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Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer
BACKGROUND: Tumor mutational burden (TMB) is an important independent biomarker for the response to immunotherapy in multiple cancers. However, the clinical implications of TMB in gastric cancer (GC) have not been fully elucidated. AIM: To explore the landscape of mutation profiles and determine the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805270/ https://www.ncbi.nlm.nih.gov/pubmed/33510848 http://dx.doi.org/10.4251/wjgo.v13.i1.37 |
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author | Zhao, Dong-Yan Sun, Xi-Zhen Yao, Shu-Kun |
author_facet | Zhao, Dong-Yan Sun, Xi-Zhen Yao, Shu-Kun |
author_sort | Zhao, Dong-Yan |
collection | PubMed |
description | BACKGROUND: Tumor mutational burden (TMB) is an important independent biomarker for the response to immunotherapy in multiple cancers. However, the clinical implications of TMB in gastric cancer (GC) have not been fully elucidated. AIM: To explore the landscape of mutation profiles and determine the correlation between TMB and microRNA (miRNA) expression in GC. METHODS: Genomic, transcriptomic, and clinical data from The Cancer Genome Atlas were used to obtain mutational profiles and investigate the statistical correlation between mutational burden and the overall survival of GC patients. The difference in immune infiltration between high- and low-TMB subgroups was evaluated by Wilcoxon rank-sum test. Furthermore, miRNAs differentially expressed between the high- and low-TMB subgroups were identified and the least absolute shrinkage and selection operator method was employed to construct a miRNA-based signature for TMB prediction. The biological functions of the predictive miRNAs were identified with DIANA-miRPath v3.0. RESULTS: C>T single nucleotide mutations exhibited the highest mutation incidence, and the top three mutated genes were TTN, TP53, and MUC16 in GC. High TMB values (top 20%) were markedly correlated with better survival outcome, and multivariable regression analysis indicated that TMB remained prognostic independent of TNM stage, histological grade, age, and gender. Different TMB levels exhibited different immune infiltration patterns. Significant differences between the high- and low-TMB subgroups were observed in the infiltration of CD8+ T cells, M1 macrophages, regulatory T cells, and CD4+ T cells. In addition, we developed a miRNA-based signature using 23 differentially expressed miRNAs to predict TMB values of GC patients. The predictive performance of the signature was confirmed in the testing and the whole set. Receiver operating characteristic curve analysis demonstrated the optimal performance of the signature. Finally, enrichment analysis demonstrated that the set of miRNAs was significantly enriched in many key cancer and immune-related pathways. CONCLUSION: TMB: |
format | Online Article Text |
id | pubmed-7805270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-78052702021-01-27 Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer Zhao, Dong-Yan Sun, Xi-Zhen Yao, Shu-Kun World J Gastrointest Oncol Observational Study BACKGROUND: Tumor mutational burden (TMB) is an important independent biomarker for the response to immunotherapy in multiple cancers. However, the clinical implications of TMB in gastric cancer (GC) have not been fully elucidated. AIM: To explore the landscape of mutation profiles and determine the correlation between TMB and microRNA (miRNA) expression in GC. METHODS: Genomic, transcriptomic, and clinical data from The Cancer Genome Atlas were used to obtain mutational profiles and investigate the statistical correlation between mutational burden and the overall survival of GC patients. The difference in immune infiltration between high- and low-TMB subgroups was evaluated by Wilcoxon rank-sum test. Furthermore, miRNAs differentially expressed between the high- and low-TMB subgroups were identified and the least absolute shrinkage and selection operator method was employed to construct a miRNA-based signature for TMB prediction. The biological functions of the predictive miRNAs were identified with DIANA-miRPath v3.0. RESULTS: C>T single nucleotide mutations exhibited the highest mutation incidence, and the top three mutated genes were TTN, TP53, and MUC16 in GC. High TMB values (top 20%) were markedly correlated with better survival outcome, and multivariable regression analysis indicated that TMB remained prognostic independent of TNM stage, histological grade, age, and gender. Different TMB levels exhibited different immune infiltration patterns. Significant differences between the high- and low-TMB subgroups were observed in the infiltration of CD8+ T cells, M1 macrophages, regulatory T cells, and CD4+ T cells. In addition, we developed a miRNA-based signature using 23 differentially expressed miRNAs to predict TMB values of GC patients. The predictive performance of the signature was confirmed in the testing and the whole set. Receiver operating characteristic curve analysis demonstrated the optimal performance of the signature. Finally, enrichment analysis demonstrated that the set of miRNAs was significantly enriched in many key cancer and immune-related pathways. CONCLUSION: TMB: Baishideng Publishing Group Inc 2021-01-15 2021-01-15 /pmc/articles/PMC7805270/ /pubmed/33510848 http://dx.doi.org/10.4251/wjgo.v13.i1.37 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
spellingShingle | Observational Study Zhao, Dong-Yan Sun, Xi-Zhen Yao, Shu-Kun Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer |
title | Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer |
title_full | Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer |
title_fullStr | Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer |
title_full_unstemmed | Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer |
title_short | Mining The Cancer Genome Atlas database for tumor mutation burden and its clinical implications in gastric cancer |
title_sort | mining the cancer genome atlas database for tumor mutation burden and its clinical implications in gastric cancer |
topic | Observational Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805270/ https://www.ncbi.nlm.nih.gov/pubmed/33510848 http://dx.doi.org/10.4251/wjgo.v13.i1.37 |
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