A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.
Date
2020-01-16ICR Author
Author
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
Type
Journal Article
Metadata
Show full item recordAbstract
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.
Collections
Subject
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
Research team
Complex Trait Genetics
Translational Genetics
Language
eng
Date accepted
2019-12-17
License start date
2020-01-16
Citation
Nature Communications, 2020, 11 (1), pp. 312 -
Publisher
NATURE PORTFOLIO