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Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma

Background: Cellular senescence is a typical irreversible form of life stagnation, and recent studies have suggested that long non-coding ribonucleic acids (lncRNA) regulate the occurrence and development of various tumors. In the present study, we attempted to construct a novel signature for predic...

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Autores principales: Sun, Rui, Wang, Xu, Chen, Jiajie, Teng, Da, Chan, Shixin, Tu, Xucan, Wang, Zhenglin, Zuo, Xiaomin, Wei, Xiang, Lin, Li, Zhang, Qing, Zhang, Xiaomin, Tang, Kechao, Zhang, Huabing, Chen, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485671/
https://www.ncbi.nlm.nih.gov/pubmed/36147502
http://dx.doi.org/10.3389/fgene.2022.949110
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author Sun, Rui
Wang, Xu
Chen, Jiajie
Teng, Da
Chan, Shixin
Tu, Xucan
Wang, Zhenglin
Zuo, Xiaomin
Wei, Xiang
Lin, Li
Zhang, Qing
Zhang, Xiaomin
Tang, Kechao
Zhang, Huabing
Chen, Wei
author_facet Sun, Rui
Wang, Xu
Chen, Jiajie
Teng, Da
Chan, Shixin
Tu, Xucan
Wang, Zhenglin
Zuo, Xiaomin
Wei, Xiang
Lin, Li
Zhang, Qing
Zhang, Xiaomin
Tang, Kechao
Zhang, Huabing
Chen, Wei
author_sort Sun, Rui
collection PubMed
description Background: Cellular senescence is a typical irreversible form of life stagnation, and recent studies have suggested that long non-coding ribonucleic acids (lncRNA) regulate the occurrence and development of various tumors. In the present study, we attempted to construct a novel signature for predicting the survival of patients with hepatocellular carcinoma (HCC) and the associated immune landscape based on senescence-related (sr) lncRNAs. Method: Expression profiles of srlncRNAs in 424 patients with HCC were retrieved from The Cancer Genome Atlas database. Lasso and Cox regression analyses were performed to identify differentially expressed lncRNAs related to senescence. The prediction efficiency of the signature was checked using a receiver operating characteristic (ROC) curve, Kaplan–Meier analysis, Cox regression analyses, nomogram, and calibration. The risk groups of the gene set enrichment analysis, immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) were also analyzed. Quantitative real-time polymerase chain reaction (qPCR) was used to confirm the levels of AC026412.3, AL451069.3, and AL031985.3 in normal hepatic and HCC cell lines. Results: We identified 3 srlncRNAs (AC026412.3, AL451069.3, and AL031985.3) and constructed a new risk model. The results of the ROC curve and Kaplan–Meier analysis suggested that it was concordant with the prediction. Furthermore, a nomogram model was constructed to accurately predict patient prognosis. The risk score also correlated with immune cell infiltration status, immune checkpoint expression, and chemosensitivity. The results of qPCR revealed that AC026412.3 and AL451069.3 were significantly upregulated in hepatoma cell lines. Conclusion: The novel srlncRNA (AC026412.3, AL451069.3, and AL031985.3) signatures may provide insights into new therapies and prognosis predictions for patients with HCC.
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spelling pubmed-94856712022-09-21 Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma Sun, Rui Wang, Xu Chen, Jiajie Teng, Da Chan, Shixin Tu, Xucan Wang, Zhenglin Zuo, Xiaomin Wei, Xiang Lin, Li Zhang, Qing Zhang, Xiaomin Tang, Kechao Zhang, Huabing Chen, Wei Front Genet Genetics Background: Cellular senescence is a typical irreversible form of life stagnation, and recent studies have suggested that long non-coding ribonucleic acids (lncRNA) regulate the occurrence and development of various tumors. In the present study, we attempted to construct a novel signature for predicting the survival of patients with hepatocellular carcinoma (HCC) and the associated immune landscape based on senescence-related (sr) lncRNAs. Method: Expression profiles of srlncRNAs in 424 patients with HCC were retrieved from The Cancer Genome Atlas database. Lasso and Cox regression analyses were performed to identify differentially expressed lncRNAs related to senescence. The prediction efficiency of the signature was checked using a receiver operating characteristic (ROC) curve, Kaplan–Meier analysis, Cox regression analyses, nomogram, and calibration. The risk groups of the gene set enrichment analysis, immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) were also analyzed. Quantitative real-time polymerase chain reaction (qPCR) was used to confirm the levels of AC026412.3, AL451069.3, and AL031985.3 in normal hepatic and HCC cell lines. Results: We identified 3 srlncRNAs (AC026412.3, AL451069.3, and AL031985.3) and constructed a new risk model. The results of the ROC curve and Kaplan–Meier analysis suggested that it was concordant with the prediction. Furthermore, a nomogram model was constructed to accurately predict patient prognosis. The risk score also correlated with immune cell infiltration status, immune checkpoint expression, and chemosensitivity. The results of qPCR revealed that AC026412.3 and AL451069.3 were significantly upregulated in hepatoma cell lines. Conclusion: The novel srlncRNA (AC026412.3, AL451069.3, and AL031985.3) signatures may provide insights into new therapies and prognosis predictions for patients with HCC. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9485671/ /pubmed/36147502 http://dx.doi.org/10.3389/fgene.2022.949110 Text en Copyright © 2022 Sun, Wang, Chen, Teng, Chan, Tu, Wang, Zuo, Wei, Lin, Zhang, Zhang, Tang, Zhang and Chen. 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
Sun, Rui
Wang, Xu
Chen, Jiajie
Teng, Da
Chan, Shixin
Tu, Xucan
Wang, Zhenglin
Zuo, Xiaomin
Wei, Xiang
Lin, Li
Zhang, Qing
Zhang, Xiaomin
Tang, Kechao
Zhang, Huabing
Chen, Wei
Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma
title Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma
title_full Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma
title_fullStr Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma
title_full_unstemmed Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma
title_short Development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma
title_sort development and validation of a novel cellular senescence-related prognostic signature for predicting the survival and immune landscape in hepatocellular carcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485671/
https://www.ncbi.nlm.nih.gov/pubmed/36147502
http://dx.doi.org/10.3389/fgene.2022.949110
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