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Hess JL, Mattheisen M, Greenwood TA, Tsuang MT, Edenberg HJ, Holmans P, Faraone SV, Glatt SJ. A polygenic resilience score moderates the genetic risk for schizophrenia: Replication in 18,090 cases and 28,114 controls from the Psychiatric Genomics Consortium. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32957. [PMID: 37551635 PMCID: PMC10850427 DOI: 10.1002/ajmg.b.32957] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 07/08/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023]
Abstract
Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever "polygenic resilience score" for SCZ (resilient controls n = 3786; polygenic risk score-matched SCZ cases n = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, p = 4.03 × 10-5 ) using newly released GWAS data from 23 independent case-control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls n = 2821; polygenic risk score-matched SCZ cases n = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score.
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Affiliation(s)
- Jonathan L. Hess
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Manuel Mattheisen
- Departments of Psychiatry and Community Health and Epidemiology, Dalhousie University, Halifax, NS, Canada
| | | | | | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Peter Holmans
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Stephen V. Faraone
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Stephen J. Glatt
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
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2
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Lori A, Pearce BD, Katrinli S, Carter S, Gillespie CF, Bradley B, Wingo AP, Jovanovic T, Michopoulos V, Duncan E, Hinrichs RC, Smith A, Ressler KJ. Genetic risk for hospitalization of African American patients with severe mental illness reveals HLA loci. Front Psychiatry 2024; 15:1140376. [PMID: 38469033 PMCID: PMC10925622 DOI: 10.3389/fpsyt.2024.1140376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 02/07/2024] [Indexed: 03/13/2024] Open
Abstract
Background Mood disorders such as major depressive and bipolar disorders, along with posttraumatic stress disorder (PTSD), schizophrenia (SCZ), and other psychotic disorders, constitute serious mental illnesses (SMI) and often lead to inpatient psychiatric care for adults. Risk factors associated with increased hospitalization rate in SMI (H-SMI) are largely unknown but likely involve a combination of genetic, environmental, and socio-behavioral factors. We performed a genome-wide association study in an African American cohort to identify possible genes associated with hospitalization due to SMI (H-SMI). Methods Patients hospitalized for psychiatric disorders (H-SMI; n=690) were compared with demographically matched controls (n=4467). Quality control and imputation of genome-wide data were performed following the Psychiatric Genetic Consortium (PGC)-PTSD guidelines. Imputation of the Human Leukocyte Antigen (HLA) locus was performed using the HIBAG package. Results Genome-wide association analysis revealed a genome-wide significant association at 6p22.1 locus in the ubiquitin D (UBD/FAT10) gene (rs362514, p=9.43x10-9) and around the HLA locus. Heritability of H-SMI (14.6%) was comparable to other psychiatric disorders (4% to 45%). We observed a nominally significant association with 2 HLA alleles: HLA-A*23:01 (OR=1.04, p=2.3x10-3) and HLA-C*06:02 (OR=1.04, p=1.5x10-3). Two other genes (VSP13D and TSPAN9), possibly associated with immune response, were found to be associated with H-SMI using gene-based analyses. Conclusion We observed a strong association between H-SMI and a locus that has been consistently and strongly associated with SCZ in multiple studies (6p21.32-p22.1), possibly indicating an involvement of the immune system and the immune response in the development of severe transdiagnostic SMI.
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Affiliation(s)
- Adriana Lori
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
- Department of Population Science, American Cancer Society, Atlanta, GA, United States
| | - Brad D. Pearce
- Department of Epidemiology, Rollins School of Public Health, Atlanta, GA, United States
| | - Seyma Katrinli
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, United States
| | - Sierra Carter
- Department of Psychology, Georgia State University, Atlanta, GA, United States
| | - Charles F. Gillespie
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | - Bekh Bradley
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | - Aliza P. Wingo
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
- Mental Health Service Line, Department of Veterans Affairs Health Care System, Decatur, GA, United States
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neuroscience, Wayne State University, Detroit, MI, United States
| | - Vasiliki Michopoulos
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | - Erica Duncan
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
- Mental Health Service Line, Department of Veterans Affairs Health Care System, Decatur, GA, United States
| | - Rebecca C. Hinrichs
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
| | - Alicia Smith
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, United States
| | - Kerry J. Ressler
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, United States
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, United States
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3
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Oblak T, Škerl P, Narang BJ, Blagus R, Krajc M, Novaković S, Žgajnar J. Breast cancer risk prediction using Tyrer-Cuzick algorithm with an 18-SNPs polygenic risk score in a European population with below-average breast cancer incidence. Breast 2023; 72:103590. [PMID: 37857130 PMCID: PMC10587756 DOI: 10.1016/j.breast.2023.103590] [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: 06/21/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 10/21/2023] Open
Abstract
GOALS To determine whether an 18 single nucleotide polymorphisms (SNPs) polygenic risk score (PRS18) improves breast cancer (BC) risk prediction for women at above-average risk of BC, aged 40-49, in a Central European population with BC incidence below EU average. METHODS 502 women aged 40-49 years at the time of BC diagnosis completed a questionnaire on BC risk factors (as per Tyrer-Cuzick algorithm) with data known at age 40 and before BC diagnosis. Blood samples were collected for DNA isolation. 250 DNA samples from healthy women aged 50 served as a control cohort. 18 BC-associated SNPs were genotyped in both groups and PRS18 was calculated. The predictive power of PRS18 to detect BC was evaluated using a ROC curve. 10-year BC risk was calculated using the Tyrer-Cuzick algorithm adapted to the Slovenian incidence rate (S-IBIS): first based on questionnaire-based risk factors and, second, including PRS18. RESULTS The AUC for PRS18 was 0.613 (95 % CI 0.570-0.657). 83.3 % of women were classified at above-average risk for BC with S-IBIS without PRS18 and 80.7 % when PRS18 was included. CONCLUSION BC risk prediction models and SNPs panels should not be automatically used in clinical practice in different populations without prior population-based validation. In our population the addition of an 18SNPs PRS to questionnaire-based risk factors in the Tyrer-Cuzick algorithm in general did not improve BC risk stratification, however, some improvements were observed at higher BC risk scores and could be valuable in distinguishing women at intermediate and high risk of BC.
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Affiliation(s)
- Tjaša Oblak
- Department of Surgical Oncology, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia; Medical Faculty, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia.
| | - Petra Škerl
- Department of Molecular Diagnostics, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
| | - Benjamin J Narang
- Institute for Biostatistics and Medical Informatics, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia; Department of Automatics, Jožef Stefan Institute, Biocybernetics and Robotics, Jamova cesta 39, Ljubljana, Slovenia; Faculty of Sport, University of Ljubljana, Gortanova 22, Ljubljana, Slovenia.
| | - Rok Blagus
- Institute for Biostatistics and Medical Informatics, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia; Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, 6000, Koper, Slovenia.
| | - Mateja Krajc
- Cancer Genetics Clinic, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
| | - Srdjan Novaković
- Department of Molecular Diagnostics, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
| | - Janez Žgajnar
- Department of Surgical Oncology, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
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4
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Levi H, Carmi S, Rosset S, Yerushalmi R, Zick A, Yablonski-Peretz T, Wang Q, Bolla MK, Dennis J, Michailidou K, Lush M, Ahearn T, Andrulis IL, Anton-Culver H, Antoniou AC, Arndt V, Augustinsson A, Auvinen P, Beane Freeman L, Beckmann M, Behrens S, Bermisheva M, Bodelon C, Bogdanova NV, Bojesen SE, Brenner H, Byers H, Camp N, Castelao J, Chang-Claude J, Chirlaque MD, Chung W, Clarke C, Collee MJ, Colonna S, Couch F, Cox A, Cross SS, Czene K, Daly M, Devilee P, Dork T, Dossus L, Eccles DM, Eliassen AH, Eriksson M, Evans G, Fasching P, Fletcher O, Flyger H, Fritschi L, Gabrielson M, Gago-Dominguez M, García-Closas M, Garcia-Saenz JA, Genkinger J, Giles GG, Goldberg M, Guénel P, Hall P, Hamann U, He W, Hillemanns P, Hollestelle A, Hoppe R, Hopper J, Jakovchevska S, Jakubowska A, Jernström H, John E, Johnson N, Jones M, Vijai J, Kaaks R, Khusnutdinova E, Kitahara C, Koutros S, Kristensen V, Kurian AW, Lacey J, Lambrechts D, Le Marchand L, Lejbkowicz F, Lindblom A, Loibl S, Lori A, Lubinski J, Mannermaa A, Manoochehri M, Mavroudis D, Menon U, Mulligan A, Murphy R, Nevelsteen I, Newman WG, Obi N, O'Brien K, Offit K, Olshan A, Plaseska-Karanfilska D, Olson J, Panico S, Park-Simon TW, Patel A, Peterlongo P, Rack B, Radice P, Rennert G, Rhenius V, Romero A, Saloustros E, Sandler D, Schmidt MK, Schwentner L, Shah M, Sharma P, Simard J, Southey M, Stone J, Tapper WJ, Taylor J, Teras L, Toland AE, Troester M, Truong T, van der Kolk LE, Weinberg C, Wendt C, Yang XR, Zheng W, Ziogas A, Dunning AM, Pharoah P, Easton DF, Ben-Sachar S, Elefant N, Shamir R, Elkon R. Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel. J Med Genet 2023; 60:1186-1197. [PMID: 37451831 PMCID: PMC10715538 DOI: 10.1136/jmg-2023-109185] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/28/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. METHODS We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. RESULTS In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). CONCLUSIONS Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.
