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

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Standard

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

I: Human Genetics and Genomics Advances, Bind 2, Nr. 3, 100042, 2021.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Kar, SP, Considine, DPC, 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, PDP, Gayther, SA & Schildkraut, JM 2021, 'Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer', Human Genetics and Genomics Advances, bind 2, nr. 3, 100042. https://doi.org/10.1016/j.xhgg.2021.100042

APA

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

Vancouver

Kar SP, Considine DPC, Tyrer JP, Plummer JT, Chen S, Dezem FS o.a. Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer. Human Genetics and Genomics Advances. 2021;2(3). 100042. https://doi.org/10.1016/j.xhgg.2021.100042

Author

Kar, Siddhartha P. ; Considine, Daniel P.C. ; Tyrer, Jonathan P. ; Plummer, Jasmine T. ; Chen, Stephanie ; Dezem, Felipe S. ; Barbeira, Alvaro N. ; Rajagopal, Padma S. ; Rosenow, Will T. ; Moreno, Fernando ; Bodelon, Clara ; Chang-Claude, Jenny ; Chenevix-Trench, Georgia ; deFazio, Anna ; Dörk, Thilo ; Ekici, Arif B. ; Ewing, Ailith ; Fountzilas, George ; Goode, Ellen L. ; Hartman, Mikael ; Heitz, Florian ; Hillemanns, Peter ; Høgdall, Estrid ; Høgdall, Claus K. ; Huzarski, Tomasz ; Jensen, Allan ; Karlan, Beth Y. ; Khusnutdinova, Elza ; Kiemeney, Lambertus A. ; Kjaer, Susanne K. ; Klapdor, Rüdiger ; Köbel, Martin ; Li, Jingmei ; Liebrich, Clemens ; May, Taymaa ; Olsson, Håkan ; Permuth, Jennifer B. ; Peterlongo, Paolo ; Radice, Paolo ; Ramus, Susan J. ; Riggan, Marjorie J. ; Risch, Harvey A. ; Saloustros, Emmanouil ; Simard, Jacques ; Szafron, Lukasz M. ; Titus, Linda ; Thompson, Cheryl L. ; Vierkant, Robert A. ; Winham, Stacey J. ; Zheng, Wei ; Doherty, Jennifer A. ; Berchuck, Andrew ; Lawrenson, Kate ; Im, Hae Kyung ; Manichaikul, Ani W. ; Pharoah, Paul D.P. ; Gayther, Simon A. ; Schildkraut, Joellen M. / Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer. I: Human Genetics and Genomics Advances. 2021 ; Bind 2, Nr. 3.

