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Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma
BACKGROUND: Hepatocellular carcinoma (HCC) as a common tumor has a poor prognosis. Recently, a combination of atezolizumab and bevacizumab has been recommended as the preferred regimen for advanced HCC. However, the overall response rate of this therapy is low. There is an urgent need to identify se...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354375/ https://www.ncbi.nlm.nih.gov/pubmed/35932027 http://dx.doi.org/10.1186/s12957-022-02681-4 |
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author | Qian, Baifeng Lin, Haozhong Lan, Tian Li, Muqi Wu, Xiwen Lin, Shuirong Song, Zimin Shen, Shunli Peng, Baogang |
author_facet | Qian, Baifeng Lin, Haozhong Lan, Tian Li, Muqi Wu, Xiwen Lin, Shuirong Song, Zimin Shen, Shunli Peng, Baogang |
author_sort | Qian, Baifeng |
collection | PubMed |
description | BACKGROUND: Hepatocellular carcinoma (HCC) as a common tumor has a poor prognosis. Recently, a combination of atezolizumab and bevacizumab has been recommended as the preferred regimen for advanced HCC. However, the overall response rate of this therapy is low. There is an urgent need to identify sensitive individuals for this precise therapy among HCC patients. METHODS: The Wilcox test was used to screen the differentially expressed immune-related genes by combining the TCGA cohort and the Immunology Database. Univariate and multivariate Cox regression analysis were used to screen the immune gene pairs concerning prognosis. A predictive model was constructed using LASSO Cox regression analysis, and correlation analysis was conducted between the signature and clinical characteristics. ICGC cohort and GSE14520 were applied for external validations of the predictive risk model. The relationship between immune cell infiltration, TMB, MSI, therapeutic sensitivity of immune checkpoint inhibitors, targeted drugs, and the risk model were assessed by bioinformatics analysis in HCC patients. RESULTS: A risk predictive model consisting of 3 immune-related gene pairs was constructed and the risk score was proved as an independent prognostic factor for HCC patients combining the TCGA cohort. This predictive model exhibited a positive correlation with tumor size (p < 0.01) and tumor stage (TNM) (p < 0.001) in the chi-square test. The predictive power was verified by external validations (ICGC and GSE14520). The risk score clearly correlated with immune cell infiltration, MSI, immune checkpoints, and markers of angiogenesis. CONCLUSIONS: Our research established a risk predictive model based on 3 immune-related gene pairs and explored its relationship with immune characteristics, which might help to assess the prognosis and treatment sensitivity to immune and targeted therapy of HCC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-022-02681-4. |
format | Online Article Text |
id | pubmed-9354375 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93543752022-08-06 Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma Qian, Baifeng Lin, Haozhong Lan, Tian Li, Muqi Wu, Xiwen Lin, Shuirong Song, Zimin Shen, Shunli Peng, Baogang World J Surg Oncol Research BACKGROUND: Hepatocellular carcinoma (HCC) as a common tumor has a poor prognosis. Recently, a combination of atezolizumab and bevacizumab has been recommended as the preferred regimen for advanced HCC. However, the overall response rate of this therapy is low. There is an urgent need to identify sensitive individuals for this precise therapy among HCC patients. METHODS: The Wilcox test was used to screen the differentially expressed immune-related genes by combining the TCGA cohort and the Immunology Database. Univariate and multivariate Cox regression analysis were used to screen the immune gene pairs concerning prognosis. A predictive model was constructed using LASSO Cox regression analysis, and correlation analysis was conducted between the signature and clinical characteristics. ICGC cohort and GSE14520 were applied for external validations of the predictive risk model. The relationship between immune cell infiltration, TMB, MSI, therapeutic sensitivity of immune checkpoint inhibitors, targeted drugs, and the risk model were assessed by bioinformatics analysis in HCC patients. RESULTS: A risk predictive model consisting of 3 immune-related gene pairs was constructed and the risk score was proved as an independent prognostic factor for HCC patients combining the TCGA cohort. This predictive model exhibited a positive correlation with tumor size (p < 0.01) and tumor stage (TNM) (p < 0.001) in the chi-square test. The predictive power was verified by external validations (ICGC and GSE14520). The risk score clearly correlated with immune cell infiltration, MSI, immune checkpoints, and markers of angiogenesis. CONCLUSIONS: Our research established a risk predictive model based on 3 immune-related gene pairs and explored its relationship with immune characteristics, which might help to assess the prognosis and treatment sensitivity to immune and targeted therapy of HCC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-022-02681-4. BioMed Central 2022-08-05 /pmc/articles/PMC9354375/ /pubmed/35932027 http://dx.doi.org/10.1186/s12957-022-02681-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Qian, Baifeng Lin, Haozhong Lan, Tian Li, Muqi Wu, Xiwen Lin, Shuirong Song, Zimin Shen, Shunli Peng, Baogang Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma |
title | Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma |
title_full | Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma |
title_fullStr | Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma |
title_full_unstemmed | Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma |
title_short | Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma |
title_sort | risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354375/ https://www.ncbi.nlm.nih.gov/pubmed/35932027 http://dx.doi.org/10.1186/s12957-022-02681-4 |
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