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Grants
- R01 CA176785 NCI NIH HHS
- NU58DP006344 NCCDPHP CDC HHS
- R37 CA070867 NCI NIH HHS
- HHSN261201800015I NCI NIH HHS
- R01 CA064277 NCI NIH HHS
- P50 CA116201 NCI NIH HHS
- G1000143 Medical Research Council
- P30 CA062203 NCI NIH HHS
- HHSN261201800015C NCI NIH HHS
- R01 CA047305 NCI NIH HHS
- HHSN261201800009I NCI NIH HHS
- R01 CA163353 NCI NIH HHS
- UM1 CA164917 NCI NIH HHS
- U01 CA199277 NCI NIH HHS
- U01 CA179715 NCI NIH HHS
- HHSN261201800032C NCI NIH HHS
- U54 CA156733 NCI NIH HHS
- HHSN261201800009C NCI NIH HHS
- Z01 CP010119 Intramural NIH HHS
- UM1 CA164973 NCI NIH HHS
- P01 CA087969 NCI NIH HHS
- UM1 CA164920 NCI NIH HHS
- NU58DP006320 CDC HHS
- UM1 CA176726 NCI NIH HHS
- R01 CA092447 NCI NIH HHS
- Z01 ES049030 Intramural NIH HHS
- R01 CA058860 NCI NIH HHS
- K07 CA092044 NCI NIH HHS
- HHSN261201800016C NCI NIH HHS
- P50 CA058223 NCI NIH HHS
- R01 CA100374 NCI NIH HHS
- P30 CA008748 NCI NIH HHS
- R01 CA128978 NCI NIH HHS
- R01 CA047147 NCI NIH HHS
- U19 CA148537 NCI NIH HHS
- R01 CA116167 NCI NIH HHS
- R01 CA148667 NCI NIH HHS
- R01 CA063464 NCI NIH HHS
- HHSN261201800016I NCI NIH HHS
- UM1 CA186107 NCI NIH HHS
- P30 CA023100 NCI NIH HHS
- U01 CA063464 NCI NIH HHS
- R01 CA077398 NCI NIH HHS
- R01 CA054281 NCI NIH HHS
- R01 CA132839 NCI NIH HHS
- P30 CA068485 NCI NIH HHS
- U01 CA058860 NCI NIH HHS
- U01 CA164920 NCI NIH HHS
- R35 CA253187 NCI NIH HHS
- 14136 Cancer Research UK
- U19 CA148112 NCI NIH HHS
- HHSN261201800032I NCI NIH HHS
- U01 CA098758 NCI NIH HHS
- Z01 ES044005 Intramural NIH HHS
- U19 CA148065 NCI NIH HHS
- P30 CA033572 NCI NIH HHS
- R01 CA069664 NCI NIH HHS
- Wellcome Trust
- 001 World Health Organization
- Z01 ES049033 Intramural NIH HHS
- R01 CA192393 NCI NIH HHS
- U01 CA164973 NCI NIH HHS
- R37 CA054281 NCI NIH HHS
- Consellería de Industria Programa Sectorial de Investigación Aplicada
- Statistics Netherlands
- South Eastern Norway Health Authority
- Lower Saxonian Cancer Society
- Lise Boserup Fund
- Heidelberger Zentrum für Personalisierte Onkologie Deutsches Krebsforschungszentrum In Der Helmholtz-Gemeinschaft
- Lon V. Smith Foundation
- Scottish Funding Council
- Komen Foundation
- Claudia von Schilling Foundation for Breast Cancer Research
- Russian Foundation for Basic Research
- Ligue Contre le Cancer
- Sigrid Juselius Foundation
- Kuopion Yliopistollinen Sairaala
- Sheffield Experimental Cancer Medicine Centre
- Stockholm läns landsting
- Department of Health and Human Services (USA)
- Department of Defence (USA)
- Stichting Tegen Kanker
- David F. and Margaret T. Grohne Family Foundation
- Sundhed og Sygdom, Det Frie Forskningsråd
- Stavros Niarchos Foundation
- Post-Cancer GWAS initiative
- Institute of the Ruhr University Bochum
- Instituto de Salud Carlos III
- Institute of Cancer Research
- Public Health Institute
- Fondation du cancer du sein du Québec
- Institut National de la Santé et de la Recherche Médicale
- Pink Ribbon
- Institute for Prevention and Occupational Medicine
- K.G. Jebsen Centre for Breast Cancer Research
- Research Centre for Genetic Engineering and Biotechnology
- Center of Excellence (Finland)
- Robert and Kate Niehaus Clinical Cancer Genetics Initiative
- Rudolf Bartling Foundation
- Center for Disease Control and Prevention (USA)
- Karolinska Institutet
- Norges Forskningsråd
- Robert Bosch Stiftung
- Intramural Research Funds of the National Cancer Institute (USA)
- Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC
- Intramural Research Program of the Division of Cancer Epidemiology and Genetics
- Centre International de Recherche sur le Cancer
- Queensland Cancer Fund
- Red Temática de Investigación Cooperativa en Cáncer
- Intramural Research Program of the National Institutes of Health
- National Health Service (UK)
- Ministerie van Volksgezondheid, Welzijn en Sport
- National cancer institute (USA)
- KWF Kankerbestrijding
- Märit and Hans Rausings Initiative Against Breast Cancer
- Associazione Italiana per la Ricerca sul Cancro
- Fundación Científica Asociación Española Contra el Cáncer
- ERC advanced grant
- Australian National Health and Medical Research Council
- Agence Nationale de la Recherche
- Dutch Prevention Funds,
- Agence Nationale de Sécurité Sanitaire de l'Alimentation, de l'Environnement et du Travail
- American Cancer Society
- Dutch Zorg Onderzoek
- Alexander von Humboldt-Stiftung
- Ministerio de Economia y Competitividad (Spain)
- Ministère du Développement Économique, de l’Innovation et de l’Exportation
- Susan G. Komen for the Cure
- Minister of Science and Higher Education
- Medical Research Council UK
- Ministry of Science and Higher Education of the Russian Federation
- Ministry of Science and Higher Education (Sweden)
- Against Breast Cancer
- Mutuelle Générale de l’Education Nationale
- Academy of Finland
- Deutsche Krebshilfe e.V.
- Dietmar-Hopp Foundation,
- Division of Cancer Prevention, National Cancer Institute
- Deutsche Krebshilfe
- World Cancer Research Fund
- Genome Québec
- National Cancer Institute’s Surveillance, Epidemiology and End Results Program
- Breast Cancer Campaign
- National Cancer Research Network
- Berta Kamprad Foundation FBKS
- Bert von Kantzows foundation
- Biomedical Research Centre at Guy’s and St Thomas
- Genome Canada
- Freistaat Sachsen
- Biobanking and Biomolecular Resources Research Infrastructure
- Friends of Hannover Medical School
- Breast Cancer Research Foundation
- California Department of Public Health
- Government of Russian Federation
- Deutsche Forschungsgemeinschaft
- National Institute for Health and Care Research
- National Health and Medical Research Council (Australia)
- German Federal Ministry of Research and Education
- National Institute of Environmental Health Sciences
- Breast Cancer Now
- Seventh Framework Programme
- Transcan
- Centrum för idrottsforskning
- UK National Institute for Health Research Biomedical Research Centre
- University of Crete
- National Breast Cancer Foundation (Finland)
- European Regional Development Fund
- National Breast Cancer Foundation (Australia)
- United States Army Medical Research and Materiel Command
- EU Horizon 2020 Research and Innovation Programme
- Directorate-General XII, Science, Research, and Development
- Baden Württemberg Ministry of Science, Research and Arts
- VicHealth
- Fondo de Investigación Sanitario
- Victorian Breast Cancer Research Consortium.
- Finnish Cancer Foundation
- University of Southern California San Francisco
- Fomento de la Investigación Clínica Independiente
- the Cancer Biology Research Center (CBRC), Djerassi Oncology Center
- Bundesministerium für Bildung und Forschung
- Cancerfonden
- Tel Aviv University Center for AI and Data Science
- University of Oulu
- National Breast Cancer Foundation (JS)
- Safra Center for Bioinformatics
- Fondation de France, Institut National du Cancer
- Israeli Science Foundation
- University of Utah
- National Cancer Center Research and Development Fund (Japan)
- Chief Scientist Office, Scottish Government Health and Social Care Directorate
- Oak Foundation
- Health Research Fund (FIS)
- Ontario Familial Breast Cancer Registry
- New South Wales Cancer Council
- North Carolina University Cancer Research Fund
- Kreftforeningen
- Northern California Breast Cancer Family Registry
- Institut Gustave Roussy
- Huntsman Cancer Institute, University of Utah
- Ovarian Cancer Research Fund
- NIHR Oxford Biomedical Research Centre
- Hellenic Health Foundation
- Oulun Yliopistollinen Sairaala
- Helmholtz Society
- Herlev and Gentofte Hospital
- PSRSIIRI-701
- Helsinki University Hospital Research Fund
- Cancer Council Victoria
- National Research Council (Italy)
- Cancer Council Tasmania
- Cancer Council Western Australia
- Hamburger Krebsgesellschaft
- Gustav V Jubilee foundation
- National Program of Cancer Registries
- Canadian Cancer Society
- Cancer Council South Australia
- Canadian Institutes of Health Research
- Cancer Council NSW
- Guy's & St. Thomas' NHS Foundation Trust
- Netherlands Organisation of Scientific Research
- Cancer Institute NSW
- National Institutes of Health (USA)
- National Research Foundation of Korea
- Syöpäsäätiö
- Cancer Foundation of Western Australia
- Netherlands Cancer Registry (NKR),
- Cancer Fund of North Savo
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Affiliation(s)
- Hagai Levi
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Saharon Rosset
- Department of Statistics and Operations Research, Tel Aviv University, Tel Aviv, Israel
| | - Rinat Yerushalmi
- Institute of Oncology, Davidoff Cancer Center, Rabin Medical Center, Beilinson Hospital, Petah Tikva, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Aviad Zick
- Department of oncology, Hadassah Medical Center, Jerusalem, Israel
- Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tamar Yablonski-Peretz
- Department of oncology, Hadassah Medical Center, Jerusalem, Israel
- Hebrew University of Jerusalem, Jerusalem, Israel
| | - Qin Wang
- 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
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Annelie Augustinsson
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Päivi Auvinen
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Oncology, University of Eastern Finland, Kuopio, Finland
- Department of Oncology, Cancer Center, Kuopio University Hospital, Kuopio, Finland
| | - Laura Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Matthias Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
| | - Clara Bodelon
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Natalia V Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, Copenhagen, Denmark
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Helen Byers
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Nicola Camp
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt lake city, UT, USA
| | - Jose Castelao
- Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo, Spain
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Wendy Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA
| | - Christine Clarke
- Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Margriet J Collee
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands
| | - Sarah Colonna
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt lake city, UT, USA
| | - Fergus Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Angela Cox
- Department of Oncology and Metabolism, Sheffield Institute for Nucleic Acids (SInFoNiA), University of Sheffield, Sheffield, UK
| | - Simon S Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mary Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, Netherlands
- Department of Human Genetics, Leiden University Medical, Leiden, Netherlands
| | - Thilo Dork
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
| | - Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Diana M Eccles
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Gareth Evans
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Peter Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Lin Fritschi
- School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Marike Gabrielson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, International Cancer Genetics and Epidemiology Group, Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Jeanine Genkinger
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, New York, New York, USA
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Mark Goldberg
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, Montreal, QU, Canada
| | - Pascal Guénel
- Team 'Exposome and Heredity', CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wei He
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter Hillemanns
- Gynaecology Research Unit, Hannover Medical School, Hamburg, Germany
| | | | - Reiner Hoppe
- Dr Margarete Fischer Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tubingen, Germany
| | - John Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Simona Jakovchevska
- Research Centre for Genetic Engineering and Biotechnology 'Georgi D. Efremov', Skopje, North Macedonia
| | - 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
| | - Helena Jernström
- Oncology, Department of Clinical Sciences in Lund, Lund University, Lund, Sweden
| | - Esther John
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nichola Johnson
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK
| | - Michael Jones
- Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK
| | - Joseph Vijai
- 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
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia
| | - Cari Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Vessela Kristensen
- Institute of Clinical Medicine, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Allison W Kurian
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - James Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
- VIB Center for Cancer Biology, VIB, Leuven, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Flavio Lejbkowicz
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Annika Lindblom
- Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Adriana Lori
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Mehdi Manoochehri
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece
| | - Usha Menon
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College, London, UK
| | - AnnaMarie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Rachel Murphy
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
- Cancer Control Research, BC Cancer Agency, Vancouver, BC, Canada
| | - Ines Nevelsteen
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
| | - William G Newman
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Nadia Obi
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Katie O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Ken 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
| | - Andrew Olshan
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Janet Olson
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
| | - Salvatore Panico
- Dipertimento Di Medicina Clinca e Chirurgia, Federico II University, Naples, Italy
| | | | - Alpa Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy
| | - Brigitte Rack
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Gad Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Valerie Rhenius
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Atocha Romero
- Laboratorio de Oncología Molecular, Hospital Clínico San Carlos, Madrid, Spain
| | | | - Dale Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Marjanka K Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Lukas Schwentner
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Priyanka Sharma
- Department of Internal Medicine, Division of Medical Oncology, University of Kansas Medical Center, Westwood, KS, USA
| | - Jacques Simard
- Genomics Center, Molecular Medicine, Université Laval, Quebec, Quebec, Canada
| | - Melissa Southey
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia
| | - William J Tapper
- Cancer Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Jack Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Lauren Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Amanda E Toland
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH, USA
| | - Melissa Troester
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Thérèse Truong
- Team 'Exposome and Heredity', CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
| | | | - Clarice Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Camilla Wendt
- Department of Clinical Science and Education, Karolinska Institutet, Stockholm, Sweden
| | - Xiaohong Rose Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Argyrios Ziogas
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Paul Pharoah
- 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
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA, USA
| | - 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
| | - Shay Ben-Sachar
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Clalit Research Institute, Clalit Health Services, Ramat Gan, Israel
| | - Naama Elefant
- Clalit Research Institute, Clalit Health Services, Ramat Gan, Israel
- Department of Genetics, Hadassah Medical Center, Jerusalem, Israel
| | - Ron Shamir
- The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Ran Elkon
- Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel
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5
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Mbuya-Bienge C, Pashayan N, Kazemali CD, Lapointe J, Simard J, Nabi H. A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population. Cancers (Basel) 2023; 15:5380. [PMID: 38001640 PMCID: PMC10670420 DOI: 10.3390/cancers15225380] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/26/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices.
