Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.

Somatic mutation accumulation is a major cause of abnormal cell growth. However, some mutations in cancer cells may be deleterious to the survival and proliferation of the cancer cells, thus offering a protective effect to the patients. We investigated this hypothesis via a unique analysis of the cl...

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Main Authors: Wensheng Zhang, Andrea Edwards, Erik Flemington, Kun Zhang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4229214?pdf=render
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spelling doaj-1c173375f1e94affa5b10f424c33f4fd2020-11-24T21:33:55ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01911e11256110.1371/journal.pone.0112561Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.Wensheng ZhangAndrea EdwardsErik FlemingtonKun ZhangSomatic mutation accumulation is a major cause of abnormal cell growth. However, some mutations in cancer cells may be deleterious to the survival and proliferation of the cancer cells, thus offering a protective effect to the patients. We investigated this hypothesis via a unique analysis of the clinical and somatic mutation datasets of ovarian carcinomas published by the Cancer Genome Atlas. We defined and screened 562 macro mutation signatures (MMSs) for their associations with the overall survival of 320 ovarian cancer patients. Each MMS measures the number of mutations present on the member genes (except for TP53) covered by a specific Gene Ontology (GO) term in each tumor. We found that somatic mutations favorable to the patient survival are predominant in ovarian carcinomas compared to those indicating poor clinical outcomes. Specially, we identified 19 (3) predictive MMSs that are, usually by a nonlinear dose-dependent effect, associated with good (poor) patient survival. The false discovery rate for the 19 "positive" predictors is at the level of 0.15. The GO terms corresponding to these MMSs include "lysosomal membrane" and "response to hypoxia", each of which is relevant to the progression and therapy of cancer. Using these MMSs as features, we established a classification tree model which can effectively partition the training samples into three prognosis groups regarding the survival time. We validated this model on an independent dataset of the same disease (Log-rank p-value < 2.3 × 10(-4)) and a dataset of breast cancer (Log-rank p-value < 9.3 × 10(-3)). We compared the GO terms corresponding to these MMSs and those enriched with expression-based predictive genes. The analysis showed that the GO term pairs with large similarity are mainly pertinent to the proteins located on the cell organelles responsible for material transport and waste disposal, suggesting the crucial role of these proteins in cancer mortality.http://europepmc.org/articles/PMC4229214?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Wensheng Zhang
Andrea Edwards
Erik Flemington
Kun Zhang
spellingShingle Wensheng Zhang
Andrea Edwards
Erik Flemington
Kun Zhang
Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
PLoS ONE
author_facet Wensheng Zhang
Andrea Edwards
Erik Flemington
Kun Zhang
author_sort Wensheng Zhang
title Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
title_short Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
title_full Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
title_fullStr Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
title_full_unstemmed Somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
title_sort somatic mutations favorable to patient survival are predominant in ovarian carcinomas.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description Somatic mutation accumulation is a major cause of abnormal cell growth. However, some mutations in cancer cells may be deleterious to the survival and proliferation of the cancer cells, thus offering a protective effect to the patients. We investigated this hypothesis via a unique analysis of the clinical and somatic mutation datasets of ovarian carcinomas published by the Cancer Genome Atlas. We defined and screened 562 macro mutation signatures (MMSs) for their associations with the overall survival of 320 ovarian cancer patients. Each MMS measures the number of mutations present on the member genes (except for TP53) covered by a specific Gene Ontology (GO) term in each tumor. We found that somatic mutations favorable to the patient survival are predominant in ovarian carcinomas compared to those indicating poor clinical outcomes. Specially, we identified 19 (3) predictive MMSs that are, usually by a nonlinear dose-dependent effect, associated with good (poor) patient survival. The false discovery rate for the 19 "positive" predictors is at the level of 0.15. The GO terms corresponding to these MMSs include "lysosomal membrane" and "response to hypoxia", each of which is relevant to the progression and therapy of cancer. Using these MMSs as features, we established a classification tree model which can effectively partition the training samples into three prognosis groups regarding the survival time. We validated this model on an independent dataset of the same disease (Log-rank p-value < 2.3 × 10(-4)) and a dataset of breast cancer (Log-rank p-value < 9.3 × 10(-3)). We compared the GO terms corresponding to these MMSs and those enriched with expression-based predictive genes. The analysis showed that the GO term pairs with large similarity are mainly pertinent to the proteins located on the cell organelles responsible for material transport and waste disposal, suggesting the crucial role of these proteins in cancer mortality.
url http://europepmc.org/articles/PMC4229214?pdf=render
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