Bibtex

@article{6ffcbd97a85c41d699c655ec82eec385,
title = "Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer",
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.",
keywords = "breast cancer, GWAS, ovarian cancer, pleiotropy, transcriptome-wide association study",
author = "Kar, {Siddhartha P.} and Considine, {Daniel P.C.} and Tyrer, {Jonathan P.} and Plummer, {Jasmine T.} and Stephanie Chen and Dezem, {Felipe S.} and Barbeira, {Alvaro N.} and Rajagopal, {Padma S.} and Rosenow, {Will T.} and Fernando Moreno and Clara Bodelon and Jenny Chang-Claude and Georgia Chenevix-Trench and Anna deFazio and Thilo D{\"o}rk and Ekici, {Arif B.} and Ailith Ewing and George Fountzilas and Goode, {Ellen L.} and Mikael Hartman and Florian Heitz and Peter Hillemanns and Estrid H{\o}gdall and H{\o}gdall, {Claus K.} and Tomasz Huzarski and Allan Jensen and Karlan, {Beth Y.} and Elza Khusnutdinova and Kiemeney, {Lambertus A.} and Kjaer, {Susanne K.} and R{\"u}diger Klapdor and Martin K{\"o}bel and Jingmei Li and Clemens Liebrich and Taymaa May and H{\aa}kan Olsson and Permuth, {Jennifer B.} and Paolo Peterlongo and Paolo Radice and Ramus, {Susan J.} and Riggan, {Marjorie J.} and Risch, {Harvey A.} and Emmanouil Saloustros and Jacques Simard and Szafron, {Lukasz M.} and Linda Titus and Thompson, {Cheryl L.} and Vierkant, {Robert A.} and Winham, {Stacey J.} and Wei Zheng and Doherty, {Jennifer A.} and Andrew Berchuck and Kate Lawrenson and Im, {Hae Kyung} and Manichaikul, {Ani W.} and Pharoah, {Paul D.P.} and Gayther, {Simon A.} and Schildkraut, {Joellen M.}",
note = "Funding Information: The analyses presented in this manuscript were funded by grant number R01CA211574 from the United States National Institutes of Health/National Cancer Institute. The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The results published here are in part based upon data generated by TCGA Research Network. The BCAC breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Minist?re de l??conomie, de la Science et de l'Innovation du Qu?bec through G?nome Qu?bec and grant PSR-SIIRI-701, the National Institutes of Health (U19 CA148065 and X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, and C1287/A10710) and the European Union (HEALTH-F2-2009-223175, H2020 633784, and 634935). All studies and funders are listed in Michailidou et al.22 The OCAC ovarian cancer genome-wide association meta-analyses were supported by the US National Institutes of Health (CA1X01HG007491-01 [C.I.A.], U19-CA148112 [T.A.S.], R01-CA149429 [C.M.P.], and R01-CA058598 [M.T.G.]); Canadian Institutes of Health Research (MOP-86727 [L.E.K.]), and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission's Seventh Framework Programme grant (agreement number 223175: HEALTH-F2?2009-223175). All studies and funders are listed in Phelan et al.23, The authors declare no competing interests. Funding Information: The analyses presented in this manuscript were funded by grant number R01CA211574 from the United States National Institutes of Health/National Cancer Institute . The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health , and by NCI , NHGRI , NHLBI , NIDA , NIMH , and NINDS . The results published here are in part based upon data generated by TCGA Research Network. The BCAC breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research , the Minist{\`e}re de l{\textquoteright}{\'E}conomie, de la Science et de l{\textquoteright}Innovation du Qu{\'e}bec through G{\'e}nome Qu{\'e}bec and grant PSR-SIIRI-701 , the National Institutes of Health ( U19 CA148065 and X01HG007492 ), Cancer Research UK ( C1287/A10118 , C1287/A16563 , and C1287/A10710 ) and the European Union ( HEALTH-F2-2009-223175 , H2020 633784 , and 634935 ). All studies and funders are listed in Michailidou et al. 22 The OCAC ovarian cancer genome-wide association meta-analyses were supported by the US National Institutes of Health ( CA1X01HG007491-01 [C.I.A.], U19-CA148112 [T.A.S.], R01-CA149429 [C.M.P.], and R01-CA058598 [M.T.G.]); Canadian Institutes of Health Research ( MOP-86727 [L.E.K.]), and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission{\textquoteright}s Seventh Framework Programme grant (agreement number 223175: HEALTH-F2–2009-223175 ). All studies and funders are listed in Phelan et al. 23 Publisher Copyright: {\textcopyright} 2021 The Author(s)",
year = "2021",
doi = "10.1016/j.xhgg.2021.100042",
language = "English",
volume = "2",
journal = "Human Genetics and Genomics Advances",
issn = "2666-2477",
publisher = "Cell Press",
number = "3",

}

RIS

TY - JOUR

T1 - Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer

AU - Kar, Siddhartha P.

AU - Considine, Daniel P.C.

AU - Tyrer, Jonathan P.

AU - Plummer, Jasmine T.

AU - Chen, Stephanie

AU - Dezem, Felipe S.

AU - Barbeira, Alvaro N.

AU - Rajagopal, Padma S.

AU - Rosenow, Will T.

AU - Moreno, Fernando

AU - Bodelon, Clara

AU - Chang-Claude, Jenny

AU - Chenevix-Trench, Georgia

AU - deFazio, Anna

AU - Dörk, Thilo

AU - Ekici, Arif B.

AU - Ewing, Ailith

AU - Fountzilas, George

AU - Goode, Ellen L.

AU - Hartman, Mikael

AU - Heitz, Florian

AU - Hillemanns, Peter

AU - Høgdall, Estrid

AU - Høgdall, Claus K.