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Affiliation(s)
- Cynthia Mbuya-Bienge
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Nora Pashayan
- Department of Applied Health Research, University College London, London WC1E 6BT, UK;
| | - Cornelia D. Kazemali
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Jacques Simard
- Endocrinology and Nephology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1V 4G2, Canada;
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Hermann Nabi
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
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6
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Tshiaba PT, Ratman DK, Sun JM, Tunstall TS, Levy B, Shah PS, Weitzel JN, Rabinowitz M, Kumar A, Im KM. Integration of a Cross-Ancestry Polygenic Model With Clinical Risk Factors Improves Breast Cancer Risk Stratification. JCO Precis Oncol 2023; 7:e2200447. [PMID: 36809055 DOI: 10.1200/po.22.00447] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023] Open
Abstract
PURPOSE To develop and validate a cross-ancestry integrated risk score (caIRS) that combines a cross-ancestry polygenic risk score (caPRS) with a clinical estimator for breast cancer (BC) risk. We hypothesized that the caIRS is a better predictor of BC risk than clinical risk factors across diverse ancestry groups. METHODS We used diverse retrospective cohort data with longitudinal follow-up to develop a caPRS and integrate it with the Tyrer-Cuzick (T-C) clinical model. We tested the association between the caIRS and BC risk in two validation cohorts including > 130,000 women. We compared model discrimination for 5-year and remaining lifetime BC risk between the caIRS and T-C and assessed how the caIRS would affect screening in the clinic. RESULTS The caIRS outperformed T-C alone for all populations tested in both validation cohorts and contributed significantly to risk prediction beyond T-C. The area under the receiver operating characteristic curve improved from 0.57 to 0.65, and the odds ratio per standard deviation increased from 1.35 (95% CI, 1.27 to 1.43) to 1.79 (95% CI, 1.70 to 1.88) in validation cohort 1 with similar improvements observed in validation cohort 2. We observed the largest gain in positive predictive value using the caIRS in Black/African American women across both validation cohorts, with an approximately two-fold increase and an equivalent negative predictive value as the T-C. In a multivariate, age-adjusted logistic regression model including both caIRS and T-C, caIRS remained significant, indicating that caIRS provides information over T-C alone. CONCLUSION Adding a caPRS to the T-C model improves BC risk stratification for women of multiple ancestries, which could have implications for screening recommendations and prevention.
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Affiliation(s)
| | | | | | | | - Brynn Levy
- MyOme Inc, Menlo Park, CA.,Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY
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7
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Roberts E, Howell S, Evans DG. Polygenic risk scores and breast cancer risk prediction. Breast 2023; 67:71-77. [PMID: 36646003 PMCID: PMC9982311 DOI: 10.1016/j.breast.2023.01.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 01/09/2023] [Indexed: 01/11/2023] Open
Abstract
Polygenic Risk Scores (PRS) are a major component of accurate breast cancer risk prediction and have the potential to improve screening and prevention strategies. PRS combine the risk from Single nucleotide polymorphisms (SNPs) associated with breast cancer in Genome Wide Association Studies (GWAS) and explain over 30% of breast cancer heritability. When incorporated into risk models, the more personalised risk assessment derived from PRS, help identify women at higher risk of breast cancer development and enables the implementation of stratified screening and prevention approaches. This review describes the role of PRS in breast cancer risk prediction including the development of PRS and their clinical application. We have also examined the role of PRS within more well-established risk prediction models which incorporate known classic risk factors and discuss the interaction of PRS with these factors and their capacity to predict breast cancer subtypes. Before PRS can be implemented on a population-wide scale, there are several challenges that must be addressed. Perhaps the most pressing of these is the use of PRS in women of non-White European origin, where PRS have been shown to have attenuated risk prediction both in discrimination and calibration. We discuss progress in developing and applying PRS in non-white European populations. PRS represent a significant advance in breast cancer risk prediction and their further development will undoubtedly enhance personalisation.
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Affiliation(s)
- Eleanor Roberts
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Sacha Howell
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK
| | - D Gareth Evans
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK.
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8
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Hughes E, Wagner S, Pruss D, Bernhisel R, Probst B, Abkevich V, Simmons T, Hullinger B, Judkins T, Rosenthal E, Roa B, Domchek SM, Eng C, Garber J, Gary M, Klemp J, Mukherjee S, Offit K, Olopade OI, Vijai J, Weitzel JN, Whitworth P, Yehia L, Gordon O, Pederson H, Kurian A, Slavin TP, Gutin A, Lanchbury JS. Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition. JCO Precis Oncol 2022; 6:e2200084. [PMID: 36331239 PMCID: PMC9666117 DOI: 10.1200/po.22.00084] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 07/11/2022] [Accepted: 09/08/2022] [Indexed: 08/12/2023] Open
Abstract
PURPOSE Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases. MATERIALS AND METHODS Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution. RESULTS In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; P = 8.6 × 10-308) and within each major ancestry. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women. CONCLUSION The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Susan M. Domchek
- Basser Center for BRCA, University of Pennsylvania, Philadelphia, PA
| | - Charis Eng
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH
| | | | | | - Jennifer Klemp
- The University of Kansas Cancer Center, The University of Kansas Medical Center, Kansas City, KS
| | | | - Kenneth Offit
- Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Joseph Vijai
- Memorial Sloan Kettering Cancer Center, New York, NY
| | | | | | - Lamis Yehia
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH
| | - Ora Gordon
- Providence Health and Services, Renton, WA
| | - Holly Pederson
- Medical Breast Services, Cleveland Clinic, Cleveland, OH
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9
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Kim MS, Naidoo D, Hazra U, Quiver MH, Chen WC, Simonti CN, Kachambwa P, Harlemon M, Agalliu I, Baichoo S, Fernandez P, Hsing AW, Jalloh M, Gueye SM, Niang L, Diop H, Ndoye M, Snyper NY, Adusei B, Mensah JE, Abrahams AOD, Biritwum R, Adjei AA, Adebiyi AO, Shittu O, Ogunbiyi O, Adebayo S, Aisuodionoe-Shadrach OI, Nwegbu MM, Ajibola HO, Oluwole OP, Jamda MA, Singh E, Pentz A, Joffe M, Darst BF, Conti DV, Haiman CA, Spies PV, van der Merwe A, Rohan TE, Jacobson J, Neugut AI, McBride J, Andrews C, Petersen LN, Rebbeck TR, Lachance J. Testing the generalizability of ancestry-specific polygenic risk scores to predict prostate cancer in sub-Saharan Africa. Genome Biol 2022; 23:194. [PMID: 36100952 PMCID: PMC9472407 DOI: 10.1186/s13059-022-02766-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 09/05/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa. RESULTS Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608-0.707, OR 2.37-5.71) than for African individuals (AUC 0.502-0.585, OR 0.95-2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores. CONCLUSIONS Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities.
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Affiliation(s)
- Michelle S Kim
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA, 30332, USA
| | - Daphne Naidoo
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | - Ujani Hazra
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA, 30332, USA
| | - Melanie H Quiver
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA, 30332, USA
| | - Wenlong C Chen
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,National Cancer Registry, National Health Laboratory Service, Johannesburg, South Africa
| | - Corinne N Simonti
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA, 30332, USA
| | | | - Maxine Harlemon
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA, 30332, USA
| | - Ilir Agalliu
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | | | - Pedro Fernandez
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Ann W Hsing
- Stanford Cancer Institute, Stanford University, Stanford, CA, USA
| | | | | | - Lamine Niang
- Universite Cheikh Anta Diop de Dakar, Dakar, Senegal
| | | | - Medina Ndoye
- Universite Cheikh Anta Diop de Dakar, Dakar, Senegal
| | | | | | - James E Mensah
- Korle-Bu Teaching Hospital and University of Ghana Medical School, Accra, Ghana
| | - Afua O D Abrahams
- Korle-Bu Teaching Hospital and University of Ghana Medical School, Accra, Ghana
| | - Richard Biritwum
- Korle-Bu Teaching Hospital and University of Ghana Medical School, Accra, Ghana
| | - Andrew A Adjei
- Department of Pathology, University of Ghana Medical School, Accra, Ghana
| | | | | | | | - Sikiru Adebayo
- College of Medicine, University of Ibadan, Ibadan, Nigeria
| | | | - Maxwell M Nwegbu
- College of Health Sciences, University of Abuja and University of Abuja Teaching Hospital, Abuja, Nigeria
| | - Hafees O Ajibola
- College of Health Sciences, University of Abuja and University of Abuja Teaching Hospital, Abuja, Nigeria
| | - Olabode P Oluwole
- College of Health Sciences, University of Abuja and University of Abuja Teaching Hospital, Abuja, Nigeria
| | - Mustapha A Jamda
- College of Health Sciences, University of Abuja and University of Abuja Teaching Hospital, Abuja, Nigeria
| | - Elvira Singh
- National Cancer Registry, National Health Laboratory Service, Johannesburg, South Africa
| | - Audrey Pentz
- Non-Communicable Diseases Research Division, Wits Health Consortium (PTY) Ltd, Johannesburg, South Africa
| | - Maureen Joffe
- Non-Communicable Diseases Research Division, Wits Health Consortium (PTY) Ltd, Johannesburg, South Africa.,MRC Developmental Pathways to Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
| | - Burcu F Darst
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - David V Conti
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A Haiman
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Petrus V Spies
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - André van der Merwe
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Thomas E Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Judith Jacobson
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Alfred I Neugut
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | - Jo McBride
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | | | | | - Timothy R Rebbeck
- Dana-Farber Cancer Institute, Boston, MA, USA.,Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Dr, Atlanta, GA, 30332, USA.
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10
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Gao G, Zhao F, Ahearn TU, Lunetta KL, Troester MA, Du Z, Ogundiran TO, Ojengbede O, Blot W, Nathanson KL, Domchek SM, Nemesure B, Hennis A, Ambs S, McClellan J, Nie M, Bertrand K, Zirpoli G, Yao S, Olshan AF, Bensen JT, Bandera EV, Nyante S, Conti DV, Press MF, Ingles SA, John EM, Bernstein L, Hu JJ, Deming-Halverson SL, Chanock SJ, Ziegler RG, Rodriguez-Gil JL, Sucheston-Campbell LE, Sandler DP, Taylor JA, Kitahara CM, O’Brien KM, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Wang Q, Figueroa J, Biritwum R, Adjei E, Wiafe S, Ambrosone CB, Zheng W, Olopade OI, García-Closas M, Palmer JR, Haiman CA, Huo D. Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach. Hum Mol Genet 2022; 31:3133-3143. [PMID: 35554533 PMCID: PMC9476624 DOI: 10.1093/hmg/ddac102] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 03/29/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.
