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A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer

Background: Emerging studies have shown the important roles of long noncoding RNAs (lncRNAs) in the occurrence and development of liver cancer. However, the exosome-related lncRNA signature in liver cancer remains to be clarified. Methods: We obtained 371 tumor specimens and 50 normal tissues from t...

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Autores principales: Su, Duntao, Zhang, Zeyu, Xu, Zhijie, Xia, Fada, Yan, Yuanliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445491/
https://www.ncbi.nlm.nih.gov/pubmed/36081999
http://dx.doi.org/10.3389/fgene.2022.965329
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author Su, Duntao
Zhang, Zeyu
Xu, Zhijie
Xia, Fada
Yan, Yuanliang
author_facet Su, Duntao
Zhang, Zeyu
Xu, Zhijie
Xia, Fada
Yan, Yuanliang
author_sort Su, Duntao
collection PubMed
description Background: Emerging studies have shown the important roles of long noncoding RNAs (lncRNAs) in the occurrence and development of liver cancer. However, the exosome-related lncRNA signature in liver cancer remains to be clarified. Methods: We obtained 371 tumor specimens and 50 normal tissues from the TCGA database. These samples were randomly divided into the training queue and verification queue. The exosome-related lncRNA risk model was verified by correlation analysis, Lasso regression analysis, and Cox regression analysis. The differences in the immune microenvironment in the two risk groups were obtained by analyzing the infiltration of different immune cells. Results: Five exosome-related lncRNAs associated (MKLN1-AS, TMCC1-AS1, AL031985.3, LINC01138, AC099850.3) with a poor prognosis were identified and used to construct the signature. Receiver operating curve (ROC) and survival curves were used to confirm the predictive ability of this signature. Based on multivariate regression analysis in the training cohort (HR: 3.033, 95% CI: 1.762–5.220) and validation cohort (HR: 1.998, 95% CI: 1.065–3.751), the risk score was found to be an independent risk factor for patient prognosis. Subsequently, a nomogram was constructed to predict the 1-, 3-, 5-years survival rates of liver cancer patients. Moreover, this signature was also related to overexpressed immune checkpoints (PD-1, B7-H3, VSIR, PD-L1, LAG3, TIGIT and CTLA4). Conclusion: Our study showed that exosome-related lncRNAs and the corresponding nomogram could be used as a better index to predict the outcome and immune regulation of liver cancer patients. This signature might provide a new idea for the immunotherapy of liver cancer in the future.
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spelling pubmed-94454912022-09-07 A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer Su, Duntao Zhang, Zeyu Xu, Zhijie Xia, Fada Yan, Yuanliang Front Genet Genetics Background: Emerging studies have shown the important roles of long noncoding RNAs (lncRNAs) in the occurrence and development of liver cancer. However, the exosome-related lncRNA signature in liver cancer remains to be clarified. Methods: We obtained 371 tumor specimens and 50 normal tissues from the TCGA database. These samples were randomly divided into the training queue and verification queue. The exosome-related lncRNA risk model was verified by correlation analysis, Lasso regression analysis, and Cox regression analysis. The differences in the immune microenvironment in the two risk groups were obtained by analyzing the infiltration of different immune cells. Results: Five exosome-related lncRNAs associated (MKLN1-AS, TMCC1-AS1, AL031985.3, LINC01138, AC099850.3) with a poor prognosis were identified and used to construct the signature. Receiver operating curve (ROC) and survival curves were used to confirm the predictive ability of this signature. Based on multivariate regression analysis in the training cohort (HR: 3.033, 95% CI: 1.762–5.220) and validation cohort (HR: 1.998, 95% CI: 1.065–3.751), the risk score was found to be an independent risk factor for patient prognosis. Subsequently, a nomogram was constructed to predict the 1-, 3-, 5-years survival rates of liver cancer patients. Moreover, this signature was also related to overexpressed immune checkpoints (PD-1, B7-H3, VSIR, PD-L1, LAG3, TIGIT and CTLA4). Conclusion: Our study showed that exosome-related lncRNAs and the corresponding nomogram could be used as a better index to predict the outcome and immune regulation of liver cancer patients. This signature might provide a new idea for the immunotherapy of liver cancer in the future. Frontiers Media S.A. 2022-08-23 /pmc/articles/PMC9445491/ /pubmed/36081999 http://dx.doi.org/10.3389/fgene.2022.965329 Text en Copyright © 2022 Su, Zhang, Xu, Xia and Yan. 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
Su, Duntao
Zhang, Zeyu
Xu, Zhijie
Xia, Fada
Yan, Yuanliang
A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer
title A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer
title_full A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer
title_fullStr A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer
title_full_unstemmed A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer
title_short A prognostic exosome-related LncRNA risk model correlates with the immune microenvironment in liver cancer
title_sort prognostic exosome-related lncrna risk model correlates with the immune microenvironment in liver cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445491/
https://www.ncbi.nlm.nih.gov/pubmed/36081999
http://dx.doi.org/10.3389/fgene.2022.965329
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