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A novel classification of HCC basing on fatty-acid-associated lncRNA

Aberrant long noncoding RNA (lncRNA) expression and fatty acid signaling dysfunction both contribute to hepatocellular carcinoma (HCC) occurrence and development. However, the relationship and interaction mechanism between lncRNAs and fatty acid signaling in HCC remain unclear. Data regarding RNA ex...

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Autores principales: Xu, Yating, Yu, Xiao, Zhang, Qiyao, He, Yuting, Guo, Wenzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640627/
https://www.ncbi.nlm.nih.gov/pubmed/36344648
http://dx.doi.org/10.1038/s41598-022-23681-0
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author Xu, Yating
Yu, Xiao
Zhang, Qiyao
He, Yuting
Guo, Wenzhi
author_facet Xu, Yating
Yu, Xiao
Zhang, Qiyao
He, Yuting
Guo, Wenzhi
author_sort Xu, Yating
collection PubMed
description Aberrant long noncoding RNA (lncRNA) expression and fatty acid signaling dysfunction both contribute to hepatocellular carcinoma (HCC) occurrence and development. However, the relationship and interaction mechanism between lncRNAs and fatty acid signaling in HCC remain unclear. Data regarding RNA expression and clinical outcomes for patients with HCC were obtained from The Cancer Genome Atlas (TCGA), HCCDB, and the Gene Expression Omnibus (GEO) databases. Hallmark pathways were identified using the single-sample gene set enrichment analysis (ssGSEA) method. ConsensusClusterPlus was used to establish a consistency matrix for classifying samples into three subtypes. A risk signature was established, and predictive values for key lncRNAs related to prognosis were evaluated using Kaplan–Meier analysis and receiver operating characteristic curves. The ESTIMATE algorithm, MCP-Counter, and ssGSEA were used to evaluate the characteristics of the tumor immune microenvironment. The CTRP2.0 and PRISM were used to analyze drug sensitivity in HCC subtypes. We discovered seven fatty-acid-associated lncRNAs with predictive prognostic capabilities, including TRAF3IP2-AS1, SNHG10, AL157392.2, LINC02641, AL357079.1, AC046134.2, and A1BG-AS. Three subtypes were obtained, which presented with differences in prognosis, clinical information, mutation features, pathway traits, immune characteristics, and drug sensitivity. The seven key lncRNAs identified in this study might serve as promising biomarkers for predicting prognosis in patients with HCC, and the three HCC subtypes classified according to lncRNA expression profiles could improve HCC classification.
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spelling pubmed-96406272022-11-15 A novel classification of HCC basing on fatty-acid-associated lncRNA Xu, Yating Yu, Xiao Zhang, Qiyao He, Yuting Guo, Wenzhi Sci Rep Article Aberrant long noncoding RNA (lncRNA) expression and fatty acid signaling dysfunction both contribute to hepatocellular carcinoma (HCC) occurrence and development. However, the relationship and interaction mechanism between lncRNAs and fatty acid signaling in HCC remain unclear. Data regarding RNA expression and clinical outcomes for patients with HCC were obtained from The Cancer Genome Atlas (TCGA), HCCDB, and the Gene Expression Omnibus (GEO) databases. Hallmark pathways were identified using the single-sample gene set enrichment analysis (ssGSEA) method. ConsensusClusterPlus was used to establish a consistency matrix for classifying samples into three subtypes. A risk signature was established, and predictive values for key lncRNAs related to prognosis were evaluated using Kaplan–Meier analysis and receiver operating characteristic curves. The ESTIMATE algorithm, MCP-Counter, and ssGSEA were used to evaluate the characteristics of the tumor immune microenvironment. The CTRP2.0 and PRISM were used to analyze drug sensitivity in HCC subtypes. We discovered seven fatty-acid-associated lncRNAs with predictive prognostic capabilities, including TRAF3IP2-AS1, SNHG10, AL157392.2, LINC02641, AL357079.1, AC046134.2, and A1BG-AS. Three subtypes were obtained, which presented with differences in prognosis, clinical information, mutation features, pathway traits, immune characteristics, and drug sensitivity. The seven key lncRNAs identified in this study might serve as promising biomarkers for predicting prognosis in patients with HCC, and the three HCC subtypes classified according to lncRNA expression profiles could improve HCC classification. Nature Publishing Group UK 2022-11-07 /pmc/articles/PMC9640627/ /pubmed/36344648 http://dx.doi.org/10.1038/s41598-022-23681-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Xu, Yating
Yu, Xiao
Zhang, Qiyao
He, Yuting
Guo, Wenzhi
A novel classification of HCC basing on fatty-acid-associated lncRNA
title A novel classification of HCC basing on fatty-acid-associated lncRNA
title_full A novel classification of HCC basing on fatty-acid-associated lncRNA
title_fullStr A novel classification of HCC basing on fatty-acid-associated lncRNA
title_full_unstemmed A novel classification of HCC basing on fatty-acid-associated lncRNA
title_short A novel classification of HCC basing on fatty-acid-associated lncRNA
title_sort novel classification of hcc basing on fatty-acid-associated lncrna
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640627/
https://www.ncbi.nlm.nih.gov/pubmed/36344648
http://dx.doi.org/10.1038/s41598-022-23681-0
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