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Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma
BACKGROUND: Liver hepatocellular carcinoma (LIHC), whose incidence is increasing globally, is one of the most prevalent malignant cancers. RAS-related pathways are involved in the cell proliferation, migration, apoptosis, and metabolism in LIHC. Long noncoding RNAs (lncRNAs) also play important role...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843414/ https://www.ncbi.nlm.nih.gov/pubmed/36660710 http://dx.doi.org/10.21037/atm-22-5827 |
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author | Li, Ding Fan, Xinxin Zuo, Lihua Wu, Xuan Wu, Yingxi Zhang, Yuanyuan Zou, Fanmei Sun, Zhi Zhang, Wenzhou |
author_facet | Li, Ding Fan, Xinxin Zuo, Lihua Wu, Xuan Wu, Yingxi Zhang, Yuanyuan Zou, Fanmei Sun, Zhi Zhang, Wenzhou |
author_sort | Li, Ding |
collection | PubMed |
description | BACKGROUND: Liver hepatocellular carcinoma (LIHC), whose incidence is increasing globally, is one of the most prevalent malignant cancers. RAS-related pathways are involved in the cell proliferation, migration, apoptosis, and metabolism in LIHC. Long noncoding RNAs (lncRNAs) also play important roles in the progression and prognosis of LIHC. However, the clinical role, prognostic significance, and immune regulation of RAS-related lncRNAs in LIHC remains unclear. Our study aims to construct and validate a RAS-related lncRNA prognostic risk signature that can estimate the prognosis and response to immunotherapy in LIHC. METHODS: The clinical information and corresponding messenger RNA (mRNA)/lncRNA expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and 502 RAS-related lncRNAs were identified by Pearson correlation analysis. A prognostic risk signature with 5 RAS-related lncRNAs was then developed based on the Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm analyses. Subsequently, Kaplan-Meier survival curve, receiver operating characteristic (ROC) curve, and the nomogram were established to evaluate the predictive accuracy of the signature. In addition, the immune microenvironment, tumor mutation burden, and drug sensitivity associated with the signature were also analyzed in LIHC. RESULTS: Compared with the low-risk groups, the high-risk groups had an unfavorable outcome. Multivariate regression analysis revealed that the risk score signature was the independent prognostic factor superior to the other clinical variables. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses demonstrated that the risk score was highly associated with the nuclear division, DNA replication, and immune response. The group with high risk tended to hold a lower immune escape rate and better immunotherapy efficacy, while the group with low risk was more sensitive to some small molecular targeted drugs. CONCLUSIONS: We developed a RAS-related lncRNA risk signature that was highly associated with the prognosis and response to immunotherapy and targeted drugs and which provided novel mechanistic insights into the personalized treatment and potential drug selection for patients with LIHC. |
format | Online Article Text |
id | pubmed-9843414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-98434142023-01-18 Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma Li, Ding Fan, Xinxin Zuo, Lihua Wu, Xuan Wu, Yingxi Zhang, Yuanyuan Zou, Fanmei Sun, Zhi Zhang, Wenzhou Ann Transl Med Original Article BACKGROUND: Liver hepatocellular carcinoma (LIHC), whose incidence is increasing globally, is one of the most prevalent malignant cancers. RAS-related pathways are involved in the cell proliferation, migration, apoptosis, and metabolism in LIHC. Long noncoding RNAs (lncRNAs) also play important roles in the progression and prognosis of LIHC. However, the clinical role, prognostic significance, and immune regulation of RAS-related lncRNAs in LIHC remains unclear. Our study aims to construct and validate a RAS-related lncRNA prognostic risk signature that can estimate the prognosis and response to immunotherapy in LIHC. METHODS: The clinical information and corresponding messenger RNA (mRNA)/lncRNA expression profiles were obtained from The Cancer Genome Atlas (TCGA) database, and 502 RAS-related lncRNAs were identified by Pearson correlation analysis. A prognostic risk signature with 5 RAS-related lncRNAs was then developed based on the Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm analyses. Subsequently, Kaplan-Meier survival curve, receiver operating characteristic (ROC) curve, and the nomogram were established to evaluate the predictive accuracy of the signature. In addition, the immune microenvironment, tumor mutation burden, and drug sensitivity associated with the signature were also analyzed in LIHC. RESULTS: Compared with the low-risk groups, the high-risk groups had an unfavorable outcome. Multivariate regression analysis revealed that the risk score signature was the independent prognostic factor superior to the other clinical variables. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses demonstrated that the risk score was highly associated with the nuclear division, DNA replication, and immune response. The group with high risk tended to hold a lower immune escape rate and better immunotherapy efficacy, while the group with low risk was more sensitive to some small molecular targeted drugs. CONCLUSIONS: We developed a RAS-related lncRNA risk signature that was highly associated with the prognosis and response to immunotherapy and targeted drugs and which provided novel mechanistic insights into the personalized treatment and potential drug selection for patients with LIHC. AME Publishing Company 2022-12 /pmc/articles/PMC9843414/ /pubmed/36660710 http://dx.doi.org/10.21037/atm-22-5827 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Li, Ding Fan, Xinxin Zuo, Lihua Wu, Xuan Wu, Yingxi Zhang, Yuanyuan Zou, Fanmei Sun, Zhi Zhang, Wenzhou Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma |
title | Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma |
title_full | Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma |
title_fullStr | Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma |
title_full_unstemmed | Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma |
title_short | Prognostic analysis of RAS-related lncRNAs in liver hepatocellular carcinoma |
title_sort | prognostic analysis of ras-related lncrnas in liver hepatocellular carcinoma |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843414/ https://www.ncbi.nlm.nih.gov/pubmed/36660710 http://dx.doi.org/10.21037/atm-22-5827 |
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