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A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer
Ovarian cancer (OC) is the most malignant tumor in the female reproductive tract. Although abundant molecular biomarkers have been identified, a robust and accurate gene expression signature is still essential to assist oncologists in evaluating the prognosis of OC patients. In this study, samples f...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593580/ https://www.ncbi.nlm.nih.gov/pubmed/33193589 http://dx.doi.org/10.3389/fgene.2020.01006 |
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author | Pan, Xin Ma, Xiaoxin |
author_facet | Pan, Xin Ma, Xiaoxin |
author_sort | Pan, Xin |
collection | PubMed |
description | Ovarian cancer (OC) is the most malignant tumor in the female reproductive tract. Although abundant molecular biomarkers have been identified, a robust and accurate gene expression signature is still essential to assist oncologists in evaluating the prognosis of OC patients. In this study, samples from 367 patients in The Cancer Genome Atlas (TCGA) database were subjected to mRNA expression profiling. Then, we used a gene set enrichment analysis (GSEA) to screen genes correlated with epithelial–mesenchymal transition (EMT) and assess their prognostic power with a Cox proportional regression model. Six genes (TGFBI, SFRP1, COL16A1, THY1, PPIB, BGN) associated with overall survival (OS) were used to construct a risk assessment model, after which the patients were divided into high-risk and low-risk groups. The six-gene signature was an independent prognostic biomarker of OS for OC patients based on the multivariate Cox regression analysis. In addition, the six-gene model was validated with samples from the Gene Expression Omnibus (GEO) database. In summary, we established a six-gene signature relevant to the prognosis of OC, which might become a therapeutic tool with clinical applications in the future. |
format | Online Article Text |
id | pubmed-7593580 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75935802020-11-13 A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer Pan, Xin Ma, Xiaoxin Front Genet Genetics Ovarian cancer (OC) is the most malignant tumor in the female reproductive tract. Although abundant molecular biomarkers have been identified, a robust and accurate gene expression signature is still essential to assist oncologists in evaluating the prognosis of OC patients. In this study, samples from 367 patients in The Cancer Genome Atlas (TCGA) database were subjected to mRNA expression profiling. Then, we used a gene set enrichment analysis (GSEA) to screen genes correlated with epithelial–mesenchymal transition (EMT) and assess their prognostic power with a Cox proportional regression model. Six genes (TGFBI, SFRP1, COL16A1, THY1, PPIB, BGN) associated with overall survival (OS) were used to construct a risk assessment model, after which the patients were divided into high-risk and low-risk groups. The six-gene signature was an independent prognostic biomarker of OS for OC patients based on the multivariate Cox regression analysis. In addition, the six-gene model was validated with samples from the Gene Expression Omnibus (GEO) database. In summary, we established a six-gene signature relevant to the prognosis of OC, which might become a therapeutic tool with clinical applications in the future. Frontiers Media S.A. 2020-10-15 /pmc/articles/PMC7593580/ /pubmed/33193589 http://dx.doi.org/10.3389/fgene.2020.01006 Text en Copyright © 2020 Pan and Ma. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Pan, Xin Ma, Xiaoxin A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer |
title | A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer |
title_full | A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer |
title_fullStr | A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer |
title_full_unstemmed | A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer |
title_short | A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer |
title_sort | novel six-gene signature for prognosis prediction in ovarian cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593580/ https://www.ncbi.nlm.nih.gov/pubmed/33193589 http://dx.doi.org/10.3389/fgene.2020.01006 |
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