Classification of Hepatocellular Carcinoma Based on N6-Methylandenosine-Related lncRNAs Profiling

Copyright © 2022 Yin, Zhou, Gao, Feng, Zhu, Xiang and Xu..

HCC is one of the most common types of malignancies worldwide and the fourth-leading cause of cancer deaths. Thus, there is an urgent need to search for novel targeted therapies in HCC. 186 m6a-related lncRNAs were screened for subsequent analysis. Two distinct m6A modification clusters were identified to be associated with the overall prognosis in TCGA-LIHC based on the m6A-related lncRNAs profiling, followed by univariate Cox regression analysis. In addition, four m6A-related lncRNAs prognostic signatures were developed and validated that could predict the OS of HCC patients, followed by univariate Cox regression, LASSO regression, and multivariate Cox regression analysis. Moreover, four m6A-related lncRNAs were identified to be related to HCC prognosis. ESTIMATE was used to evaluate the stromal score, immune score, ESTIMATE score, and tumor purity of each HCC sample. ssGSEA was performed to identify the enrichment levels of 29 immune signatures in each sample. Finally, quantitative real-time polymerase chain reaction shown that KDM4A-AS1, BACE1-AS, and NRAV expressions were upregulated in HCC patients. We proved that our m6A-related lncRNAs signature had powerful and robust ability for predicting OS of different HCC subgroups.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:9

Enthalten in:

Frontiers in molecular biosciences - 9(2022) vom: 02., Seite 807418

Sprache:

Englisch

Beteiligte Personen:

Yin, Lu [VerfasserIn]
Zhou, Liuzhi [VerfasserIn]
Gao, Shiqi [VerfasserIn]
Feng, Yina [VerfasserIn]
Zhu, Hanzhang [VerfasserIn]
Xiang, Jingjing [VerfasserIn]
Xu, Rujun [VerfasserIn]

Links:

Volltext

Themen:

Biomarkers
Classification
Hepatocellular carcinoma
Journal Article
M6A-related lncRNA
Machine learning
Prognosis
Tumor microenvironment

Anmerkungen:

Date Revised 23.02.2022

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.3389/fmolb.2022.807418

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM337189102