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Affiliation(s)
- Guimin Gao
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Fangyuan Zhao
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Melissa A Troester
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhaohui Du
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Temidayo O Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oladosu Ojengbede
- Centre for Population & Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Katherine L Nathanson
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Susan M Domchek
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | - Anselm Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
- University of the West Indies, Bridgetown, Bardados
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Julian McClellan
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Mark Nie
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | | | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, Boston, MA 02215, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jeannette T Bensen
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Elisa V Bandera
- Cancer Prevention and Control Program, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA
| | - Sarah Nyante
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - David V Conti
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Michael F Press
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Sue A Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Esther M John
- Departments of Epidemiology & Population Health and of Medicine (Oncology) and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Leslie Bernstein
- Biomarkers of Early Detection and Prevention, Department of Population Sciences, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA
| | - Jennifer J Hu
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Sandra L Deming-Halverson
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Jorge L Rodriguez-Gil
- Genomics, Development and Disease Section, Genetic Disease Research Branch, National Human Genome Research Institute, Bethesda, MD 20894, USA
| | - Lara E Sucheston-Campbell
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Cari M Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katie M O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Manjeet K Bolla
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Joe Dennis
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Alison M Dunning
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia 2371, Cyprus
| | - Paul D P Pharoah
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Qin Wang
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Jonine Figueroa
- Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh EH16 5TJ, UK
- Cancer Research UK Edinburgh Centre, Edinburgh EH4 2XR, UK
| | | | | | - Seth Wiafe
- School of Public Health, Loma Linda University, Loma Linda, CA 92350, USA
| | | | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL 60637, USA
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, Boston, MA 02215, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Dezheng Huo
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL 60637, USA
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11
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Racial disparities in breast cancer preclinical and clinical models. BREAST CANCER RESEARCH : BCR 2022; 24:56. [PMID: 35932017 PMCID: PMC9354441 DOI: 10.1186/s13058-022-01551-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 07/26/2022] [Indexed: 11/10/2022]
Abstract
Breast cancer (BCa) has long been a health burden to women across the globe. However, the burden is not equally carried across races. Though the manifestation and behavior of BCa differs among racial groups, the racial representation of models used in preclinical trials and clinical trial participants lacks this heterogeneity. Women of African Ancestry (WAA) are disproportionately afflicted by having an increased risk of developing BCas that are more aggressive in nature, and consequently suffer from poorer outcomes relative to women of European ancestry (WEA). Notwithstanding this, one of the most commonly used tools in studying BCa, cell lines, exhibit a sizeable gap in cell line derivatives of WEA relative to WAA. In this review, we summarize the available BCa cell lines grouped by race by major suppliers, American Type Culture Collection (ATCC) and the European Collection of Authenticated Cell Cultures (ECACC). Next, examined the enrollment of WAA in clinical trials for BCa. Of the cell lines found provided by ATCC and ECACC, those derived from WEA constituted approximately 80% and 94%, respectively. The disparity is mirrored in clinical trial enrollment where, on average, WEA made up more than 70% of participants in trials found where ancestry information was provided. As both experimental models and clinical trial participants primarily consist of WEA, results may have poorer translatability toward other races. This highlights the need for greater racial diversity at the preclinical and clinical levels to more accurately represent the population and strengthen the translatability of results.
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12
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Role of Polygenic Risk Score in Cancer Precision Medicine of Non-European Populations: A Systematic Review. Curr Oncol 2022; 29:5517-5530. [PMID: 36005174 PMCID: PMC9406904 DOI: 10.3390/curroncol29080436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/28/2022] [Accepted: 08/01/2022] [Indexed: 11/17/2022] Open
Abstract
The development of new screening methods and diagnostic tests for traits, common diseases, and cancer is linked to the advent of precision genomic medicine, in which health care is individually adjusted based on a person’s lifestyle, environmental influences, and genetic variants. Based on genome-wide association study (GWAS) analysis, rapid and continuing progress in the discovery of relevant single nucleotide polymorphisms (SNPs) for traits or complex diseases has increased interest in the potential application of genetic risk models for routine health practice. The polygenic risk score (PRS) estimates an individual’s genetic risk of a trait or disease, calculated by employing a weighted sum of allele counts combined with non-genetic variables. However, 98.38% of PRS records held in public databases relate to the European population. Therefore, PRSs for multiethnic populations are urgently needed. We performed a systematic review to discuss the role of polygenic risk scores in advancing precision medicine for different cancer types in multiethnic non-European populations.
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13
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Trastulla L, Noorbakhsh J, Vazquez F, McFarland J, Iorio F. Computational estimation of quality and clinical relevance of cancer cell lines. Mol Syst Biol 2022; 18:e11017. [PMID: 35822563 PMCID: PMC9277610 DOI: 10.15252/msb.202211017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 12/12/2022] Open
Abstract
Immortal cancer cell lines (CCLs) are the most widely used system for investigating cancer biology and for the preclinical development of oncology therapies. Pharmacogenomic and genome-wide editing screenings have facilitated the discovery of clinically relevant gene-drug interactions and novel therapeutic targets via large panels of extensively characterised CCLs. However, tailoring pharmacological strategies in a precision medicine context requires bridging the existing gaps between tumours and in vitro models. Indeed, intrinsic limitations of CCLs such as misidentification, the absence of tumour microenvironment and genetic drift have highlighted the need to identify the most faithful CCLs for each primary tumour while addressing their heterogeneity, with the development of new models where necessary. Here, we discuss the most significant limitations of CCLs in representing patient features, and we review computational methods aiming at systematically evaluating the suitability of CCLs as tumour proxies and identifying the best patient representative in vitro models. Additionally, we provide an overview of the applications of these methods to more complex models and discuss future machine-learning-based directions that could resolve some of the arising discrepancies.
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Affiliation(s)
| | - Javad Noorbakhsh
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Present address:
Kojin TherapeuticsBostonMAUSA
| | - Francisca Vazquez
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Medical OncologyDana‐Farber Cancer InstituteBostonMAUSA
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14
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Galisa SLG, Jacob PL, de Farias AA, Lemes RB, Alves LU, Nóbrega JCL, Zatz M, Santos S, Weller M. Haplotypes of single cancer driver genes and their local ancestry in a highly admixed long-lived population of Northeast Brazil. Genet Mol Biol 2022; 45:e20210172. [PMID: 35112701 PMCID: PMC8811751 DOI: 10.1590/1678-4685-gmb-2021-0172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 11/17/2021] [Indexed: 12/02/2022] Open
Abstract
Admixed populations have not been examined in detail in cancer genetic studies. Here, we inferred the local ancestry of cancer-associated single nucleotide polymorphisms (SNPs) and haplotypes of a highly admixed Brazilian population. SNP array was used to genotype 73 unrelated individuals aged 80-102 years. Local ancestry inference was performed by merging genotyped regions with phase three data from the 1000 Genomes Project Consortium using RFmix. The average ancestry tract length was 9.12-81.71 megabases. Strong linkage disequilibrium was detected in 48 haplotypes containing 35 SNPs in 10 cancer driver genes. All together, 19 risk and eight protective alleles were identified in 23 out of 48 haplotypes. Homozygous individuals were mainly of European ancestry, whereas heterozygotes had at least one Native American and one African ancestry tract. Native-American ancestry for homozygous individuals with risk alleles for HNF1B, CDH1, and BRCA1 was inferred for the first time. Results indicated that analysis of SNP polymorphism in the present admixed population has a high potential to identify new ancestry-associated alleles and haplotypes that modify cancer susceptibility differentially in distinct human populations. Future case-control studies with populations with a complex history of admixture could help elucidate ancestry-associated biological differences in cancer incidence and therapeutic outcomes.
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Affiliation(s)
- Steffany Larissa Galdino Galisa
- Universidade Estadual da Paraíba (UEPB), Núcleo de Estudos em
Genética e Educação, Programa de Pós-Graduação em Saúde Pública, Campina Grande, PB,
Brazil
| | - Priscila Lima Jacob
- Universidade Estadual da Paraíba (UEPB), Núcleo de Estudos em
Genética e Educação, Programa de Pós-Graduação em Saúde Pública, Campina Grande, PB,
Brazil
| | - Allysson Allan de Farias
- Universidade Estadual da Paraíba (UEPB), Núcleo de Estudos em
Genética e Educação, Programa de Pós-Graduação em Saúde Pública, Campina Grande, PB,
Brazil
- Universidade de São Paulo (USP), Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Renan Barbosa Lemes
- Universidade de São Paulo (USP), Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Leandro Ucela Alves
- Universidade Estadual da Paraíba (UEPB), Núcleo de Estudos em
Genética e Educação, Programa de Pós-Graduação em Saúde Pública, Campina Grande, PB,
Brazil
- Universidade de São Paulo (USP), Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Júlia Cristina Leite Nóbrega
- Universidade Estadual da Paraíba (UEPB), Núcleo de Estudos em
Genética e Educação, Programa de Pós-Graduação em Saúde Pública, Campina Grande, PB,
Brazil
| | - Mayana Zatz
- Universidade de São Paulo (USP), Departamento de Genética e Biologia
Evolutiva, São Paulo, SP, Brazil
| | - Silvana Santos
- Universidade Estadual da Paraíba (UEPB), Núcleo de Estudos em
Genética e Educação, Programa de Pós-Graduação em Saúde Pública, Campina Grande, PB,
Brazil
- Universidade Estadual da Paraíba (UEPB), Departamento de Biologia,
Campina Grande, PB, Brazil
| | - Mathias Weller
- Universidade Estadual da Paraíba (UEPB), Núcleo de Estudos em
Genética e Educação, Programa de Pós-Graduação em Saúde Pública, Campina Grande, PB,
Brazil
- Universidade Estadual da Paraíba (UEPB), Departamento de Biologia,
Campina Grande, PB, Brazil
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15
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Evans DG, van Veen EM, Byers H, Roberts E, Howell A, Howell SJ, Harkness EF, Brentnall A, Cuzick J, Newman WG. The importance of ethnicity: Are breast cancer polygenic risk scores ready for women who are not of White European origin? Int J Cancer 2022; 150:73-79. [PMID: 34460111 PMCID: PMC9290473 DOI: 10.1002/ijc.33782] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 07/08/2021] [Accepted: 08/02/2021] [Indexed: 11/07/2022]
Abstract
Polygenic risk scores (PRS) for disease risk stratification show great promise for application in general populations, but most are based on data from individuals of White European origin. We assessed two well validated PRS (SNP18, SNP143) in the Predicting-Risk-of-Cancer-At-Screening (PROCAS) study in North-West England for breast cancer prediction based on ethnicity. Overall, 9475 women without breast cancer at study entry, including 645 who subsequently developed invasive breast cancer or ductal carcinoma in situ provided DNA. All were genotyped for SNP18 and a subset of 1868 controls were genotyped for SNP143. For White Europeans both PRS discriminated well between individuals with and without cancer. For n = 395 Black (n = 112), Asian (n = 119), mixed (n = 44) or Jewish (n = 120) women without cancer both PRS overestimated breast cancer risk, being most marked for women of Black and Jewish origin (P < .001). SNP143 resulted in a potential mean 40% breast cancer risk overestimation in the combined group of non-White/non-European origin. SNP-PRS that has been normalized based on White European ethnicity for breast cancer should not be used to predict risk in women of other ethnicities. There is an urgent need to develop PRS specific for other ethnicities, in order to widen access of this technology.
