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A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Accepted version
Peer-reviewed

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Authors

Escala-Garcia, Maria 
Abraham, Jean 
Anton-Culver, Hoda 

Abstract

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.

Description

Keywords

Apoptosis, Breast Neoplasms, Circadian Clocks, Computational Biology, Female, GTP-Binding Protein alpha Subunits, GTP-Binding Protein alpha Subunits, Gq-G11, Gene Regulatory Networks, Genetic Variation, Genome-Wide Association Study, Genotype, Germ Cells, Humans, Prognosis, Receptors, Estrogen, Signal Transduction

Journal Title

Nat Commun

Conference Name

Journal ISSN

2041-1723
2041-1723

Volume Title

11

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved
Sponsorship
National Cancer Institute (U19CA148537)
National Cancer Institute (R01CA128978)
National Cancer Institute (U19CA148065)
European Commission Horizon 2020 (H2020) Societal Challenges (634935)
European Commission Horizon 2020 (H2020) Societal Challenges (633784)
European Commission (16563)
European Commission (223175)
Cancer Research UK (A10710)
Cancer Research UK (A16563)
Cancer Research UK (A12014)
Cancer Research UK (A10118)
National Cancer Institute (P30CA023100)