Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma
Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognosti...
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Frontiers Media S.A.
2021-04-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2021.653836/full |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shixin Xiang Shixin Xiang Jing Li Jing Shen Jing Shen Yueshui Zhao Yueshui Zhao Xu Wu Xu Wu Mingxing Li Mingxing Li Xiao Yang Parham Jabbarzadeh Kaboli Parham Jabbarzadeh Kaboli Fukuan Du Fukuan Du Yuan Zheng Qinglian Wen Chi Hin Cho Chi Hin Cho Chi Hin Cho Tao Yi Zhangang Xiao Zhangang Xiao |
spellingShingle |
Shixin Xiang Shixin Xiang Jing Li Jing Shen Jing Shen Yueshui Zhao Yueshui Zhao Xu Wu Xu Wu Mingxing Li Mingxing Li Xiao Yang Parham Jabbarzadeh Kaboli Parham Jabbarzadeh Kaboli Fukuan Du Fukuan Du Yuan Zheng Qinglian Wen Chi Hin Cho Chi Hin Cho Chi Hin Cho Tao Yi Zhangang Xiao Zhangang Xiao Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma Frontiers in Immunology tumor microenvironment Hepatocellular carcinoma TCGA ESTIMATE algorithm Prognosis |
author_facet |
Shixin Xiang Shixin Xiang Jing Li Jing Shen Jing Shen Yueshui Zhao Yueshui Zhao Xu Wu Xu Wu Mingxing Li Mingxing Li Xiao Yang Parham Jabbarzadeh Kaboli Parham Jabbarzadeh Kaboli Fukuan Du Fukuan Du Yuan Zheng Qinglian Wen Chi Hin Cho Chi Hin Cho Chi Hin Cho Tao Yi Zhangang Xiao Zhangang Xiao |
author_sort |
Shixin Xiang |
title |
Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma |
title_short |
Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma |
title_full |
Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma |
title_fullStr |
Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma |
title_full_unstemmed |
Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma |
title_sort |
identification of prognostic genes in the tumor microenvironment of hepatocellular carcinoma |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Immunology |
issn |
1664-3224 |
publishDate |
2021-04-01 |
description |
Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes. |
topic |
tumor microenvironment Hepatocellular carcinoma TCGA ESTIMATE algorithm Prognosis |
url |
https://www.frontiersin.org/articles/10.3389/fimmu.2021.653836/full |
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doaj-dd696fee1d2d4bc0922dba1fcc05097b2021-04-07T13:22:49ZengFrontiers Media S.A.Frontiers in Immunology1664-32242021-04-011210.3389/fimmu.2021.653836653836Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular CarcinomaShixin Xiang0Shixin Xiang1Jing Li2Jing Shen3Jing Shen4Yueshui Zhao5Yueshui Zhao6Xu Wu7Xu Wu8Mingxing Li9Mingxing Li10Xiao Yang11Parham Jabbarzadeh Kaboli12Parham Jabbarzadeh Kaboli13Fukuan Du14Fukuan Du15Yuan Zheng16Qinglian Wen17Chi Hin Cho18Chi Hin Cho19Chi Hin Cho20Tao Yi21Zhangang Xiao22Zhangang Xiao23Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaDepartment of Oncology and Hematology, Hospital (T.C.M) Affiliated to Southwest Medical University, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaNeijiang Health and Health Vocational College, Neijiang, ChinaDepartment of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaSouth Sichuan Institute of Translational Medicine, Luzhou, ChinaFaculty of Medicine, School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, ChinaSchool of Chinese Medicine, Hong Kong Baptist University, Hong Kong, ChinaLaboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, ChinaDepartment of Pharmacy, The Affiliated Hospital of Southwest Medical University, Luzhou, ChinaBackground: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.https://www.frontiersin.org/articles/10.3389/fimmu.2021.653836/fulltumor microenvironmentHepatocellular carcinomaTCGAESTIMATE algorithmPrognosis |