AU - Huzarski, Tomasz

AU - Jensen, Allan

AU - Karlan, Beth Y.

AU - Khusnutdinova, Elza

AU - Kiemeney, Lambertus A.

AU - Kjaer, Susanne K.

AU - Klapdor, Rüdiger

AU - Köbel, Martin

AU - Li, Jingmei

AU - Liebrich, Clemens

AU - May, Taymaa

AU - Olsson, Håkan

AU - Permuth, Jennifer B.

AU - Peterlongo, Paolo

AU - Radice, Paolo

AU - Ramus, Susan J.

AU - Riggan, Marjorie J.

AU - Risch, Harvey A.

AU - Saloustros, Emmanouil

AU - Simard, Jacques

AU - Szafron, Lukasz M.

AU - Titus, Linda

AU - Thompson, Cheryl L.

AU - Vierkant, Robert A.

AU - Winham, Stacey J.

AU - Zheng, Wei

AU - Doherty, Jennifer A.

AU - Berchuck, Andrew

AU - Lawrenson, Kate

AU - Im, Hae Kyung

AU - Manichaikul, Ani W.

AU - Pharoah, Paul D.P.

AU - Gayther, Simon A.

AU - Schildkraut, Joellen M.

N1 - Funding Information: The analyses presented in this manuscript were funded by grant number R01CA211574 from the United States National Institutes of Health/National Cancer Institute. The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The results published here are in part based upon data generated by TCGA Research Network. The BCAC breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Minist?re de l??conomie, de la Science et de l'Innovation du Qu?bec through G?nome Qu?bec and grant PSR-SIIRI-701, the National Institutes of Health (U19 CA148065 and X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, and C1287/A10710) and the European Union (HEALTH-F2-2009-223175, H2020 633784, and 634935). All studies and funders are listed in Michailidou et al.22 The OCAC ovarian cancer genome-wide association meta-analyses were supported by the US National Institutes of Health (CA1X01HG007491-01 [C.I.A.], U19-CA148112 [T.A.S.], R01-CA149429 [C.M.P.], and R01-CA058598 [M.T.G.]); Canadian Institutes of Health Research (MOP-86727 [L.E.K.]), and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission's Seventh Framework Programme grant (agreement number 223175: HEALTH-F2?2009-223175). All studies and funders are listed in Phelan et al.23, The authors declare no competing interests. Funding Information: The analyses presented in this manuscript were funded by grant number R01CA211574 from the United States National Institutes of Health/National Cancer Institute . The GTEx Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health , and by NCI , NHGRI , NHLBI , NIDA , NIMH , and NINDS . The results published here are in part based upon data generated by TCGA Research Network. The BCAC breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research , the Ministère de l’Économie, de la Science et de l’Innovation du Québec through Génome Québec and grant PSR-SIIRI-701 , the National Institutes of Health ( U19 CA148065 and X01HG007492 ), Cancer Research UK ( C1287/A10118 , C1287/A16563 , and C1287/A10710 ) and the European Union ( HEALTH-F2-2009-223175 , H2020 633784 , and 634935 ). All studies and funders are listed in Michailidou et al. 22 The OCAC ovarian cancer genome-wide association meta-analyses were supported by the US National Institutes of Health ( CA1X01HG007491-01 [C.I.A.], U19-CA148112 [T.A.S.], R01-CA149429 [C.M.P.], and R01-CA058598 [M.T.G.]); Canadian Institutes of Health Research ( MOP-86727 [L.E.K.]), and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission’s Seventh Framework Programme grant (agreement number 223175: HEALTH-F2–2009-223175 ). All studies and funders are listed in Phelan et al. 23 Publisher Copyright: © 2021 The Author(s)

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - breast cancer

KW - GWAS

KW - ovarian cancer

KW - pleiotropy

KW - transcriptome-wide association study

U2 - 10.1016/j.xhgg.2021.100042

DO - 10.1016/j.xhgg.2021.100042

M3 - Journal article

C2 - 34317694

AN - SCOPUS:85120470217

VL - 2

JO - Human Genetics and Genomics Advances

JF - Human Genetics and Genomics Advances

SN - 2666-2477

IS - 3

M1 - 100042

ER -

ID: 302153555