PMCID: PMC8616400 DOI: 10.3390/cancers13225815] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/17/2021] [Accepted: 11/18/2021] [Indexed: 12/24/2022] Open
Abstract
Despite the high prevalence of prostate cancer in older men, the predictive value of a polygenic risk score (PRS) remains uncertain in men aged ≥70 years. We used a 6.6 million-variant PRS to predict the risk of incident prostate cancer in a prospective study of 5701 men of European descent aged ≥70 years (mean age 75 years) enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) clinical trial. The study endpoint was prostate cancer, including metastatic or non-metastatic disease, confirmed by an expert panel. After excluding participants with a history of prostate cancer at enrolment, we used a multivariable Cox proportional hazards model to assess the association between the PRS and incident prostate cancer risk, adjusting for covariates. Additionally, we examined the distribution of Gleason grade groups by PRS group to determine if a higher PRS was associated with higher grade disease. We tested for interaction between the PRS and aspirin treatment. Logistic regression was used to independently assess the association of the PRS with prevalent (pre-trial) prostate cancer, reported in medical histories. During a median follow-up time of 4.6 years, 218 of the 5701 participants (3.8%) were diagnosed with prostate cancer. The PRS predicted incident risk with a hazard ratio (HR) of 1.52 per standard deviation (SD) (95% confidence interval (CI) 1.33-1.74, p < 0.001). Men in the top quintile of the PRS distribution had an almost three times higher risk of prostate cancer than men in the lowest quintile (HR = 2.99 (95% CI 1.90-4.27), p < 0.001). However, a higher PRS was not associated with a higher Gleason grade groups. We found no interaction between aspirin treatment and the PRS for prostate cancer risk. The PRS was also associated with prevalent prostate cancer (odds ratio = 1.80 per SD (95% CI 1.65-1.96), p < 0.001).While a PRS for prostate cancer is strongly associated with incident risk in men aged ≥70 years, the clinical utility of the PRS as a biomarker is currently limited by its inability to select for clinically significant disease.
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Affiliation(s)
- Andrew Bakshi
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; (M.R.); (S.G.O.); (P.R.C.); (J.L.M.); (J.J.M.); (P.L.)
| | - Moeen Riaz
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; (M.R.); (S.G.O.); (P.R.C.); (J.L.M.); (J.J.M.); (P.L.)
| | - Suzanne G. Orchard
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; (M.R.); (S.G.O.); (P.R.C.); (J.L.M.); (J.J.M.); (P.L.)
| | - Prudence R. Carr
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; (M.R.); (S.G.O.); (P.R.C.); (J.L.M.); (J.J.M.); (P.L.)
| | - Amit D. Joshi
- Clinical and Translational Epidemiology Unit, MGH Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02108, USA; (A.D.J.); (A.T.C.)
| | - Yin Cao
- Alvin J. Siteman Cancer Center, Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA;
| | - Richard Rebello
- Centre for Cancer Research, Department of Clinical Pathology, University of Melbourne, Melbourne, VIC 3010, Australia;
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Tú Nguyen-Dumont
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Department of Clinical Pathology, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC 3168, Australia; (T.N.-D.); (M.C.S.)
- Department of Clinical Pathology, University of Melbourne, Melbourne, VIC 3010, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
| | - Jeremy L. Millar
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; (M.R.); (S.G.O.); (P.R.C.); (J.L.M.); (J.J.M.); (P.L.)
