Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer

Kar SP, Considine DP, Tyrer JP, Plummer JT, Chen S, Dezem FS, Barbeira AN, Rajagopal PS, Rosenow WT, Moreno F, Bodelon C, Chang-Claude J, Chenevix-Trench G, deFazio A, Dörk T, Ekici AB, Ewing A, Fountzilas G, Goode EL, Hartman M, Heitz F, Hillemanns P, Høgdall E, Høgdall CK, Huzarski T, Jensen A, Karlan BY, Khusnutdinova E, Kiemeney LA, Kjaer SK, Klapdor R, Köbel M, Li J, Liebrich C, May T, Olsson H, Permuth JB, Peterlongo P, Radice P, Ramus SJ, Riggan MJ, Risch HA, Saloustros E, Simard J, Szafron LM, Titus L, Thompson CL, Vierkant RA, Winham SJ, Zheng W, Doherty JA, Berchuck A, Lawrenson K, Im HK, Manichaikul AW, Pharoah PD, Gayther SA, Schildkraut JM (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Book Volume: 2

Article Number: 100042

Journal Issue: 3

DOI: 10.1016/j.xhgg.2021.100042

Abstract

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

Authors with CRIS profile

Involved external institutions

University of Cambridge United Kingdom (GB) Cedars-Sinai Medical Center United States (USA) (US) QIMR Berghofer Medical Research Institute (früher: the Queensland Institute of Medical Research) Australia (AU) Aristotle University of Thessaloniki Greece (GR) University of Copenhagen Denmark (DK) University of California Los Angeles (UCLA) United States (USA) (US) Russian Academy of Sciences / Росси́йская акаде́мия нау́к (RAS) Russian Federation (RU) University of Calgary Canada (CA) Case Western Reserve University United States (USA) (US) University of Virginia (UVA) United States (USA) (US) Hospital Clínico San Carlos Spain (ES) National Cancer Institute (NCI) United States (USA) (US) Deutsches Krebsforschungszentrum (DKFZ) Germany (DE) University of Sydney (USYD) Australia (AU) Medizinische Hochschule Hannover (MHH) / Hannover Medical School Germany (DE) Mayo Clinic United States (USA) (US) NUS Yong Loo Lin School of Medicine Singapore (SG) Kliniken Essen-Mitte Germany (DE) Kræftens Bekæmpelse Denmark (DK) Pomeranian Medical University / Pomorski Uniwersytet Medyczny w Szczecinie (PMU) Poland (PL) University of Edinburgh United Kingdom (GB) University of Bristol United Kingdom (GB) University of Chicago United States (USA) (US) Princess Margaret Cancer Centre / Princess Margaret Hospital Canada (CA) Lund University / Lunds universitet Sweden (SE) H. Lee Moffitt Cancer Center & Research Institute United States (USA) (US) IFOM - FIRC Institute of Molecular Oncology Italy (IT) Fondazione IRCCS: Istituto Nazionale dei Tumori Italy (IT) University of New South Wales (UNSW) Australia (AU) Duke University United States (USA) (US) Yale University United States (USA) (US) General University Hospital of Larissa Greece (GR) Centre hospitalier universitaire de Québec Canada (CA) Maria Skłodowska-Curie Institute of Oncology / Centrum Onkologii–Instytut im. Marii Skłodowskiej-Curie w Warszawie Poland (PL) University of Southern Maine United States (USA) (US) Vanderbilt University Medical Center United States (USA) (US) Huntsman Cancer Institute United States (USA) (US) Emory University United States (USA) (US) Radboud University Nijmegen Medical Centre / Radboudumc of voluit Radboud Universitair Medisch Centrum (UMC) Netherlands (NL)

How to cite

APA:

Kar, S.P., Considine, D.P., Tyrer, J.P., Plummer, J.T., Chen, S., Dezem, F.S.,... Schildkraut, J.M. (2021). Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer. Human Genetics and Genomics Advances, 2(3). https://doi.org/10.1016/j.xhgg.2021.100042

MLA:

Kar, Siddhartha P., et al. "Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer." Human Genetics and Genomics Advances 2.3 (2021).

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