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MESH Headings
- Adult
- Aged
- Biomarkers, Tumor/genetics
- Breast Density
- Breast Neoplasms/epidemiology
- Breast Neoplasms/genetics
- Breast Neoplasms/pathology
- Carcinoma, Ductal, Breast/epidemiology
- Carcinoma, Ductal, Breast/genetics
- Carcinoma, Ductal, Breast/pathology
- Carcinoma, Intraductal, Noninfiltrating/epidemiology
- Carcinoma, Intraductal, Noninfiltrating/genetics
- Carcinoma, Intraductal, Noninfiltrating/pathology
- Case-Control Studies
- England/epidemiology
- Ethnicity/genetics
- Female
- Follow-Up Studies
- Genetic Predisposition to Disease
- Humans
- Middle Aged
- Polymorphism, Single Nucleotide
- Prognosis
- Risk Factors
- White People/genetics
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Affiliation(s)
- D. Gareth Evans
- Nightingale/Prevent Breast Cancer Centre, Wythenshawe HospitalManchester University NHS Foundation TrustManchesterUK
- Manchester Breast Centre, Manchester Cancer Research CentreThe Christie HospitalManchesterUK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation TrustManchesterUK
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation TrustManchesterUK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and HealthUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
| | - Elke M. van Veen
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation TrustManchesterUK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and HealthUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
| | - Helen Byers
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation TrustManchesterUK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and HealthUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
| | - Eleanor Roberts
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
| | - Anthony Howell
- Nightingale/Prevent Breast Cancer Centre, Wythenshawe HospitalManchester University NHS Foundation TrustManchesterUK
- Manchester Breast Centre, Manchester Cancer Research CentreThe Christie HospitalManchesterUK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
| | - Sacha J. Howell
- Nightingale/Prevent Breast Cancer Centre, Wythenshawe HospitalManchester University NHS Foundation TrustManchesterUK
- Manchester Breast Centre, Manchester Cancer Research CentreThe Christie HospitalManchesterUK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of ManchesterManchester Academic Health Science CentreManchesterUK
| | - Elaine F. Harkness
- Nightingale/Prevent Breast Cancer Centre, Wythenshawe HospitalManchester University NHS Foundation TrustManchesterUK
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
| | - Adam Brentnall
- Queen Mary University of London, Centre for Cancer Prevention, Wolfson Institute of Preventive MedicineLondonUK
| | - Jack Cuzick
- Queen Mary University of London, Centre for Cancer Prevention, Wolfson Institute of Preventive MedicineLondonUK
| | - William G. Newman
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation TrustManchesterUK
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation TrustManchesterUK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and HealthUniversity of Manchester, Manchester Academic Health Science CentreManchesterUK
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16
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Wang Y, Zhu M, Ma H, Shen H. Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention. MEDICAL REVIEW (BERLIN, GERMANY) 2021; 1:129-149. [PMID: 37724297 PMCID: PMC10471106 DOI: 10.1515/mr-2021-0025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 12/13/2021] [Indexed: 09/20/2023]
Abstract
Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of an individual's genetic susceptibility to cancer. Recently, PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer, which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk. In this context, we provide an overview of the major discoveries from cancer GWASs. We then review the methodologies used for PRS construction, and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors. Potential utility of PRSs in cancer risk prediction, screening, and precision prevention are illustrated. Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed.
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Affiliation(s)
- Yuzhuo Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
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17
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A Higher Polygenic Risk Score Is Associated with a Higher Recurrence Rate of Atrial Fibrillation in Direct Current Cardioversion-Treated Patients. Medicina (B Aires) 2021; 57:medicina57111263. [PMID: 34833481 PMCID: PMC8624440 DOI: 10.3390/medicina57111263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 11/08/2021] [Accepted: 11/16/2021] [Indexed: 11/23/2022] Open
Abstract
Background and Objectives: Recurrence of atrial fibrillation (AF) within six months after sinus rhythm restoration with direct current cardioversion (DCC) is a significant treatment challenge. Currently, the factors influencing outcome are mostly unknown. Studies have found a link between genetics and the risk of AF and efficacy of rhythm control. The aim of this study was to examine the association between eight single-nucleotide variants (SNVs) and the risk of AF development and recurrence after DCC. Materials and Methods: Regarding the occurrence of AF, 259 AF cases and 108 controls were studied. Genotypes for the eight SNVs located in the genes CAV1, MYH7, SOX5, KCNN3, ZFHX3, KCNJ5 and PITX2 were determined using high-resolution melting analysis and confirmed with Sanger sequencing. Six months after DCC, a telephone interview was conducted to determine whether AF had recurred. A polygenic risk score (PRS) was calculated as the unweighted sum of risk alleles. Multivariate regression analyses were performed to assess SNV and PRS association with AF occurrence and recurrence after DCC. Results: The risk allele of rs2200733 (PITX2) was significantly associated with the development of AF (p = 0.012, OR = 2.31, 95% CI = 1.206–4.423). AF recurred in 60% of patients and the allele generally associated with a decreased risk of AF of rs11047543 (SOX5) was associated with a greater risk of AF recurrence (p = 0.014, OR = 0.223, 95% CI = 0.067–0.738). A PRS of greater than 7 was significantly associated (p = 0.008) with a higher likelihood of developing AF after DCC (OR = 4.174, 95% CI = 1.454–11.980). Conclusions: A higher PRS is associated with increased odds of AF recurrence after treatment with DCC. PITX2 (rs2200733) is significantly associated with an increased risk of AF. The protective allele of rs11047543 (SOX5) is associated with a greater risk of AF recurrence. Further studies are needed to predict the success of rhythm control and guide patient selection towards the most efficacious treatment.
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18
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Liu C, Zeinomar N, Chung WK, Kiryluk K, Gharavi AG, Hripcsak G, Crew KD, Shang N, Khan A, Fasel D, Manolio TA, Jarvik GP, Rowley R, Justice AE, Rahm AK, Fullerton SM, Smoller JW, Larson EB, Crane PK, Dikilitas O, Wiesner GL, Bick AG, Terry MB, Weng C. Generalizability of Polygenic Risk Scores for Breast Cancer Among Women With European, African, and Latinx Ancestry. JAMA Netw Open 2021; 4:e2119084. [PMID: 34347061 PMCID: PMC8339934 DOI: 10.1001/jamanetworkopen.2021.19084] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
IMPORTANCE Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. OBJECTIVE To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. DESIGN, SETTING, AND PARTICIPANTS This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. MAIN OUTCOMES AND MEASURES Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. RESULTS This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. CONCLUSIONS AND RELEVANCE This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.
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Affiliation(s)
- Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Nur Zeinomar
- Department of Epidemiology, Columbia University Irving Medical Center, New York, New York
- Division of Medical Oncology, Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, New Jersey
| | - Wendy K. Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Krzysztof Kiryluk
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Ali G. Gharavi
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Katherine D. Crew
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Ning Shang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Atlas Khan
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - David Fasel
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Teri A. Manolio
- National Human Genome Research Institute, Bethesda, Maryland
| | - Gail P. Jarvik
- Department of Medicine, University of Washington, Seattle
| | - Robb Rowley
- National Human Genome Research Institute, Bethesda, Maryland
| | - Ann E. Justice
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | - Alanna K. Rahm
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
| | - Georgia L. Wiesner
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Alexander G. Bick
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Mary Beth Terry
- Department of Epidemiology, Columbia University Irving Medical Center, New York, New York
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
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19
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Minnier J, Rajeevan N, Gao L, Park B, Pyarajan S, Spellman P, Haskell SG, Brandt CA, Luoh SW. Polygenic Breast Cancer Risk for Women Veterans in the Million Veteran Program. JCO Precis Oncol 2021; 5:PO.20.00541. [PMID: 34381935 DOI: 10.1200/po.20.00541] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 04/15/2021] [Accepted: 06/11/2021] [Indexed: 01/02/2023] Open
Abstract
Accurate breast cancer (BC) risk assessment allows personalized screening and prevention. Prospective validation of prediction models is required before clinical application. Here, we evaluate clinical- and genetic-based BC prediction models in a prospective cohort of women from the Million Veteran Program. MATERIALS AND METHODS Clinical BC risk prediction models were validated in combination with a genetic polygenic risk score of 313 (PRS313) single-nucleotide polymorphisms in genetic females without prior BC diagnosis (n = 35,130, mean age 49 years) with 30% non-Hispanic African ancestry (AA). Clinical risk models tested were Breast and Prostate Cancer Cohort Consortium, literature review, and Breast Cancer Risk Assessment Tool, and implemented with or without PRS313. Prediction accuracy and association with incident breast cancer was evaluated with area under the receiver operating characteristic curve (AUC), hazard ratios, and proportion with high absolute lifetime risk. RESULTS Three hundred thirty-eight participants developed incident breast cancers with a median follow-up of 3.9 years (2.5 cases/1,000 person-years), with 196 incident cases in women of European ancestry and 112 incident cases in AA women. Individualized Coherent Absolute Risk Estimator-literature review in combination with PRS313 had an AUC of 0.708 (95% CI, 0.659 to 0.758) in women with European or non-African ancestries and 0.625 (0.539 to 0.711) in AA women. Breast Cancer Risk Assessment Tool with PRS313 had an AUC of 0.695 (0.62 to 0.729) in European or non-AA and 0.675 (0.626 to 0.723) in AA women. Incorporation of PRS313 with clinical models improved prediction in European but not in AA women. Models estimated up to 9% of European and 18% of AA women with absolute lifetime risk > 20%. CONCLUSION Clinical and genetic BC risk models predict incident BC in a large prospective multiracial cohort; however, more work is needed to improve genetic risk estimation in AA women.
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Affiliation(s)
- Jessica Minnier
- OHSU-PSU School of Public Health, Oregon Health & Science University, Portland, OR.,Knight Cancer Institute, Oregon Health & Science University, Portland, OR.,VA Portland Health Care System, Portland, OR
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT.,Yale Center for Medical Informatics (YCMI), Yale School of Medicine, New Haven, CT
| | - Lina Gao
- OHSU-PSU School of Public Health, Oregon Health & Science University, Portland, OR.,Knight Cancer Institute, Oregon Health & Science University, Portland, OR.,VA Portland Health Care System, Portland, OR
| | - Byung Park
- OHSU-PSU School of Public Health, Oregon Health & Science University, Portland, OR.,Knight Cancer Institute, Oregon Health & Science University, Portland, OR.,VA Portland Health Care System, Portland, OR
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA.,Department of Medicine, Harvard Medical School, Boston, MA
| | - Paul Spellman
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR.,VA Portland Health Care System, Portland, OR
| | - Sally G Haskell
- VA Connecticut Healthcare System, West Haven, CT.,Department of Internal Medicine, Yale School of Medicine, New Haven, CT
| | - Cynthia A Brandt
- Yale Center for Medical Informatics (YCMI), Yale School of Medicine, New Haven, CT.,VA Connecticut Healthcare System, West Haven, CT
| | - Shiuh-Wen Luoh
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR.,VA Portland Health Care System, Portland, OR
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20
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Salas LA, Lundgren SN, Browne EP, Punska EC, Anderton DL, Karagas MR, Arcaro KF, Christensen BC. Prediagnostic breast milk DNA methylation alterations in women who develop breast cancer. Hum Mol Genet 2021; 29:662-673. [PMID: 31943067 PMCID: PMC7068171 DOI: 10.1093/hmg/ddz301] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 11/30/2019] [Accepted: 12/06/2019] [Indexed: 12/16/2022] Open
Abstract
Prior candidate gene studies have shown tumor suppressor DNA methylation in breast milk related with history of breast biopsy, an established risk factor for breast cancer. To further establish the utility of breast milk as a tissue-specific biospecimen for investigations of breast carcinogenesis, we measured genome-wide DNA methylation in breast milk from women with and without a diagnosis of breast cancer in two independent cohorts. DNA methylation was assessed using Illumina HumanMethylation450k in 87 breast milk samples. Through an epigenome-wide association study we explored CpG sites associated with a breast cancer diagnosis in the prospectively collected milk samples from the breast that would develop cancer compared with women without a diagnosis of breast cancer using linear mixed effects models adjusted for history of breast biopsy, age, RefFreeCellMix cell estimates, time of delivery, array chip and subject as random effect. We identified 58 differentially methylated CpG sites associated with a subsequent breast cancer diagnosis (q-value <0.05). Nearly all CpG sites associated with a breast cancer diagnosis were hypomethylated in cases compared with controls and were enriched for CpG islands. In addition, inferred repeat element methylation was lower in breast milk DNA from cases compared to controls, and cases exhibited increased estimated epigenetic mitotic tick rate as well as DNA methylation age compared with controls. Breast milk has utility as a biospecimen for prospective assessment of disease risk, for understanding the underlying molecular basis of breast cancer risk factors and improving primary and secondary prevention of breast cancer.