- Alfred Health Radiation Oncology, Alfred Hospital, Melbourne, VIC 3004, Australia
- Central Clinical School, Monash University, Melbourne, VIC 3168, Australia
| | - Lucy Gately
- Personalised Oncology Division, Walter and Eliza Hall Institute Medical Research, Faculty of Medicine, University of Melbourne, Melbourne, VIC 3052, Australia; (L.G.); (P.G.)
| | - Peter Gibbs
- Personalised Oncology Division, Walter and Eliza Hall Institute Medical Research, Faculty of Medicine, University of Melbourne, Melbourne, VIC 3052, Australia; (L.G.); (P.G.)
| | - Leslie G. Ford
- Division of Cancer Prevention, National Cancer Institute, Rockville, MD 20892, USA; (L.G.F.); (H.L.P.)
| | - Howard L. Parnes
- Division of Cancer Prevention, National Cancer Institute, Rockville, MD 20892, USA; (L.G.F.); (H.L.P.)
| | - Andrew T. Chan
- Clinical and Translational Epidemiology Unit, MGH Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02108, USA; (A.D.J.); (A.T.C.)
| | - John J. McNeil
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; (M.R.); (S.G.O.); (P.R.C.); (J.L.M.); (J.J.M.); (P.L.)
| | - Paul Lacaze
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; (M.R.); (S.G.O.); (P.R.C.); (J.L.M.); (J.J.M.); (P.L.)
- Clinical and Translational Epidemiology Unit, MGH Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02108, USA; (A.D.J.); (A.T.C.)
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16
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Brockman DG, Petronio L, Dron JS, Kwon BC, Vosburg T, Nip L, Tang A, O'Reilly M, Lennon N, Wong B, Ng K, Huang KH, Fahed AC, Khera AV. Design and user experience testing of a polygenic score report: a qualitative study of prospective users. BMC Med Genomics 2021; 14:238. [PMID: 34598685 PMCID: PMC8485114 DOI: 10.1186/s12920-021-01056-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 08/12/2021] [Indexed: 12/28/2022] Open
Abstract
Background Polygenic scores—which quantify inherited risk by integrating information from many common sites of DNA variation—may enable a tailored approach to clinical medicine. However, alongside considerable enthusiasm, we and others have highlighted a lack of standardized approaches for score disclosure. Here, we review the landscape of polygenic score reporting and describe a generalizable approach for development of a polygenic score disclosure tool for coronary artery disease. Methods We assembled a working group of clinicians, geneticists, data visualization specialists, and software developers. The group reviewed existing polygenic score reports and then designed a two-page mock report for coronary artery disease. We then conducted a qualitative user-experience study with this report using an interview guide focused on comprehension, experience, and attitudes. Interviews were transcribed and analyzed for themes identification to inform report revision. Results Review of nine existing polygenic score reports from commercial and academic groups demonstrated significant heterogeneity, reinforcing the need for additional efforts to study and standardize score disclosure. Using a newly developed mock score report, we conducted interviews with ten adult individuals (50% females, 70% without prior genetic testing experience, age range 20–70 years) recruited via an online platform. We identified three themes from interviews: (1) visual elements, such as color and simple graphics, enable participants to interpret, relate to, and contextualize their polygenic score, (2) word-based descriptions of risk and polygenic scores presented as percentiles were the best recognized and understood, (3) participants had varying levels of interest in understanding complex genomic information and therefore would benefit from additional resources that can adapt to their individual needs in real time. In response to user feedback, colors used for communicating risk were modified to minimize unintended color associations and odds ratios were removed. All 10 participants expressed interest in receiving a polygenic score report based on their personal genomic information. Conclusions Our findings describe a generalizable approach to develop a polygenic score report understandable by potential patients. Although additional studies are needed across a wider spectrum of patient populations, these results are likely to inform ongoing efforts related to polygenic score disclosure within clinical practice. Supplementary Information The online version contains supplementary material available at 10.1186/s12920-021-01056-0.
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Affiliation(s)
- Deanna G Brockman
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, 185 Cambridge Street, Simches Research Building
- CPZN 6.256, Boston, MA, 02114, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lia Petronio
- Pattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jacqueline S Dron
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bum Chul Kwon
- Center for Computational Health, IBM Research, Cambridge, MA, USA
| | - Trish Vosburg
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Genomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lisa Nip
- Pattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrew Tang
- Pattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mary O'Reilly
- Pattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Niall Lennon
- Genomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bang Wong
- Pattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kenney Ng
- Center for Computational Health, IBM Research, Cambridge, MA, USA
| | - Katherine H Huang
- Pattern Visualization Team, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Akl C Fahed
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, 185 Cambridge Street, Simches Research Building
- CPZN 6.256, Boston, MA, 02114, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Amit V Khera
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, 185 Cambridge Street, Simches Research Building
- CPZN 6.256, Boston, MA, 02114, USA. .,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Department of Medicine, Harvard Medical School, Boston, MA, USA.
