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

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

Human Genetics and Genomics Advances

10.1016/j.xhgg.2021.100042

http://dx.doi.org/10.1016/j.xhgg.2021.100042

Siddhartha P. Kar, Daniel P.C. Considine, Jonathan P. Tyrer, Jasmine T. Plummer, Stephanie Chen, Felipe S. Dezem, Alvaro N. Barbeira, Padma S. Rajagopal, Will T. Rosenow, Fernando Moreno, Clara Bodelon, Jenny Chang-Claude, Georgia Chenevix-Trench, Anna deFazio, Thilo Dörk, Arif B. Ekici, Ailith Ewing, George Fountzilas, Ellen L. Goode, Mikael Hartman, Florian Heitz, Peter Hillemanns, Estrid Høgdall, Claus K. Høgdall, Tomasz Huzarski, Allan Jensen, Beth Y. Karlan, Elza Khusnutdinova, Lambertus A. Kiemeney, Susanne K. Kjaer, Rüdiger Klapdor, Martin Köbel, Jingmei Li, Clemens Liebrich, Taymaa May, Håkan Olsson, Jennifer B. Permuth, Paolo Peterlongo, Paolo Radice, Susan J. Ramus, Marjorie J. Riggan, Harvey A. Risch, Emmanouil Saloustros, Jacques Simard, Lukasz M. Szafron, Linda Titus, Cheryl L. Thompson, Robert A. Vierkant, Stacey J. Winham, Wei Zheng, Jennifer A. Doherty, Andrew Berchuck, Kate Lawrenson, Hae Kyung Im, Ani W. Manichaikul, Paul D.P. Pharoah, Simon A. Gayther, Joellen M. Schildkraut

General Medicine

16 June 2021

Kar, S. P., Considine, D. P. C., Tyrer, J. P., Plummer, J. T., Chen, S., Dezem, F. S., Barbeira, A. N., Rajagopal, P. S., Rosenow, W. T., Moreno, F., Bodelon, C., Chang-Claude, J., Chenevix-Trench, G., deFazio, A., Dörk, T., Ekici, A. B., Ewing, A., Fountzilas, G., Goode, E. L., … 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), 100042. https://doi.org/10.1016/j.xhgg.2021.100042

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.

Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

There was no specific funding for the research done

https://oar.a-star.edu.sg/communities-collections/articles/18170

2666-2477

Genome Institute of Singapore

https://doi.org/10.1016/j.xhgg.2021.100042