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Affiliation(s)
- Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH 03766, USA.,The Children's Environmental Health and Disease Prevention Research Center at Dartmouth, Hanover, NH 03766, USA
| | - Sara N Lundgren
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH 03766, USA.,The Children's Environmental Health and Disease Prevention Research Center at Dartmouth, Hanover, NH 03766, USA
| | - Eva P Browne
- Department of Veterinary & Animal Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Elizabeth C Punska
- Department of Veterinary & Animal Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Douglas L Anderton
- Department of Sociology, University of South Carolina, Columbus, SC 29208, USA
| | - Margaret R Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH 03766, USA.,The Children's Environmental Health and Disease Prevention Research Center at Dartmouth, Hanover, NH 03766, USA
| | - Kathleen F Arcaro
- Department of Veterinary & Animal Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH 03766, USA.,Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH 03766, USA.,Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Hanover, NH 03766, USA
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21
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Zeinomar N, Chung WK. Cases in Precision Medicine: The Role of Polygenic Risk Scores in Breast Cancer Risk Assessment. Ann Intern Med 2021; 174:408-412. [PMID: 33253037 PMCID: PMC7965355 DOI: 10.7326/m20-5874] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Polygenic risk scores (PRSs) have been consistently associated with elevated breast cancer risk in cohort studies and are associated with risk in both women with and those without a family history of breast cancer. However, before clinical implementation, several issues must be addressed, including understanding the potential clinical utility and optimal method to communicate personalized screening recommendations that incorporate the PRS. Several trials are under way to answer some of these questions and facilitate clinical implementation. Because these PRSs have been developed in women of European ancestry, it is important to understand the limitations of their predictive ability in other ancestral groups. Finally, the value of the PRS will lie in considering it along with other clinical, familial, and rare genetic factors that are currently used in personalized risk assessment of breast cancer.
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Affiliation(s)
- Nur Zeinomar
- Mailman School of Public Health, Columbia University, New York, New York (N.Z.)
| | - Wendy K Chung
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, Columbia University, New York, New York (W.K.C.)
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22
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Shieh Y, Fejerman L, Lott PC, Marker K, Sawyer SD, Hu D, Huntsman S, Torres J, Echeverry M, Bohórquez ME, Martínez-Chéquer JC, Polanco-Echeverry G, Estrada-Flórez AP, Haiman CA, John EM, Kushi LH, Torres-Mejía G, Vidaurre T, Weitzel JN, Zambrano SC, Carvajal-Carmona LG, Ziv E, Neuhausen SL. A Polygenic Risk Score for Breast Cancer in US Latinas and Latin American Women. J Natl Cancer Inst 2021; 112:590-598. [PMID: 31553449 PMCID: PMC7301155 DOI: 10.1093/jnci/djz174] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 07/23/2019] [Accepted: 09/04/2019] [Indexed: 01/19/2023] Open
Abstract
Background More than 180 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified; these SNPs can be combined into polygenic risk scores (PRS) to predict breast cancer risk. Because most SNPs were identified in predominantly European populations, little is known about the performance of PRS in non-Europeans. We tested the performance of a 180-SNP PRS in Latinas, a large ethnic group with variable levels of Indigenous American, European, and African ancestry. Methods We conducted a pooled case-control analysis of US Latinas and Latin American women (4658 cases and 7622 controls). We constructed a 180-SNP PRS consisting of SNPs associated with breast cancer risk (P < 5 × 10–8). We evaluated the association between the PRS and breast cancer risk using multivariable logistic regression, and assessed discrimination using an area under the receiver operating characteristic curve. We also assessed PRS performance across quartiles of Indigenous American genetic ancestry. All statistical tests were two-sided. Results Of 180 SNPs tested, 142 showed directionally consistent associations compared with European populations, and 39 were nominally statistically significant (P < .05). The PRS was associated with breast cancer risk, with an odds ratio per SD increment of 1.58 (95% confidence interval [CI = 1.52 to 1.64) and an area under the receiver operating characteristic curve of 0.63 (95% CI = 0.62 to 0.64). The discrimination of the PRS was similar between the top and bottom quartiles of Indigenous American ancestry. Conclusions The 180-SNP PRS predicts breast cancer risk in Latinas, with similar performance as reported for Europeans. The performance of the PRS did not vary substantially according to Indigenous American ancestry.
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Affiliation(s)
- Yiwey Shieh
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Laura Fejerman
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Paul C Lott
- UC Davis Genome Center, University of California, Davis, Davis, CA
| | - Katie Marker
- School of Public Health, University of California, Berkeley; Berkeley, CA
| | | | - Donglei Hu
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Scott Huntsman
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Javier Torres
- Unidad de Investigación en Enfermedades Infecciosas, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Magdalena Echeverry
- Grupo de Citogenética, Filogenia y Evolución de Poblaciones, Facultades de Ciencias y Facultad de Ciencias de la Salud, Universidad del Tolima, Ibagué, Colombia
| | - Mabel E Bohórquez
- Grupo de Citogenética, Filogenia y Evolución de Poblaciones, Facultades de Ciencias y Facultad de Ciencias de la Salud, Universidad del Tolima, Ibagué, Colombia
| | | | | | - Ana P Estrada-Flórez
- UC Davis Genome Center, University of California, Davis, Davis, CA.,Grupo de Citogenética, Filogenia y Evolución de Poblaciones, Facultades de Ciencias y Facultad de Ciencias de la Salud, Universidad del Tolima, Ibagué, Colombia
| | | | - Christopher A Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Esther M John
- Department of Medicine, Stanford University School of Medicine, Stanford, CA.,Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA
| | - Lawrence H Kushi
- UC Davis Genome Center, University of California, Davis, Davis, CA.,Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | | | | | - Jeffrey N Weitzel
- Division of Clinical Genetics, City of Hope National Medical Center, Duarte, CA
| | | | - Luis G Carvajal-Carmona
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Sacramento, CA.,Population Science and Health Disparities Program, University of California Davis Comprehensive Cancer Center, Sacramento, CA
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA
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23
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Zavala VA, Bracci PM, Carethers JM, Carvajal-Carmona L, Coggins NB, Cruz-Correa MR, Davis M, de Smith AJ, Dutil J, Figueiredo JC, Fox R, Graves KD, Gomez SL, Llera A, Neuhausen SL, Newman L, Nguyen T, Palmer JR, Palmer NR, Pérez-Stable EJ, Piawah S, Rodriquez EJ, Sanabria-Salas MC, Schmit SL, Serrano-Gomez SJ, Stern MC, Weitzel J, Yang JJ, Zabaleta J, Ziv E, Fejerman L. Cancer health disparities in racial/ethnic minorities in the United States. Br J Cancer 2021; 124:315-332. [PMID: 32901135 PMCID: PMC7852513 DOI: 10.1038/s41416-020-01038-6] [Citation(s) in RCA: 470] [Impact Index Per Article: 156.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 07/16/2020] [Accepted: 08/03/2020] [Indexed: 02/06/2023] Open
Abstract
There are well-established disparities in cancer incidence and outcomes by race/ethnicity that result from the interplay between structural, socioeconomic, socio-environmental, behavioural and biological factors. However, large research studies designed to investigate factors contributing to cancer aetiology and progression have mainly focused on populations of European origin. The limitations in clinicopathological and genetic data, as well as the reduced availability of biospecimens from diverse populations, contribute to the knowledge gap and have the potential to widen cancer health disparities. In this review, we summarise reported disparities and associated factors in the United States of America (USA) for the most common cancers (breast, prostate, lung and colon), and for a subset of other cancers that highlight the complexity of disparities (gastric, liver, pancreas and leukaemia). We focus on populations commonly identified and referred to as racial/ethnic minorities in the USA-African Americans/Blacks, American Indians and Alaska Natives, Asians, Native Hawaiians/other Pacific Islanders and Hispanics/Latinos. We conclude that even though substantial progress has been made in understanding the factors underlying cancer health disparities, marked inequities persist. Additional efforts are needed to include participants from diverse populations in the research of cancer aetiology, biology and treatment. Furthermore, to eliminate cancer health disparities, it will be necessary to facilitate access to, and utilisation of, health services to all individuals, and to address structural inequities, including racism, that disproportionally affect racial/ethnic minorities in the USA.
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Affiliation(s)
- Valentina A Zavala
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Paige M Bracci
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - John M Carethers
- Departments of Internal Medicine and Human Genetics, and Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Luis Carvajal-Carmona
- University of California Davis Comprehensive Cancer Center and Department of Biochemistry and Molecular Medicine, School of Medicine, University of California Davis, Sacramento, CA, USA
- Genome Center, University of California Davis, Davis, CA, USA
| | | | - Marcia R Cruz-Correa
- Department of Cancer Biology, University of Puerto Rico Comprehensive Cancer Center, San Juan, Puerto Rico
| | - Melissa Davis
- Division of Breast Surgery, Department of Surgery, NewYork-Presbyterian/Weill Cornell Medical Center, New York, NY, USA
| | - Adam J de Smith
- Center for Genetic Epidemiology, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Julie Dutil
- Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, Puerto Rico
| | - Jane C Figueiredo
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Rena Fox
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Kristi D Graves
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Scarlett Lin Gomez
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Andrea Llera
- Laboratorio de Terapia Molecular y Celular, IIBBA, Fundación Instituto Leloir, CONICET, Buenos Aires, Argentina
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Lisa Newman
- Division of Breast Surgery, Department of Surgery, NewYork-Presbyterian/Weill Cornell Medical Center, New York, NY, USA
- Interdisciplinary Breast Program, New York-Presbyterian/Weill Cornell Medical Center, New York, NY, USA
| | - Tung Nguyen
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA
| | - Nynikka R Palmer
- Department of Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California, San Francisco, San Francisco, CA, USA
| | - Eliseo J Pérez-Stable
- Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Office of the Director, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Sorbarikor Piawah
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Division of Hematology/Oncology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Erik J Rodriquez
- Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Stephanie L Schmit
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Silvia J Serrano-Gomez
- Grupo de investigación en biología del cáncer, Instituto Nacional de Cancerología, Bogotá, Colombia
| | - Mariana C Stern
- Departments of Preventive Medicine and Urology, Keck School of Medicine of USC, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Jeffrey Weitzel
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
- Department of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Jun J Yang
- Department of Pharmaceutical Sciences, Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jovanny Zabaleta
- Department of Pediatrics and Stanley S. Scott Cancer Center LSUHSC, New Orleans, LA, USA
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Laura Fejerman
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
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Hu Y, Xie C, Yang H, Ho JWK, Wen J, Han L, Chiu KWH, Fu J, Vardhanabhuti V. Assessment of Intratumoral and Peritumoral Computed Tomography Radiomics for Predicting Pathological Complete Response to Neoadjuvant Chemoradiation in Patients With Esophageal Squamous Cell Carcinoma. JAMA Netw Open 2020; 3:e2015927. [PMID: 32910196 PMCID: PMC7489831 DOI: 10.1001/jamanetworkopen.2020.15927] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
IMPORTANCE For patients with locally advanced esophageal squamous cell carcinoma, neoadjuvant chemoradiation has been shown to improve long-term outcomes, but the treatment response varies among patients. Accurate pretreatment prediction of response remains an urgent need. OBJECTIVE To determine whether peritumoral radiomics features derived from baseline computed tomography images could provide valuable information about neoadjuvant chemoradiation response and enhance the ability of intratumoral radiomics to estimate pathological complete response. DESIGN, SETTING, AND PARTICIPANTS A total of 231 patients with esophageal squamous cell carcinoma, who underwent baseline contrast-enhanced computed tomography and received neoadjuvant chemoradiation followed by surgery at 2 institutions in China, were consecutively included. This diagnostic study used single-institution data between April 2007 and December 2018 to extract radiomics features from intratumoral and peritumoral regions and established intratumoral, peritumoral, and combined radiomics models using different classifiers. External validation was conducted using independent data collected from another hospital during the same period. Radiogenomics analysis using gene expression profile was done in a subgroup of the training set for pathophysiological explanation. Data were analyzed from June to December 2019. EXPOSURES Computed tomography-based radiomics. MAIN OUTCOMES AND MEASURES The discriminative performances of radiomics models were measured by area under the receiver operating characteristic curve. RESULTS Among the 231 patients included (192 men [83.1%]; mean [SD] age, 59.8 [8.7] years), the optimal intratumoral and peritumoral radiomics models yielded similar areas under the receiver operating characteristic curve of 0.730 (95% CI, 0.609-0.850) and 0.734 (0.613-0.854), respectively. The combined model was composed of 7 intratumoral and 6 peritumoral features and achieved better discriminative performance, with an area under the receiver operating characteristic curve of 0.852 (95% CI, 0.753-0.951), accuracy of 84.3%, sensitivity of 90.3%, and specificity of 79.5% in the test set. Gene sets associated with the combined model mainly involved lymphocyte-mediated immunity. The association of peritumoral area with response identification might be partially attributed to type I interferon-related biological process. CONCLUSIONS AND RELEVANCE A combination of peritumoral radiomics features appears to improve the predictive performance of intratumoral radiomics to estimate pathological complete response after neoadjuvant chemoradiation in patients with esophageal squamous cell carcinoma. This study underlines the significant application of peritumoral radiomics to assess treatment response in clinical practice.