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17
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Fadason T, Farrow S, Gokuladhas S, Golovina E, Nyaga D, O'Sullivan JM, Schierding W. Assigning function to SNPs: Considerations when interpreting genetic variation. Semin Cell Dev Biol 2021; 121:135-142. [PMID: 34446357 DOI: 10.1016/j.semcdb.2021.08.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 08/12/2021] [Indexed: 12/26/2022]
Abstract
Assigning function to single nucleotide polymorphisms (SNPs) to understand the mechanisms that link genetic and phenotypic variation and disease is an area of intensive research that is necessary to contribute to the continuing development of precision medicine. However, despite the apparent simplicity that is captured in the name SNP - 'single nucleotide' changes are not easy to functionally characterize. This complexity arises from multiple features of the genome including the fact that function is development and environment specific. As such, we are often fooled by our terminology and underlying assumptions that there is a single function for a SNP. Here we discuss some of what is known about SNPs, their functions and how we can go about characterizing them.
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Affiliation(s)
- Tayaza Fadason
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | - Sophie Farrow
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | | | - Evgeniia Golovina
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Denis Nyaga
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Justin M O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand; Garvan Institute of Medical Research, Sydney, New South Wales, Australia; MRC Lifecourse Epidemiology Unit, University of Southampton, United Kingdom.
| | - William Schierding
- Liggins Institute, The University of Auckland, Auckland, New Zealand; The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
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18
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Abstract
More than 40% of the risk of developing prostate cancer (PCa) is from genetic factors. Genome-wide association studies have led to the discovery of more than 140 variants associated with PCa risk. Polygenic risk scores (PRS) generated using these variants show promise in identifying individuals at much higher (and lower) lifetime risk than the average man. PCa PRS also improve the predictive value of prostate-specific antigen screening, may inform the age for starting PCa screening, and are informative for development of more aggressive tumors. Despite the promise, few clinical trials have evaluated the benefit of PCa PRS for clinical care.
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19
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Doan DK, Schmidt KT, Chau CH, Figg WD. Germline Genetics of Prostate Cancer: Prevalence of Risk Variants and Clinical Implications for Disease Management. Cancers (Basel) 2021; 13:cancers13092154. [PMID: 33947030 PMCID: PMC8124444 DOI: 10.3390/cancers13092154] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 04/27/2021] [Accepted: 04/28/2021] [Indexed: 12/30/2022] Open
Abstract
Prostate cancer has entered into the era of precision medicine with the recent approvals of targeted therapeutics (olaparib and rucaparib). The presence of germline mutations has important hereditary cancer implications for patients with prostate cancer, and germline testing is increasingly important in cancer screening, risk assessment, and the overall treatment and management of the disease. In this review, we discuss germline variants associated with inherited predisposition, prostate cancer risk and outcomes. We review recommendations for germline testing, available testing platforms, genetic counseling as well as discuss the therapeutic implications of germline variants relevant to prostate cancer treatments. Understanding the role of germline (heritable) mutations that affect prostate cancer biology and risk as well as the subsequent effect of these alterations on potential therapies is critical as the treatment paradigm shifts towards precision medicine. Furthermore, enhancing patient education tactics and healthcare system infrastructure is essential for the utilization of relevant predictive biomarkers and the improvement of clinical outcomes of patients with prostate cancer or at high risk of developing the disease.
