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A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma

BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis. Cuproptosis is a novel type of cell death, which differs from previously reported types of cell death such as apoptosis, autophagy, proptosis, ferroptosis, necroptosis, etc. Long non-coding RNAs (lncRNAs) play multip...

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Autores principales: Wu, Jingyi, Yao, Jianzuo, Jia, Shu, Yao, Xiaokun, Shao, Jingping, Cao, Weijuan, Ma, Shuwei, Yao, Xiaomin, Li, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558351/
https://www.ncbi.nlm.nih.gov/pubmed/37810122
http://dx.doi.org/10.1016/j.heliyon.2023.e19352
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author Wu, Jingyi
Yao, Jianzuo
Jia, Shu
Yao, Xiaokun
Shao, Jingping
Cao, Weijuan
Ma, Shuwei
Yao, Xiaomin
Li, Hong
author_facet Wu, Jingyi
Yao, Jianzuo
Jia, Shu
Yao, Xiaokun
Shao, Jingping
Cao, Weijuan
Ma, Shuwei
Yao, Xiaomin
Li, Hong
author_sort Wu, Jingyi
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis. Cuproptosis is a novel type of cell death, which differs from previously reported types of cell death such as apoptosis, autophagy, proptosis, ferroptosis, necroptosis, etc. Long non-coding RNAs (lncRNAs) play multiple roles in HCC. METHODS: We downloaded information from The Cancer Genome Atlas (TCGA) database, and obtained cuproptosis-related genes from published studies. The cuproptosis-related lncRNAs were obtained by correlation analysis, and subsequently used to construct a prognostic cuproptosis-related lncRNA signature. Analyses of overall survival (OS), progression-free survival (PFS), receiver operating characteristic (ROC) curve with the area under the curve (AUC) values and the index of concordance (c-index) curve were used to evaluate the signature. The tumor microenvironment (TME) was analyzed by ESTIMATE algorithm. The immune cell data was downloaded from the Tumor Immune Estimation Resource (TIMER) 2.0 database. Immune-related pathways were analyzed by single-sample gene set enrichment analysis (ssGSEA) algorithm. Immunophenoscore (IPS) scores from The Cancer Immunome (TCIA) database were used to evaluate immunotherapy response. The “pRRophetic” was employed to screen drugs for high-risk patients. The candidate lncRNA expression levels were detected by Real Time Quantitative PCR. RESULTS: We constructed a cuproptosis-related lncRNA signature containing seven lncRNAs: AC125437.1, PCED1B-AS1, PICSAR, AP001372.2, AC027097.1, LINC00479, and SLC6A1-AS1. This signature had excellent accuracy, and was independent of the stratification of clinicopathological features. Further study showed that high-risk tumors under this signature had higher TMB, fewer TME components and higher tumor purity. The tumors with high risk were not enriched in immune cell infiltration or immune process pathways, and high-risk patients had a poor response to immunotherapy. Moreover, 29 drugs such as sorafenib, dasatinib and paclitaxel were screened for high-risk HCC patients to improve their prognosis. The expression levels of the candidate lncRNAs in HCC tissue were significantly increased (except PCED1B-AS1). CONCLUSIONS: Our prognostic cuproptosis-related lncRNA signature was accurate and effective for predicting the prognosis of HCC. The immunotherapy was unsuitable for high-risk HCC patients with this signature.
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spelling pubmed-105583512023-10-08 A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma Wu, Jingyi Yao, Jianzuo Jia, Shu Yao, Xiaokun Shao, Jingping Cao, Weijuan Ma, Shuwei Yao, Xiaomin Li, Hong Heliyon Research Article BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis. Cuproptosis is a novel type of cell death, which differs from previously reported types of cell death such as apoptosis, autophagy, proptosis, ferroptosis, necroptosis, etc. Long non-coding RNAs (lncRNAs) play multiple roles in HCC. METHODS: We downloaded information from The Cancer Genome Atlas (TCGA) database, and obtained cuproptosis-related genes from published studies. The cuproptosis-related lncRNAs were obtained by correlation analysis, and subsequently used to construct a prognostic cuproptosis-related lncRNA signature. Analyses of overall survival (OS), progression-free survival (PFS), receiver operating characteristic (ROC) curve with the area under the curve (AUC) values and the index of concordance (c-index) curve were used to evaluate the signature. The tumor microenvironment (TME) was analyzed by ESTIMATE algorithm. The immune cell data was downloaded from the Tumor Immune Estimation Resource (TIMER) 2.0 database. Immune-related pathways were analyzed by single-sample gene set enrichment analysis (ssGSEA) algorithm. Immunophenoscore (IPS) scores from The Cancer Immunome (TCIA) database were used to evaluate immunotherapy response. The “pRRophetic” was employed to screen drugs for high-risk patients. The candidate lncRNA expression levels were detected by Real Time Quantitative PCR. RESULTS: We constructed a cuproptosis-related lncRNA signature containing seven lncRNAs: AC125437.1, PCED1B-AS1, PICSAR, AP001372.2, AC027097.1, LINC00479, and SLC6A1-AS1. This signature had excellent accuracy, and was independent of the stratification of clinicopathological features. Further study showed that high-risk tumors under this signature had higher TMB, fewer TME components and higher tumor purity. The tumors with high risk were not enriched in immune cell infiltration or immune process pathways, and high-risk patients had a poor response to immunotherapy. Moreover, 29 drugs such as sorafenib, dasatinib and paclitaxel were screened for high-risk HCC patients to improve their prognosis. The expression levels of the candidate lncRNAs in HCC tissue were significantly increased (except PCED1B-AS1). CONCLUSIONS: Our prognostic cuproptosis-related lncRNA signature was accurate and effective for predicting the prognosis of HCC. The immunotherapy was unsuitable for high-risk HCC patients with this signature. Elsevier 2023-08-29 /pmc/articles/PMC10558351/ /pubmed/37810122 http://dx.doi.org/10.1016/j.heliyon.2023.e19352 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Wu, Jingyi
Yao, Jianzuo
Jia, Shu
Yao, Xiaokun
Shao, Jingping
Cao, Weijuan
Ma, Shuwei
Yao, Xiaomin
Li, Hong
A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma
title A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma
title_full A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma
title_fullStr A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma
title_full_unstemmed A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma
title_short A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma
title_sort cuproptosis-related lncrna signature for predicting prognosis and immune response in hepatocellular carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558351/
https://www.ncbi.nlm.nih.gov/pubmed/37810122
http://dx.doi.org/10.1016/j.heliyon.2023.e19352
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