Cargando…

The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics

OBJECTIVE: Epigenetic aberration plays an important role in the development and progression of hepatocellular carcinoma (HCC). However, the alteration of RNA N6-methyladenosine (m6A) modifications and its role in HCC progression remain unclear. We therefore aimed to provide evidence using bioinforma...

Descripción completa

Detalles Bibliográficos
Autores principales: Shen, Xiaotian, Hu, Beiyuan, Xu, Jing, Qin, Wei, Fu, Yan, Wang, Shun, Dong, Qiongzhu, Qin, Lunxiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Compuscript 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721089/
https://www.ncbi.nlm.nih.gov/pubmed/33299645
http://dx.doi.org/10.20892/j.issn.2095-3941.2020.0402
_version_ 1783619971125870592
author Shen, Xiaotian
Hu, Beiyuan
Xu, Jing
Qin, Wei
Fu, Yan
Wang, Shun
Dong, Qiongzhu
Qin, Lunxiu
author_facet Shen, Xiaotian
Hu, Beiyuan
Xu, Jing
Qin, Wei
Fu, Yan
Wang, Shun
Dong, Qiongzhu
Qin, Lunxiu
author_sort Shen, Xiaotian
collection PubMed
description OBJECTIVE: Epigenetic aberration plays an important role in the development and progression of hepatocellular carcinoma (HCC). However, the alteration of RNA N6-methyladenosine (m6A) modifications and its role in HCC progression remain unclear. We therefore aimed to provide evidence using bioinformatics analysis. METHODS: We comprehensively analyzed the m6A regulator modification patterns of 605 HCC samples and correlated them with metabolic alteration characteristics. We elucidated 390 gene-based m6A-related signatures and defined an m6Ascore to quantify m6A modifications. We then assessed their values for predicting prognoses and therapeutic responses in HCC patients. RESULTS: We identified 3 distinct m6A modification patterns in HCC, and each pattern had distinct metabolic characteristics. The evaluation of m6A modification patterns using m6Ascores could predict the prognoses, tumor stages, and responses to sorafenib treatments of HCC patients. A nomogram based on m6Ascores showed high accuracy in predicting the overall survival of patients. The area under the receiver operating characteristic curve of predictions of 1, 3, and 5-year overall survivals were 0.71, 0.69, and 0.70 in the training cohort, and in the test cohort it was 0.74, 0.75, and 0.71, respectively. M6Acluster C1, which corresponded to hypoactive mRNA methylation, lower expression of m6A regulators, and a lower m6Ascore, was characterized by metabolic hyperactivity, lower tumor stage, better prognosis, and lower response to sorafenib treatment. In contrast, m6Acluster C3 was distinct in its hyperactive mRNA methylations, higher expression of m6A regulators, and higher m6Ascores, and was characterized by hypoactive metabolism, advanced tumor stage, poorer prognosis, and a better response to sorafenib. The m6Acluster, C2, was intermediate between C1 and C3. CONCLUSIONS: HCCs harbored distinct m6A regulator modification patterns that contributed to the metabolic heterogeneity and diversity of HCC. Development of m6A gene signatures and the m6Ascore provides a more comprehensive understanding of m6A modifications in HCC, and helps predict the prognosis and treatment response.
format Online
Article
Text
id pubmed-7721089
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Compuscript
record_format MEDLINE/PubMed
spelling pubmed-77210892020-12-08 The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics Shen, Xiaotian Hu, Beiyuan Xu, Jing Qin, Wei Fu, Yan Wang, Shun Dong, Qiongzhu Qin, Lunxiu Cancer Biol Med Original Article OBJECTIVE: Epigenetic aberration plays an important role in the development and progression of hepatocellular carcinoma (HCC). However, the alteration of RNA N6-methyladenosine (m6A) modifications and its role in HCC progression remain unclear. We therefore aimed to provide evidence using bioinformatics analysis. METHODS: We comprehensively analyzed the m6A regulator modification patterns of 605 HCC samples and correlated them with metabolic alteration characteristics. We elucidated 390 gene-based m6A-related signatures and defined an m6Ascore to quantify m6A modifications. We then assessed their values for predicting prognoses and therapeutic responses in HCC patients. RESULTS: We identified 3 distinct m6A modification patterns in HCC, and each pattern had distinct metabolic characteristics. The evaluation of m6A modification patterns using m6Ascores could predict the prognoses, tumor stages, and responses to sorafenib treatments of HCC patients. A nomogram based on m6Ascores showed high accuracy in predicting the overall survival of patients. The area under the receiver operating characteristic curve of predictions of 1, 3, and 5-year overall survivals were 0.71, 0.69, and 0.70 in the training cohort, and in the test cohort it was 0.74, 0.75, and 0.71, respectively. M6Acluster C1, which corresponded to hypoactive mRNA methylation, lower expression of m6A regulators, and a lower m6Ascore, was characterized by metabolic hyperactivity, lower tumor stage, better prognosis, and lower response to sorafenib treatment. In contrast, m6Acluster C3 was distinct in its hyperactive mRNA methylations, higher expression of m6A regulators, and higher m6Ascores, and was characterized by hypoactive metabolism, advanced tumor stage, poorer prognosis, and a better response to sorafenib. The m6Acluster, C2, was intermediate between C1 and C3. CONCLUSIONS: HCCs harbored distinct m6A regulator modification patterns that contributed to the metabolic heterogeneity and diversity of HCC. Development of m6A gene signatures and the m6Ascore provides a more comprehensive understanding of m6A modifications in HCC, and helps predict the prognosis and treatment response. Compuscript 2020-11-15 2020-12-15 /pmc/articles/PMC7721089/ /pubmed/33299645 http://dx.doi.org/10.20892/j.issn.2095-3941.2020.0402 Text en Copyright: © 2020, Cancer Biology & Medicine 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) 4.0 (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
spellingShingle Original Article
Shen, Xiaotian
Hu, Beiyuan
Xu, Jing
Qin, Wei
Fu, Yan
Wang, Shun
Dong, Qiongzhu
Qin, Lunxiu
The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics
title The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics
title_full The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics
title_fullStr The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics
title_full_unstemmed The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics
title_short The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics
title_sort m6a methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721089/
https://www.ncbi.nlm.nih.gov/pubmed/33299645
http://dx.doi.org/10.20892/j.issn.2095-3941.2020.0402
work_keys_str_mv AT shenxiaotian them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT hubeiyuan them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT xujing them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT qinwei them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT fuyan them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT wangshun them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT dongqiongzhu them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT qinlunxiu them6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT shenxiaotian m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT hubeiyuan m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT xujing m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT qinwei m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT fuyan m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT wangshun m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT dongqiongzhu m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics
AT qinlunxiu m6amethylationlandscapestratifieshepatocellularcarcinomainto3subtypeswithdistinctmetaboliccharacteristics