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

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
A network analysis to identify mediators of germline-driven differences in breast cancer prognosis
Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapted 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 studied studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirmed confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identified identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules showed biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.
2041-1723
Eccles, Diana
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
Escala-Garcia, Maria
be71247c-3e00-4f52-a8ab-080a12c9e657
Tapper, William
9d5ddc92-a8dd-4c78-ac67-c5867b62724c
et al.
Eccles, Diana
5b59bc73-11c9-4cf0-a9d5-7a8e523eee23
Escala-Garcia, Maria
be71247c-3e00-4f52-a8ab-080a12c9e657
Tapper, William
9d5ddc92-a8dd-4c78-ac67-c5867b62724c

Escala-Garcia, Maria , et al. (2020) A network analysis to identify mediators of germline-driven differences in breast cancer prognosis. Nature Communications, 11 (1), [312]. (doi:10.1038/s41467-019-14100-6).

Record type: Article

Abstract

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapted 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 studied studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirmed confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identified identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules showed biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.

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Escala-Garcia_Pathway-MainText[09.08.19]_trackChanges - Accepted Manuscript
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Accepted/In Press date: 17 December 2019
e-pub ahead of print date: 16 January 2020

Identifiers

Local EPrints ID: 439145
URI: http://eprints.soton.ac.uk/id/eprint/439145
ISSN: 2041-1723
PURE UUID: deddde2f-ed8e-4d4a-bbc1-164fc8ddcf19
ORCID for Diana Eccles: ORCID iD orcid.org/0000-0002-9935-3169
ORCID for William Tapper: ORCID iD orcid.org/0000-0002-5896-1889

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Date deposited: 06 Apr 2020 16:30
Last modified: 26 Nov 2021 05:54

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Contributors

Author: Diana Eccles ORCID iD
Author: Maria Escala-Garcia
Author: William Tapper ORCID iD
Corporate Author: et al.

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