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Multiomics analysis of tumor mutational burden across cancer types

Whether tumor mutational burden (TMB) is related to improved survival outcomes or the promotion of immunotherapy in various malignant tumors remains controversial, and we lack a comprehensive understanding of TMB across cancers. Based on the data obtained from The Cancer Genome Atlas (TCGA), we cond...

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Autores principales: Li, Lin, Bai, Long, Lin, Huan, Dong, Lin, Zhang, Rumeng, Cheng, Xiao, Liu, Zexian, Ouyang, Yi, Ding, Keshuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531462/
https://www.ncbi.nlm.nih.gov/pubmed/34745455
http://dx.doi.org/10.1016/j.csbj.2021.10.013
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author Li, Lin
Bai, Long
Lin, Huan
Dong, Lin
Zhang, Rumeng
Cheng, Xiao
Liu, Zexian
Ouyang, Yi
Ding, Keshuo
author_facet Li, Lin
Bai, Long
Lin, Huan
Dong, Lin
Zhang, Rumeng
Cheng, Xiao
Liu, Zexian
Ouyang, Yi
Ding, Keshuo
author_sort Li, Lin
collection PubMed
description Whether tumor mutational burden (TMB) is related to improved survival outcomes or the promotion of immunotherapy in various malignant tumors remains controversial, and we lack a comprehensive understanding of TMB across cancers. Based on the data obtained from The Cancer Genome Atlas (TCGA), we conducted a multiomics analysis of TMB across 21 cancer types to identify characteristics related to TMB and determine the mechanism as it relates to prognosis, gene expression, gene mutation and signaling pathways. In our study, TMB was found to have a significant relationship with prognosis for 21 tumors, and the relationship was different in different tumors. TMB may also be related to different outcomes for patients with different tumor subtypes. TMB was confirmed to be correlated with clinical information, such as age and sex. Mutations in GATA3 and MAP3K1 in beast invasive carcinoma (BRCA), TCF7L2 in colon adenocarcinoma (COAD), NFE2L2 in esophageal carcinoma (ESCA), CIC and IDH1 in brain lower grade glioma (LGG), CDH1 in stomach adenocarcinoma (STAD), and TP53 in uterine corpus endometrial carcinoma (UCEC) were demonstrated to be correlated with lower TMB. Moreover, we identified differentially expressed genes (DEGs) and differentially methylated regions (DMRs) according to different TMB levels in 21 cancers. We also investigated the correlation between enrichment of signaling pathways, immune cell infiltration and TMB. In conclusion, we identified multiomic characteristics related to the TMB in 21 tumors, providing support for a comprehensive understanding of the role of TMB in different tumors.
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spelling pubmed-85314622021-11-04 Multiomics analysis of tumor mutational burden across cancer types Li, Lin Bai, Long Lin, Huan Dong, Lin Zhang, Rumeng Cheng, Xiao Liu, Zexian Ouyang, Yi Ding, Keshuo Comput Struct Biotechnol J Research Article Whether tumor mutational burden (TMB) is related to improved survival outcomes or the promotion of immunotherapy in various malignant tumors remains controversial, and we lack a comprehensive understanding of TMB across cancers. Based on the data obtained from The Cancer Genome Atlas (TCGA), we conducted a multiomics analysis of TMB across 21 cancer types to identify characteristics related to TMB and determine the mechanism as it relates to prognosis, gene expression, gene mutation and signaling pathways. In our study, TMB was found to have a significant relationship with prognosis for 21 tumors, and the relationship was different in different tumors. TMB may also be related to different outcomes for patients with different tumor subtypes. TMB was confirmed to be correlated with clinical information, such as age and sex. Mutations in GATA3 and MAP3K1 in beast invasive carcinoma (BRCA), TCF7L2 in colon adenocarcinoma (COAD), NFE2L2 in esophageal carcinoma (ESCA), CIC and IDH1 in brain lower grade glioma (LGG), CDH1 in stomach adenocarcinoma (STAD), and TP53 in uterine corpus endometrial carcinoma (UCEC) were demonstrated to be correlated with lower TMB. Moreover, we identified differentially expressed genes (DEGs) and differentially methylated regions (DMRs) according to different TMB levels in 21 cancers. We also investigated the correlation between enrichment of signaling pathways, immune cell infiltration and TMB. In conclusion, we identified multiomic characteristics related to the TMB in 21 tumors, providing support for a comprehensive understanding of the role of TMB in different tumors. Research Network of Computational and Structural Biotechnology 2021-10-12 /pmc/articles/PMC8531462/ /pubmed/34745455 http://dx.doi.org/10.1016/j.csbj.2021.10.013 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Li, Lin
Bai, Long
Lin, Huan
Dong, Lin
Zhang, Rumeng
Cheng, Xiao
Liu, Zexian
Ouyang, Yi
Ding, Keshuo
Multiomics analysis of tumor mutational burden across cancer types
title Multiomics analysis of tumor mutational burden across cancer types
title_full Multiomics analysis of tumor mutational burden across cancer types
title_fullStr Multiomics analysis of tumor mutational burden across cancer types
title_full_unstemmed Multiomics analysis of tumor mutational burden across cancer types
title_short Multiomics analysis of tumor mutational burden across cancer types
title_sort multiomics analysis of tumor mutational burden across cancer types
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531462/
https://www.ncbi.nlm.nih.gov/pubmed/34745455
http://dx.doi.org/10.1016/j.csbj.2021.10.013
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