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Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma
Nowadays, primary liver cancer is still a major threat to human health. Anoikis is a particular form of programed cell death that has an inhibitory effect on neoplasm metastasis. Although several prognostic models based on anoikis‐related genes for Hepatocellular carcinoma (HCC) have been establishe...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439496/ https://www.ncbi.nlm.nih.gov/pubmed/37417684 http://dx.doi.org/10.1049/syb2.12070 |
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author | Du, Sihao Cao, Ke Wang, Zhenshun Lin, Dongdong |
author_facet | Du, Sihao Cao, Ke Wang, Zhenshun Lin, Dongdong |
author_sort | Du, Sihao |
collection | PubMed |
description | Nowadays, primary liver cancer is still a major threat to human health. Anoikis is a particular form of programed cell death that has an inhibitory effect on neoplasm metastasis. Although several prognostic models based on anoikis‐related genes for Hepatocellular carcinoma (HCC) have been established, signatures associated with anoikis‐related lncRNAs have not been identified. To fill this blank space, the authors built up a prognostic signature and appraised its value in guiding immunotherapy. Eleven prognostic anoikis‐related lncRNAs were identified through Least Absolute Shrinkage and Selection Operator Cox analysis. The accuracy of the risk signature in predicting prognosis was verified by K–M survival analysis and Receiver operating characteristic analysis. We further discovered that the high‐risk group was often enriched in signal pathways related to cell growth and death and immune response; in addition, in the low‐risk group, cells often undergo metabolic changes through gene set enrichment analysis. Finally, we realised that HCC patients in the high‐risk group were upregulated in immune‐checkpoint molecules and tend to have a higher tumour mutation burden level which indicated a higher sensitivity to immunotherapy. All in all, the anoikis‐related lncRNAs risk signature showed excellent ability in predicting prognosis and may guide the application of immunotherapy in future clinical practice. |
format | Online Article Text |
id | pubmed-10439496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104394962023-08-20 Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma Du, Sihao Cao, Ke Wang, Zhenshun Lin, Dongdong IET Syst Biol Original Research Nowadays, primary liver cancer is still a major threat to human health. Anoikis is a particular form of programed cell death that has an inhibitory effect on neoplasm metastasis. Although several prognostic models based on anoikis‐related genes for Hepatocellular carcinoma (HCC) have been established, signatures associated with anoikis‐related lncRNAs have not been identified. To fill this blank space, the authors built up a prognostic signature and appraised its value in guiding immunotherapy. Eleven prognostic anoikis‐related lncRNAs were identified through Least Absolute Shrinkage and Selection Operator Cox analysis. The accuracy of the risk signature in predicting prognosis was verified by K–M survival analysis and Receiver operating characteristic analysis. We further discovered that the high‐risk group was often enriched in signal pathways related to cell growth and death and immune response; in addition, in the low‐risk group, cells often undergo metabolic changes through gene set enrichment analysis. Finally, we realised that HCC patients in the high‐risk group were upregulated in immune‐checkpoint molecules and tend to have a higher tumour mutation burden level which indicated a higher sensitivity to immunotherapy. All in all, the anoikis‐related lncRNAs risk signature showed excellent ability in predicting prognosis and may guide the application of immunotherapy in future clinical practice. John Wiley and Sons Inc. 2023-07-07 /pmc/articles/PMC10439496/ /pubmed/37417684 http://dx.doi.org/10.1049/syb2.12070 Text en © 2023 The Authors. IET Systems Biology published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Research Du, Sihao Cao, Ke Wang, Zhenshun Lin, Dongdong Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma |
title | Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma |
title_full | Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma |
title_fullStr | Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma |
title_full_unstemmed | Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma |
title_short | Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma |
title_sort | comprehensive analysis of anoikis‐related lncrnas for predicting prognosis and response of immunotherapy in hepatocellular carcinoma |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439496/ https://www.ncbi.nlm.nih.gov/pubmed/37417684 http://dx.doi.org/10.1049/syb2.12070 |
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