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Affiliation(s)
- Yihuai Hu
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
| | - Chenyi Xie
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Hong Yang
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
| | - Joshua W. K. Ho
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Jing Wen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
| | - Lujun Han
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Keith W. H. Chiu
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Jianhua Fu
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
- Guangdong Esophageal Cancer Institute, Guangzhou, China
| | - Varut Vardhanabhuti
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
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25
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Hill HE, Schiemann WP, Varadan V. Understanding breast cancer disparities-a multi-scale challenge. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:906. [PMID: 32793750 DOI: 10.21037/atm.2020.04.37] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Despite convergence of overall breast cancer incidence rates between European American (EA) and African American (AA) women, disparities in mortality persist. The factors contributing to differences in mortality rates across population groups remain controversial and range from population genetics to sociodemographic influences. This review explores the complex multi-factorial nature of tumor-intrinsic and -extrinsic factors that impact the biology and clinical outcomes of breast cancer patients. In addition to summarizing the current state of breast cancer disparities research, we also motivate the development of integrative multi-scale approaches involving interdisciplinary teams to tackle this complex clinical challenge.
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Affiliation(s)
- Hannah E Hill
- Department of Pharmacology, Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - William P Schiemann
- Department of Pharmacology, Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA.,Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Vinay Varadan
- Department of Pharmacology, Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA.,Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA
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26
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Yanes T, McInerney-Leo AM, Law MH, Cummings S. The emerging field of polygenic risk scores and perspective for use in clinical care. Hum Mol Genet 2020; 29:R165-R176. [DOI: 10.1093/hmg/ddaa136] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 06/30/2020] [Accepted: 07/01/2020] [Indexed: 02/06/2023] Open
Abstract
Abstract
Genetic testing is used widely for diagnostic, carrier and predictive testing in monogenic diseases. Until recently, there were no genetic testing options available for multifactorial complex diseases like heart disease, diabetes and cancer. Genome-wide association studies (GWAS) have been invaluable in identifying single-nucleotide polymorphisms (SNPs) associated with increased or decreased risk for hundreds of complex disorders. For a given disease, SNPs can be combined to generate a cumulative estimation of risk known as a polygenic risk score (PRS). After years of research, PRSs are increasingly used in clinical settings. In this article, we will review the literature on how both genome-wide and restricted PRSs are developed and the relative merit of each. The validation and evaluation of PRSs will also be discussed, including the recognition that PRS validity is intrinsically linked to the methodological and analytical approach of the foundation GWAS together with the ethnic characteristics of that cohort. Specifically, population differences may affect imputation accuracy, risk magnitude and direction. Even as PRSs are being introduced into clinical practice, there is a push to combine them with clinical and demographic risk factors to develop a holistic disease risk. The existing evidence regarding the clinical utility of PRSs is considered across four different domains: informing population screening programs, guiding therapeutic interventions, refining risk for families at high risk, and facilitating diagnosis and predicting prognostic outcomes. The evidence for clinical utility in relation to five well-studied disorders is summarized. The potential ethical, legal and social implications are also highlighted.
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Affiliation(s)
- Tatiane Yanes
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Aideen M McInerney-Leo
- Dermatology Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Matthew H Law
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, Herston QLD 4006, Australia
- Faculty of Health, School of Biomedical Sciences, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove QLD 4059, Australia
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27
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Harlemon M, Ajayi O, Kachambwa P, Kim MS, Simonti CN, Quiver MH, Petersen DC, Mittal A, Fernandez PW, Hsing AW, Baichoo S, Agalliu I, Jalloh M, Gueye SM, Snyper NYF, Adusei B, Mensah JE, Abrahams AOD, Adebiyi AO, Orunmuyi AT, Aisuodionoe-Shadrach OI, Nwegbu MM, Joffe M, Chen WC, Irusen H, Neugut AI, Quintana Y, Seutloali M, Fadipe MB, Warren C, Woehrmann MH, Zhang P, Ongaco CM, Mawhinney M, McBride J, Andrews CV, Adams M, Pugh E, Rebbeck TR, Petersen LN, Lachance J. A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa. Cancer Res 2020; 80:2956-2966. [PMID: 32393663 PMCID: PMC7335354 DOI: 10.1158/0008-5472.can-19-2165] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 10/03/2019] [Accepted: 05/06/2020] [Indexed: 12/25/2022]
Abstract
Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. Samples from Ghana and Nigeria clustered together, whereas samples from Senegal and South Africa yielded distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores for prostate cancer were higher in Nigeria than in Senegal. In summary, individual and population-level differences in prostate cancer risk were revealed using a novel genotyping array. SIGNIFICANCE: This study presents an Africa-specific genotyping array, which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers.
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Affiliation(s)
- Maxine Harlemon
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
- Clark Atlanta University, Atlanta, Georgia
| | - Olabode Ajayi
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | | | - Michelle S Kim
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | - Corinne N Simonti
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | - Melanie H Quiver
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | | | | | - Pedro W Fernandez
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Ann W Hsing
- Stanford Cancer Institute, Stanford University, Stanford, California
| | | | - Ilir Agalliu
- Albert Einstein College of Medicine, Bronx, New York
| | - Mohamed Jalloh
- Hôpital Général de Grand Yoff, Institut de Formation et de Recherche en Urologie et Santé Familiale, Dakar, Senegal
| | - Serigne M Gueye
- Hôpital Général de Grand Yoff, Institut de Formation et de Recherche en Urologie et Santé Familiale, Dakar, Senegal
| | | | | | - James E Mensah
- Korle-Bu Teaching Hospital and University of Ghana, Accra, Ghana
| | | | | | | | | | - Maxwell M Nwegbu
- College of Health Sciences, University of Abuja and University of Abuja Teaching Hospital, Abuja, Nigeria
| | - Maureen Joffe
- Non-Communicable Diseases Research Division, Wits Health Consortium (PTY) Ltd, Johannesburg, South Africa
- MRC Developmental Pathways to Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
| | - Wenlong C Chen
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- National Cancer Registry, National Health Laboratory Service, Johannesburg, South Africa
| | - Hayley Irusen
- Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Alfred I Neugut
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, New York
| | - Yuri Quintana
- Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
| | | | - Mayowa B Fadipe
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | | | | | - Peng Zhang
- Center for Inherited Disease Research, Johns Hopkins University, Baltimore, Maryland
| | - Chrissie M Ongaco
- Center for Inherited Disease Research, Johns Hopkins University, Baltimore, Maryland
| | - Michelle Mawhinney
- Center for Inherited Disease Research, Johns Hopkins University, Baltimore, Maryland
| | - Jo McBride
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | | | - Marcia Adams
- Center for Inherited Disease Research, Johns Hopkins University, Baltimore, Maryland
| | - Elizabeth Pugh
- Center for Inherited Disease Research, Johns Hopkins University, Baltimore, Maryland
| | - Timothy R Rebbeck
- Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | | | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia.
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28
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Palmer JR. Polygenic Risk Scores for Breast Cancer Risk Prediction: Lessons Learned and Future Opportunities. J Natl Cancer Inst 2020; 112:555-556. [PMID: 31553456 PMCID: PMC7301152 DOI: 10.1093/jnci/djz176] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 09/04/2019] [Indexed: 02/07/2023] Open
Affiliation(s)
- Julie R Palmer
- Correspondence to: Julie R. Palmer, ScD, MPH, Slone Epidemiology Center at Boston University, 72 E Concord St, L-7, Boston, MA 02118 (e-mail: )
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29
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Yanes T, Young MA, Meiser B, James PA. Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field. Breast Cancer Res 2020; 22:21. [PMID: 32066492 PMCID: PMC7026946 DOI: 10.1186/s13058-020-01260-3] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 02/07/2020] [Indexed: 01/04/2023] Open
Abstract
Polygenic factors are estimated to account for an additional 18% of the familial relative risk of breast cancer, with those at the highest level of polygenic risk distribution having a least a twofold increased risk of the disease. Polygenic testing promises to revolutionize health services by providing personalized risk assessments to women at high-risk of breast cancer and within population breast screening programs. However, implementation of polygenic testing needs to be considered in light of its current limitations, such as limited risk prediction for women of non-European ancestry. This article aims to provide a comprehensive review of the evidence for polygenic breast cancer risk, including the discovery of variants associated with breast cancer at the genome-wide level of significance and the use of polygenic risk scores to estimate breast cancer risk. We also review the different applications of this technology including testing of women from high-risk breast cancer families with uninformative genetic testing results, as a moderator of monogenic risk, and for population screening programs. Finally, a potential framework for introducing testing for polygenic risk in familial cancer clinics and the potential challenges with implementing this technology in clinical practice are discussed.
