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Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer

PURPOSE: Growing evidence has demonstrated an indispensable role for N (6)‐methyladenosine (m(6)A) in human diseases, but the copy number variations (CNVs) of m(6)A regulatory genes in bladder cancer (BLCA) remains largely unknown. METHODS: We investigated the CNVs on all known m(6)A regulatory gene...

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Autores principales: Wang, Xiaoshuai, Yu, Jingwei, Chen, Jinbao, Hou, Yingdong, Du, Zefeng, Huang, Haoyang, Tang, Siqi, Han, Yueyin, Ding, Changhai, Xue, Zhicheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8559456/
https://www.ncbi.nlm.nih.gov/pubmed/34668652
http://dx.doi.org/10.1002/cam4.3981
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author Wang, Xiaoshuai
Yu, Jingwei
Chen, Jinbao
Hou, Yingdong
Du, Zefeng
Huang, Haoyang
Tang, Siqi
Han, Yueyin
Ding, Changhai
Xue, Zhicheng
author_facet Wang, Xiaoshuai
Yu, Jingwei
Chen, Jinbao
Hou, Yingdong
Du, Zefeng
Huang, Haoyang
Tang, Siqi
Han, Yueyin
Ding, Changhai
Xue, Zhicheng
author_sort Wang, Xiaoshuai
collection PubMed
description PURPOSE: Growing evidence has demonstrated an indispensable role for N (6)‐methyladenosine (m(6)A) in human diseases, but the copy number variations (CNVs) of m(6)A regulatory genes in bladder cancer (BLCA) remains largely unknown. METHODS: We investigated the CNVs on all known m(6)A regulatory genes using the Cancer Genome Atlas (TCGA) database. The association between CNV events and clinicopathological as well as molecular characteristics of BLCA patients were explored. Gene set enrichment analysis (GSEA) was implemented to reveal relative cellular processes. Association between m(6)A regulatory genes and immune infiltrates was analyzed by The Tumor Immune Estimation Resource (TIMER) database. RESULTS: CNV events of m(6)A regulatory genes were frequently observed in BLCA. CNVs of METTL3, METTL14, and METTL16 correlated with molecular characteristics of BLCA patients including TP53 mutation. CNVs of METTL3 associated with the overall survival (OS) of BLCA patients. METTL3 was also associated with several cancer‐related cellular processes, including mitotic spindle assembly, G2/M checkpoint, and E2F targets signaling pathway. Besides, the CNVs of m(6)A regulatory genes were correlated with specific kinds of immune infiltrates. CONCLUSIONS: There are significant correlations between m(6)A regulatory genes with CNVs and clinicopathological characteristics. METTL3 with CNVs were associated with the immune infiltrates and performed as a prognostic marker in BLCA.
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spelling pubmed-85594562021-11-08 Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer Wang, Xiaoshuai Yu, Jingwei Chen, Jinbao Hou, Yingdong Du, Zefeng Huang, Haoyang Tang, Siqi Han, Yueyin Ding, Changhai Xue, Zhicheng Cancer Med Bioinformatics PURPOSE: Growing evidence has demonstrated an indispensable role for N (6)‐methyladenosine (m(6)A) in human diseases, but the copy number variations (CNVs) of m(6)A regulatory genes in bladder cancer (BLCA) remains largely unknown. METHODS: We investigated the CNVs on all known m(6)A regulatory genes using the Cancer Genome Atlas (TCGA) database. The association between CNV events and clinicopathological as well as molecular characteristics of BLCA patients were explored. Gene set enrichment analysis (GSEA) was implemented to reveal relative cellular processes. Association between m(6)A regulatory genes and immune infiltrates was analyzed by The Tumor Immune Estimation Resource (TIMER) database. RESULTS: CNV events of m(6)A regulatory genes were frequently observed in BLCA. CNVs of METTL3, METTL14, and METTL16 correlated with molecular characteristics of BLCA patients including TP53 mutation. CNVs of METTL3 associated with the overall survival (OS) of BLCA patients. METTL3 was also associated with several cancer‐related cellular processes, including mitotic spindle assembly, G2/M checkpoint, and E2F targets signaling pathway. Besides, the CNVs of m(6)A regulatory genes were correlated with specific kinds of immune infiltrates. CONCLUSIONS: There are significant correlations between m(6)A regulatory genes with CNVs and clinicopathological characteristics. METTL3 with CNVs were associated with the immune infiltrates and performed as a prognostic marker in BLCA. John Wiley and Sons Inc. 2021-10-20 /pmc/articles/PMC8559456/ /pubmed/34668652 http://dx.doi.org/10.1002/cam4.3981 Text en © 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Bioinformatics
Wang, Xiaoshuai
Yu, Jingwei
Chen, Jinbao
Hou, Yingdong
Du, Zefeng
Huang, Haoyang
Tang, Siqi
Han, Yueyin
Ding, Changhai
Xue, Zhicheng
Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer
title Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer
title_full Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer
title_fullStr Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer
title_full_unstemmed Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer
title_short Copy number variation analysis of m(6)A regulators identified METTL3 as a prognostic and immune‐related biomarker in bladder cancer
title_sort copy number variation analysis of m(6)a regulators identified mettl3 as a prognostic and immune‐related biomarker in bladder cancer
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8559456/
https://www.ncbi.nlm.nih.gov/pubmed/34668652
http://dx.doi.org/10.1002/cam4.3981
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