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Affiliation(s)
| | - Keith T. Schmidt
- Clinical Pharmacology Program, Office of the Clinical Director, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA;
| | - Cindy H. Chau
- Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA;
| | - William D. Figg
- Clinical Pharmacology Program, Office of the Clinical Director, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA;
- Genitourinary Malignancies Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA;
- Correspondence: ; Tel.: +1-240-760-6179; Fax: +1-240-858-3020
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20
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Song SH, Byun SS. Polygenic risk score for genetic evaluation of prostate cancer risk in Asian populations: A narrative review. Investig Clin Urol 2021; 62:256-266. [PMID: 33943048 PMCID: PMC8100017 DOI: 10.4111/icu.20210124] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 04/15/2021] [Accepted: 04/15/2021] [Indexed: 12/16/2022] Open
Abstract
Decreasing costs of genetic testing and interest in disease inheritance has changed the landscape of cancer prediction in prostate cancer (PCa), and guidelines now include genetic testing for high-risk groups. Familial and hereditary PCa comprises approximately 20% and 5% of all PCa, respectively. Multifaceted disorders like PCa are caused by a combinatory effect of rare genes of high penetrance and smaller genetic variants of relatively lower effect size. Polygenic risk score (PRS) is a novel tool utilizing PCa-associated single nucleotide polymorphisms (SNPs) identified from genome-wide association study (GWAS) to generate an additive estimate of an individual's lifetime genetic risk for cancer. However, most PRS are developed based on GWAS collected from mainly European populations and do not address ethnic differences in PCa genetics. This review highlights the attempts to generate a PRS tailored to Asian males including data from Korea, China, and Japan, and discuss the clinical implications for prediction of early onset and aggressive PCa.
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Affiliation(s)
- Sang Hun Song
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Seok Soo Byun
- Department of Urology, Seoul National University Bundang Hospital, Seongnam, Korea.,Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Korea.
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21
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Wei J, Shi Z, Na R, Resurreccion WK, Wang CH, Duggan D, Zheng SL, Hulick PJ, Helfand BT, Xu J. Calibration of polygenic risk scores is required prior to clinical implementation: results of three common cancers in UKB. J Med Genet 2020; 59:243-247. [PMID: 33443076 DOI: 10.1136/jmedgenet-2020-107286] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 11/18/2020] [Accepted: 11/21/2020] [Indexed: 11/03/2022]
Abstract
BACKGROUND SNP-based polygenic risk scores have recently been adopted in the clinic for risk assessment of some common diseases. Their validity is supported by a consistent trend between their percentile rank and disease risk in populations. However, for clinical use at the individual level, the reliability of score values is necessary considering they are directly used to calculate remaining lifetime risk. OBJECTIVES We assessed the reliability of polygenic score values to estimate prostate cancer (PCa), breast cancer (BCa) and colorectal cancer (CRC) risk in three incident cohorts from the UK Biobank (n>500 000). METHODS Cancer-specific Genetic Risk Score (GRS), a well-established population-standardised polygenic risk score, was calculated. RESULTS A systematic bias was found between estimated risks (GRS values) and observed risks; β (95% CI) was 0.67 (0.58-0.76), 0.74 (0.65-0.84) and 0.82 (0.75-0.89), respectively, for PCa, BCa and CRC, all significantly lower than 1.00 (perfect calibration), p<0.001. After applying a correction factor derived from a training data set, the β for corrected GRS values in an independent testing data set were 1.09 (1.05-1.13), 1.00 (0.88-1.12) and 1.08 (0.96-1.21), respectively, for PCa, BCa and CRC. CONCLUSION Assessing the calibration of polygenic risk scores is necessary and feasible to ensure their reliability prior to clinical implementation.
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Affiliation(s)
- Jun Wei
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Zhuqing Shi
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Rong Na
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - W Kyle Resurreccion
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Chi-Hsiung Wang
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - David Duggan
- Affiliate of City of Hope, Translational Genomics Research Institute, Phoenix, Arizona, USA
| | - S Lilly Zheng
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Peter J Hulick
- Department of Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Brian T Helfand
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Jianfeng Xu
- Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, Illinois, USA
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