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

Maria Escala Garcia; Jean Abraham; Irene L. Andrulis; Hoda Anton-Culver; Volker Arndt; Alan Ashworth; Paul L. Auer; Päivi Auvinen; Matthias W. Beckmann; Jonathan Beesley; Lodewyk F.A. Wessels; null More Authors

doi:10.1038/s41467-019-14100-6

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

Maria Escala Garcia, Jean Abraham, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Alan Ashworth, Paul L. Auer, Päivi Auvinen, Matthias W. Beckmann, Jonathan Beesley, Lodewyk F.A. Wessels, More Authors

Pattern Recognition and Bioinformatics

Research output: Contribution to journal › Article › Scientific › peer-review

27 Citations (Scopus)

95 Downloads (Pure)

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.

Original language	English
Article number	312
Pages (from-to)	1-14
Number of pages	14
Journal	Nature Communications
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41467-019-14100-6
Publication status	Published - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1038/s41467-019-14100-6

s41467-019-14100-6Final published version, 4.15 MBLicence: CC BY

Cite this

Escala Garcia, M., Abraham, J., Andrulis, I. L., Anton-Culver, H., Arndt, V., Ashworth, A., Auer, P. L., Auvinen, P., Beckmann, M. W., Beesley, J., Wessels, L. F. A., & More Authors (2020). A network analysis to identify mediators of germline-driven differences in breast cancer prognosis. Nature Communications, 11(1), 1-14. Article 312. https://doi.org/10.1038/s41467-019-14100-6

@article{51051b6d2d034741999dff0e1d45c7b5,

title = "A network analysis to identify mediators of germline-driven differences in breast cancer prognosis",

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.",

author = "{Escala Garcia}, Maria and Jean Abraham and Andrulis, {Irene L.} and Hoda Anton-Culver and Volker Arndt and Alan Ashworth and Auer, {Paul L.} and P{\"a}ivi Auvinen and Beckmann, {Matthias W.} and Jonathan Beesley and Wessels, {Lodewyk F.A.} and {More Authors}",

year = "2020",

doi = "10.1038/s41467-019-14100-6",

language = "English",

volume = "11",

pages = "1--14",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature",

number = "1",

}

TY - JOUR

T1 - A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

AU - Escala Garcia, Maria

AU - Abraham, Jean

AU - Andrulis, Irene L.

AU - Anton-Culver, Hoda

AU - Arndt, Volker

AU - Ashworth, Alan

AU - Auer, Paul L.

AU - Auvinen, Päivi

AU - Beckmann, Matthias W.

AU - Beesley, Jonathan

AU - Wessels, Lodewyk F.A.

AU - More Authors, null

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85077940819&partnerID=8YFLogxK

U2 - 10.1038/s41467-019-14100-6

DO - 10.1038/s41467-019-14100-6

M3 - Article

C2 - 31949161

SN - 2041-1723

VL - 11

SP - 1

EP - 14

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 312

ER -

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

Abstract

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this