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Affiliation(s)
- Tatiane Yanes
- Psychosocial Research Group, Prince of Wales Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia. .,The University of Queensland Diamantina Institute, Dermatology Research Centre, University of Queensland, Brisbane, QLD, 4102, Australia.
| | - Mary-Anne Young
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia
| | - Bettina Meiser
- Psychosocial Research Group, Prince of Wales Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia
| | - Paul A James
- Parkville Integrated Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, 3000, Australia
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30
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Jenkins BD, Martini RN, Hire R, Brown A, Bennett B, Brown I, Howerth EW, Egan M, Hodgson J, Yates C, Kittles R, Chitale D, Ali H, Nathanson D, Nikolinakos P, Newman L, Monteil M, Davis MB. Atypical Chemokine Receptor 1 ( DARC/ACKR1) in Breast Tumors Is Associated with Survival, Circulating Chemokines, Tumor-Infiltrating Immune Cells, and African Ancestry. Cancer Epidemiol Biomarkers Prev 2019; 28:690-700. [PMID: 30944146 PMCID: PMC6450416 DOI: 10.1158/1055-9965.epi-18-0955] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 11/11/2018] [Accepted: 01/04/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Tumor-specific immune response is an important aspect of disease prognosis and ultimately impacts treatment decisions for innovative immunotherapies. The atypical chemokine receptor 1 (ACKR1 or DARC) gene plays a pivotal role in immune regulation and harbors several single-nucleotide variants (SNV) that are specific to sub-Saharan African ancestry. METHODS Using computational The Cancer Genome Atlas (TCGA) analysis, case-control clinical cohort Luminex assays, and CIBERSORT deconvolution, we identified distinct immune cell profile-associated DARC/ACKR1 tumor expression and race with increased macrophage subtypes and regulatory T cells in DARC/ACKR1-high tumors. RESULTS In this study, we report the clinical relevance of DARC/ACKR1 tumor expression in breast cancer, in the context of a tumor immune response that may be associated with sub-Saharan African ancestry. Briefly, we found that for infiltrating carcinomas, African Americans have a higher proportion of DARC/ACKR1-negative tumors compared with white Americans, and DARC/ACKR1 tumor expression is correlated with proinflammatory chemokines, CCL2/MCP-1 (P <0.0001) and anticorrelated with CXCL8/IL8 (P <0.0001). Sub-Saharan African-specific DARC/ACKR1 alleles likely drive these correlations. Relapse-free survival (RFS) and overall survival (OS) were significantly longer in individuals with DARC/ACKR1-high tumors (P <1.0 × 10-16 and P <2.2 × 10-6, respectively) across all molecular tumor subtypes. CONCLUSIONS DARC/AKCR1 regulates immune responses in tumors, and its expression is associated with sub-Saharan African-specific alleles. DARC/ACKR1-positive tumors will have a distinct immune response compared with DARC/AKCR1-negative tumors. IMPACT This study has high relevance in cancer management, as we introduce a functional regulator of inflammatory chemokines that can determine an infiltrating tumor immune cell landscape that is distinct among patients of African ancestry.
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Affiliation(s)
- Brittany D Jenkins
- Department of Genetics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia
| | - Rachel N Martini
- Department of Genetics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia
| | - Rupali Hire
- Department of Genetics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia
| | - Andrea Brown
- Department of Genetics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia
| | - Briana Bennett
- Department of Genetics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia
| | - I'nasia Brown
- Department of Genetics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia
| | - Elizabeth W Howerth
- Department of Pathology, College of Veterinary Medicine, University of Georgia, Athens, Georgia
| | - Mary Egan
- University Cancer and Blood Center, Athens, Georgia
| | | | - Clayton Yates
- Department of Biology and Center for Cancer Research, Tuskegee University, Tuskegee, Alabama
| | - Rick Kittles
- Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte, California
| | - Dhananjay Chitale
- Department of Pathology, Henry Ford Health System, Detroit, Michigan
| | - Haythem Ali
- Department of Hematology and Oncology, Henry Ford Health System, Detroit, Michigan
| | - David Nathanson
- Department of Surgery, Henry Ford Health System, Detroit, Michigan
| | | | - Lisa Newman
- Department of Surgery, Henry Ford Health System, Detroit, Michigan
| | - Michele Monteil
- Department of Molecular Biology and Biochemistry, Augusta University/University of Georgia Medical Partnership, Athens, Georgia
| | - Melissa B Davis
- Department of Genetics, Franklin College of Arts and Sciences, University of Georgia, Athens, Georgia.
- Department of Molecular Biology and Biochemistry, Augusta University/University of Georgia Medical Partnership, Athens, Georgia
- Department of Public Health Sciences, Henry Ford Health System, Detroit, Michigan
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31
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Dutil J, Chen Z, Monteiro AN, Teer JK, Eschrich SA. An Interactive Resource to Probe Genetic Diversity and Estimated Ancestry in Cancer Cell Lines. Cancer Res 2019; 79:1263-1273. [PMID: 30894373 DOI: 10.1158/0008-5472.can-18-2747] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 11/08/2018] [Accepted: 12/26/2018] [Indexed: 12/21/2022]
Abstract
Recent work points to a lack of diversity in genomics studies from genome-wide association studies to somatic (tumor) genome analyses. Yet, population-specific genetic variation has been shown to contribute to health disparities in cancer risk and outcomes. Immortalized cancer cell lines are widely used in cancer research, from mechanistic studies to drug screening. Larger collections of cancer cell lines better represent the genomic heterogeneity found in primary tumors. Yet, the genetic ancestral origin of cancer cell lines is rarely acknowledged and often unknown. Using genome-wide genotyping data from 1,393 cancer cell lines from the Catalogue of Somatic Mutations in Cancer (COSMIC) and Cancer Cell Line Encyclopedia (CCLE), we estimated the genetic ancestral origin for each cell line. Our data indicate that cancer cell line collections are not representative of the diverse ancestry and admixture characterizing human populations. We discuss the implications of genetic ancestry and diversity of cellular models for cancer research and present an interactive tool, Estimated Cell Line Ancestry (ECLA), where ancestry can be visualized with reference populations of the 1000 Genomes Project. Cancer researchers can use this resource to identify cell line models for their studies by taking ancestral origins into consideration.
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Affiliation(s)
- Julie Dutil
- Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, Puerto Rico.
| | - Zhihua Chen
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Alvaro N Monteiro
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Jamie K Teer
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Steven A Eschrich
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida.
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Zavala VA, Serrano-Gomez SJ, Dutil J, Fejerman L. Genetic Epidemiology of Breast Cancer in Latin America. Genes (Basel) 2019; 10:E153. [PMID: 30781715 PMCID: PMC6410045 DOI: 10.3390/genes10020153] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 02/13/2019] [Accepted: 02/14/2019] [Indexed: 12/20/2022] Open
Abstract
The last 10 years witnessed an acceleration of our understanding of what genetic factors underpin the risk of breast cancer. Rare high- and moderate-penetrance variants such as those in the BRCA genes account for a small proportion of the familial risk of breast cancer. Low-penetrance alleles are expected to underlie the remaining heritability. By now, there are about 180 genetic polymorphisms that are associated with risk, most of them of modest effect. In combination, they can be used to identify women at the lowest or highest ends of the risk spectrum, which might lead to more efficient cancer prevention strategies. Most of these variants were discovered in populations of European descent. As a result, we might be failing to discover additional polymorphisms that could explain risk in other groups. This review highlights breast cancer genetic epidemiology studies conducted in Latin America, and summarizes the information that they provide, with special attention to similarities and differences with studies in other populations. It includes studies of common variants, as well as moderate- and high-penetrance variants. In addition, it addresses the gaps that need to be bridged in order to better understand breast cancer genetic risk in Latin America.
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Affiliation(s)
- Valentina A Zavala
- Department of Medicine, Division of General Internal Medicine, University of California San Francisco, San Francisco, CA 94143-1793, USA.
| | - Silvia J Serrano-Gomez
- Grupo de investigación en biología del cáncer, Instituto Nacional de Cancerología, Bogotá 11001000, Colombia.
| | - Julie Dutil
- Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, PR 00732, USA.
| | - Laura Fejerman
- Department of Medicine, Division of General Internal Medicine, University of California San Francisco, San Francisco, CA 94143-1793, USA.
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Wang Z, Liu Q, Wilson CL, Easton J, Mulder H, Chang TC, Rusch MC, Edmonson MN, Rice SV, Ehrhardt MJ, Howell RM, Kesserwan CA, Wu G, Nichols KE, Downing JR, Hudson MM, Zhang J, Yasui Y, Robison LL. Polygenic Determinants for Subsequent Breast Cancer Risk in Survivors of Childhood Cancer: The St Jude Lifetime Cohort Study (SJLIFE). Clin Cancer Res 2018; 24:6230-6235. [PMID: 30366939 PMCID: PMC6295266 DOI: 10.1158/1078-0432.ccr-18-1775] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 07/28/2018] [Accepted: 09/05/2018] [Indexed: 01/19/2023]
Abstract
PURPOSE The risk of subsequent breast cancer among female childhood cancer survivors is markedly elevated. We aimed to determine genetic contributions to this risk, focusing on polygenic determinants implicated in breast cancer susceptibility in the general population. EXPERIMENTAL DESIGN Whole-genome sequencing (30×) was performed on survivors in the St Jude Lifetime Cohort, and germline mutations in breast cancer predisposition genes were classified for pathogenicity. A polygenic risk score (PRS) was constructed for each survivor using 170 established common risk variants. Relative rate (RR) and 95% confidence interval (95% CI) of subsequent breast cancer incidence were estimated using multivariable piecewise exponential regression. RESULTS The analysis included 1,133 female survivors of European ancestry (median age at last follow-up = 35.4 years; range, 8.4-67.4), of whom 47 were diagnosed with one or more subsequent breast cancers (median age at subsequent breast cancer = 40.3 years; range, 24.5-53.0). Adjusting for attained age, age at primary diagnosis, chest irradiation, doses of alkylating agents and anthracyclines, and genotype eigenvectors, RRs for survivors with PRS in the highest versus lowest quintiles were 2.7 (95% CI, 1.0-7.3), 3.0 (95% CI, 1.1-8.1), and 2.4 (95% CI, 0.1-81.1) for all survivors and survivors with and without chest irradiation, respectively. Similar associations were observed after excluding carriers of pathogenic/likely pathogenic mutations in breast cancer predisposition genes. Notably, the PRS was associated with the subsequent breast cancer rate under the age of 45 years (RR = 3.2; 95% CI, 1.2-8.3). CONCLUSIONS Genetic profiles comprised of small-effect common variants and large-effect predisposing mutations can inform personalized breast cancer risk and surveillance/intervention in female childhood cancer survivors.
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Affiliation(s)
- Zhaoming Wang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee.
| | - Qi Liu
- School of Public Health, University of Alberta, Edmonton, Alberta, Canada
| | - Carmen L Wilson
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - John Easton
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Heather Mulder
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Ti-Cheng Chang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Michael C Rusch
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Michael N Edmonson
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Stephen V Rice
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Matthew J Ehrhardt
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Rebecca M Howell
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Chimene A Kesserwan
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Gang Wu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Kim E Nichols
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - James R Downing
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Melissa M Hudson
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Jinghui Zhang
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Yutaka Yasui
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Leslie L Robison
- Department of Epidemiology and Cancer Control, St. Jude Children's Research Hospital, Memphis, Tennessee
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Spaeth E, Starlard-Davenport A, Allman R. Bridging the Data Gap in Breast Cancer Risk Assessment to Enable Widespread Clinical Implementation across the Multiethnic Landscape of the US. ACTA ACUST UNITED AC 2018; 2:1-6. [PMID: 30662981 PMCID: PMC6334765 DOI: 10.29245/2578-2967/2018/4.1137] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Breast cancer remains the second leading cause of cancer death among women and is the most commonly diagnosed cancer in women. Breast cancer risk assessment has been clinically available for nearly 30 years yet is under-utilized in practice for multiple reasons. Incorporation of polygenic risk as well as breast density measurements, promise to increase the accuracy of risk assessment. With that comes the hope that both prevention and screening become more personalized and thus more effective. Incidence rates have been static over the past 15 years and have even increased slightly in African American and Asian/Pacific Islander populations despite the robust data on breast cancer risk reduction measures that exist. Current challenges in reducing breast cancer incidence begin with robust data curation that allows for appropriate risk stratification across our multiethnic population and conclude with the implementation of prevention strategies within our fractured healthcare system.
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Affiliation(s)
| | - Athena Starlard-Davenport
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
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