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

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ICR Authors

Authors

Escala-Garcia, M
Abraham, J
Andrulis, IL
Anton-Culver, H
Arndt, V
Ashworth, A
Auer, PL
Auvinen, P
Beckmann, MW
Beesley, J
Behrens, S
Benitez, J
Bermisheva, M
Blomqvist, C
Blot, W
Bogdanova, NV
Bojesen, SE
Bolla, MK
Børresen-Dale, A-L
Brauch, H
Brenner, H
Brucker, SY
Burwinkel, B
Caldas, C
Canzian, F
Chang-Claude, J
Chanock, SJ
Chin, S-F
Clarke, CL
Couch, FJ
Cox, A
Cross, SS
Czene, K
Daly, MB
Dennis, J
Devilee, P
Dunn, JA
Dunning, AM
Dwek, M
Earl, HM
Eccles, DM
Eliassen, AH
Ellberg, C
Evans, DG
Fasching, PA
Figueroa, J
Flyger, H
Gago-Dominguez, M
Gapstur, SM
García-Closas, M
García-Sáenz, JA
Gaudet, MM
George, A
Giles, GG
Goldgar, DE
González-Neira, A
Grip, M
Guénel, P
Guo, Q
Haiman, CA
Håkansson, N
Hamann, U
Harrington, PA
Hiller, L
Hooning, MJ
Hopper, JL
Howell, A
Huang, C-S
Huang, G
Hunter, DJ
Jakubowska, A
John, EM
Kaaks, R
Kapoor, PM
Keeman, R
Kitahara, CM
Koppert, LB
Kraft, P
Kristensen, VN
Lambrechts, D
Le Marchand, L
Lejbkowicz, F
Lindblom, A
Lubiński, J
Mannermaa, A
Manoochehri, M
Manoukian, S
Margolin, S
Martinez, ME
Maurer, T
Mavroudis, D
Meindl, A
Milne, RL
Mulligan, AM
Neuhausen, SL
Nevanlinna, H
Newman, WG
Olshan, AF
Olson, JE
Olsson, H
Orr, N
Peterlongo, P
Petridis, C
Prentice, RL
Presneau, N
Punie, K
Ramachandran, D
Rennert, G
Romero, A
Sachchithananthan, M
Saloustros, E
Sawyer, EJ
Schmutzler, RK
Schwentner, L
Scott, C
Simard, J
Sohn, C
Southey, MC
Swerdlow, AJ
Tamimi, RM
Tapper, WJ
Teixeira, MR
Terry, MB
Thorne, H
Tollenaar, RAEM
Tomlinson, I
Troester, MA
Truong, T
Turnbull, C
Vachon, CM
van der Kolk, LE
Wang, Q
Winqvist, R
Wolk, A
Yang, XR
Ziogas, A
Pharoah, PDP
Hall, P
Wessels, LFA
Chenevix-Trench, G
Bader, GD
Dörk, T
Easton, DF
Canisius, S
Schmidt, MK

Document Type

Journal Article

Date

2020-01-16

Date Accepted

2019-12-17

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.

Citation

Nature Communications, 2020, 11 (1), pp. 312 -

Source Title

Nature Communications

Publisher

NATURE PORTFOLIO

ISSN

2041-1723

eISSN

2041-1723
2041-1723

Research Team

Complex Trait Genetics
Translational Genetics

Notes