Cargando…

Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients

Despite recent advances in surgical and multimodal therapies, the overall survival (OS) of advanced colorectal cancer (CRC) patients remains low. Thus, discerning sensitive prognostic biomarkers to give the optimistic treatment for CRC patients is extremely critical. N6-methyladenosine (m6A) and lon...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Zhiyong, Liu, Yang, Yi, Huijie, Cai, Ting, Wei, Yunwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561883/
https://www.ncbi.nlm.nih.gov/pubmed/36246627
http://dx.doi.org/10.3389/fgene.2022.947747
_version_ 1784808045641990144
author Li, Zhiyong
Liu, Yang
Yi, Huijie
Cai, Ting
Wei, Yunwei
author_facet Li, Zhiyong
Liu, Yang
Yi, Huijie
Cai, Ting
Wei, Yunwei
author_sort Li, Zhiyong
collection PubMed
description Despite recent advances in surgical and multimodal therapies, the overall survival (OS) of advanced colorectal cancer (CRC) patients remains low. Thus, discerning sensitive prognostic biomarkers to give the optimistic treatment for CRC patients is extremely critical. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play an important role in CRC progression. Nonetheless, few studies have focused on the impact of m6A-related lncRNAs on the prognosis, tumor microenvironment (TME) and treatment of CRC. In this study, 1707 m6A-related lncRNAs were identified through Pearson correlation analysis and Weighted co-expression network analysis (WGCNA) using The Cancer Genome Atlas (TCGA) cohort. Then, 28 m6A-related prognostic lncRNAs were screened by univariate Cox regression analysis, followed by identifying two clusters by consensus clustering analysis. A prognostic model consisted of 8 lncRNA signatures was constructed by the least absolute shrinkage and selection operator (LASSO). Kaplan–Meier curve analysis and a nomogram were performed to investigate the prognostic ability of this model. The risk score of prognostic model act as an independent risk factor for OS rate. Functional enrichment analysis indicated that lncRNA signatures related tumor immunity. The low-risk group characterized by increased microsatellite instability-high (MSI-H), mutation burden, and immunity activation, indicated favorable odds of OS. Moreover, the lncRNA signatures were significantly associated with the cancer stem cell (CSC) index and drug sensitivity. In addition, 3 common immune genes shared by the lncRNA signatures were screened out. We found that these immune genes were widely distributed in 2 cell types of TME. Finally, a ceRNA network was constructed to identify ZEB1-AS1 regulatory axis in CRC. We found that ZEB1-AS1 was significantly overexpressed in tumor tissues, and was related to the metastasis of EMT and the chemoresistance of 5-Fu in CRC. Therefore, our study demonstrated the important role of m6A-related lncRNAs in TME remodeling. Moreover, these results illustrated the levels of ZEB1-AS1 might be valuable for predicting the progression and prognosis of CRC, and further provided a new target for the diagnosis and treatment of CRC patients.
format Online
Article
Text
id pubmed-9561883
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-95618832022-10-15 Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients Li, Zhiyong Liu, Yang Yi, Huijie Cai, Ting Wei, Yunwei Front Genet Genetics Despite recent advances in surgical and multimodal therapies, the overall survival (OS) of advanced colorectal cancer (CRC) patients remains low. Thus, discerning sensitive prognostic biomarkers to give the optimistic treatment for CRC patients is extremely critical. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play an important role in CRC progression. Nonetheless, few studies have focused on the impact of m6A-related lncRNAs on the prognosis, tumor microenvironment (TME) and treatment of CRC. In this study, 1707 m6A-related lncRNAs were identified through Pearson correlation analysis and Weighted co-expression network analysis (WGCNA) using The Cancer Genome Atlas (TCGA) cohort. Then, 28 m6A-related prognostic lncRNAs were screened by univariate Cox regression analysis, followed by identifying two clusters by consensus clustering analysis. A prognostic model consisted of 8 lncRNA signatures was constructed by the least absolute shrinkage and selection operator (LASSO). Kaplan–Meier curve analysis and a nomogram were performed to investigate the prognostic ability of this model. The risk score of prognostic model act as an independent risk factor for OS rate. Functional enrichment analysis indicated that lncRNA signatures related tumor immunity. The low-risk group characterized by increased microsatellite instability-high (MSI-H), mutation burden, and immunity activation, indicated favorable odds of OS. Moreover, the lncRNA signatures were significantly associated with the cancer stem cell (CSC) index and drug sensitivity. In addition, 3 common immune genes shared by the lncRNA signatures were screened out. We found that these immune genes were widely distributed in 2 cell types of TME. Finally, a ceRNA network was constructed to identify ZEB1-AS1 regulatory axis in CRC. We found that ZEB1-AS1 was significantly overexpressed in tumor tissues, and was related to the metastasis of EMT and the chemoresistance of 5-Fu in CRC. Therefore, our study demonstrated the important role of m6A-related lncRNAs in TME remodeling. Moreover, these results illustrated the levels of ZEB1-AS1 might be valuable for predicting the progression and prognosis of CRC, and further provided a new target for the diagnosis and treatment of CRC patients. Frontiers Media S.A. 2022-09-30 /pmc/articles/PMC9561883/ /pubmed/36246627 http://dx.doi.org/10.3389/fgene.2022.947747 Text en Copyright © 2022 Li, Liu, Yi, Cai and Wei. 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 Genetics
Li, Zhiyong
Liu, Yang
Yi, Huijie
Cai, Ting
Wei, Yunwei
Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients
title Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients
title_full Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients
title_fullStr Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients
title_full_unstemmed Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients
title_short Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients
title_sort identification of n6-methylandenosine related lncrna signatures for predicting the prognosis and therapy response in colorectal cancer patients
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9561883/
https://www.ncbi.nlm.nih.gov/pubmed/36246627
http://dx.doi.org/10.3389/fgene.2022.947747
work_keys_str_mv AT lizhiyong identificationofn6methylandenosinerelatedlncrnasignaturesforpredictingtheprognosisandtherapyresponseincolorectalcancerpatients
AT liuyang identificationofn6methylandenosinerelatedlncrnasignaturesforpredictingtheprognosisandtherapyresponseincolorectalcancerpatients
AT yihuijie identificationofn6methylandenosinerelatedlncrnasignaturesforpredictingtheprognosisandtherapyresponseincolorectalcancerpatients
AT caiting identificationofn6methylandenosinerelatedlncrnasignaturesforpredictingtheprognosisandtherapyresponseincolorectalcancerpatients
AT weiyunwei identificationofn6methylandenosinerelatedlncrnasignaturesforpredictingtheprognosisandtherapyresponseincolorectalcancerpatients