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Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer

Esophageal cancer (ESCA) is a leading cause of cancer-related mortality, with poor prognosis worldwide. DNA damage repair is one of the hallmarks of cancer. Loss of genomic integrity owing to inactivation of DNA repair genes can increase the risk of cancer progression and lead to poor prognosis. We...

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Autores principales: Wang, Lin, Li, Xueping, Zhao, Lan, Jiang, Longyang, Song, Xinyue, Qi, Aoshuang, Chen, Ting, Ju, Mingyi, Hu, Baohui, Wei, Minjie, He, Miao, Zhao, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262199/
https://www.ncbi.nlm.nih.gov/pubmed/34257547
http://dx.doi.org/10.3389/pore.2021.596899
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author Wang, Lin
Li, Xueping
Zhao, Lan
Jiang, Longyang
Song, Xinyue
Qi, Aoshuang
Chen, Ting
Ju, Mingyi
Hu, Baohui
Wei, Minjie
He, Miao
Zhao, Lin
author_facet Wang, Lin
Li, Xueping
Zhao, Lan
Jiang, Longyang
Song, Xinyue
Qi, Aoshuang
Chen, Ting
Ju, Mingyi
Hu, Baohui
Wei, Minjie
He, Miao
Zhao, Lin
author_sort Wang, Lin
collection PubMed
description Esophageal cancer (ESCA) is a leading cause of cancer-related mortality, with poor prognosis worldwide. DNA damage repair is one of the hallmarks of cancer. Loss of genomic integrity owing to inactivation of DNA repair genes can increase the risk of cancer progression and lead to poor prognosis. We aimed to identify a novel gene signature related to DNA repair to predict the prognosis of ESCA patients. Based on gene expression profiles of ESCA patients from The Cancer Genome Atlas and gene set enrichment analysis, 102 genes related to DNA repair were identified as candidates. After stepwise Cox regression analysis, we established a five-gene prognostic model comprising DGCR8, POM121, TAF9, UPF3B, and BCAP31. Kaplan-Meier survival analysis confirmed a strong correlation between the prognostic model and survival. Moreover, we verified the clinical value of the prognostic signature under the influence of different clinical parameters. We found that small-molecule drugs (trametinib, selumetinib, and refametinib) could help to improve patient survival. In summary, our study provides a novel and promising prognostic signature based on DNA-repair-related genes to predict survival of patients with ESCA. Systematic data mining provides a theoretical basis for further exploring the molecular pathogenesis of ESCA and identifying therapeutic targets.
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spelling pubmed-82621992021-07-12 Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer Wang, Lin Li, Xueping Zhao, Lan Jiang, Longyang Song, Xinyue Qi, Aoshuang Chen, Ting Ju, Mingyi Hu, Baohui Wei, Minjie He, Miao Zhao, Lin Pathol Oncol Res Society Journal Archive Esophageal cancer (ESCA) is a leading cause of cancer-related mortality, with poor prognosis worldwide. DNA damage repair is one of the hallmarks of cancer. Loss of genomic integrity owing to inactivation of DNA repair genes can increase the risk of cancer progression and lead to poor prognosis. We aimed to identify a novel gene signature related to DNA repair to predict the prognosis of ESCA patients. Based on gene expression profiles of ESCA patients from The Cancer Genome Atlas and gene set enrichment analysis, 102 genes related to DNA repair were identified as candidates. After stepwise Cox regression analysis, we established a five-gene prognostic model comprising DGCR8, POM121, TAF9, UPF3B, and BCAP31. Kaplan-Meier survival analysis confirmed a strong correlation between the prognostic model and survival. Moreover, we verified the clinical value of the prognostic signature under the influence of different clinical parameters. We found that small-molecule drugs (trametinib, selumetinib, and refametinib) could help to improve patient survival. In summary, our study provides a novel and promising prognostic signature based on DNA-repair-related genes to predict survival of patients with ESCA. Systematic data mining provides a theoretical basis for further exploring the molecular pathogenesis of ESCA and identifying therapeutic targets. Frontiers Media S.A. 2021-03-30 /pmc/articles/PMC8262199/ /pubmed/34257547 http://dx.doi.org/10.3389/pore.2021.596899 Text en Copyright © 2021 Wang, Li, Zhao, Jiang, Song, Qi, Chen, Ju, Hu, Wei, He and Zhao. https://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 Society Journal Archive
Wang, Lin
Li, Xueping
Zhao, Lan
Jiang, Longyang
Song, Xinyue
Qi, Aoshuang
Chen, Ting
Ju, Mingyi
Hu, Baohui
Wei, Minjie
He, Miao
Zhao, Lin
Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer
title Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer
title_full Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer
title_fullStr Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer
title_full_unstemmed Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer
title_short Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer
title_sort identification of dna-repair-related five-gene signature to predict prognosis in patients with esophageal cancer
topic Society Journal Archive
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262199/
https://www.ncbi.nlm.nih.gov/pubmed/34257547
http://dx.doi.org/10.3389/pore.2021.596899
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