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Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma
by
Xiang, Shixin
, Li, Mingxing
, Li, Jing
, Cho, Chi Hin
, Yi, Tao
, Yang, Xiao
, Zheng, Yuan
, Du, Fukuan
, Wu, Xu
, Shen, Jing
, Kaboli, Parham Jabbarzadeh
, Xiao, Zhangang
, Zhao, Yueshui
, Wen, Qinglian
in
Algorithms
/ Bioinformatics
/ Biomarkers
/ Cancer therapies
/ ESTIMATE algorithm
/ Gene set enrichment analysis
/ Genes
/ Hepatocellular carcinoma
/ Immune response
/ Immunology
/ Immunomodulation
/ Immunotherapy
/ Infiltration
/ Liver cancer
/ Medical prognosis
/ Metabolism
/ Metastases
/ Metastasis
/ Mortality
/ Mutation
/ Patients
/ Prognosis
/ Regression analysis
/ Signal transduction
/ Survival analysis
/ TCGA
/ Transcriptomes
/ Tumor microenvironment
/ Tumorigenesis
/ Tumors
2021
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Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma
by
Xiang, Shixin
, Li, Mingxing
, Li, Jing
, Cho, Chi Hin
, Yi, Tao
, Yang, Xiao
, Zheng, Yuan
, Du, Fukuan
, Wu, Xu
, Shen, Jing
, Kaboli, Parham Jabbarzadeh
, Xiao, Zhangang
, Zhao, Yueshui
, Wen, Qinglian
in
Algorithms
/ Bioinformatics
/ Biomarkers
/ Cancer therapies
/ ESTIMATE algorithm
/ Gene set enrichment analysis
/ Genes
/ Hepatocellular carcinoma
/ Immune response
/ Immunology
/ Immunomodulation
/ Immunotherapy
/ Infiltration
/ Liver cancer
/ Medical prognosis
/ Metabolism
/ Metastases
/ Metastasis
/ Mortality
/ Mutation
/ Patients
/ Prognosis
/ Regression analysis
/ Signal transduction
/ Survival analysis
/ TCGA
/ Transcriptomes
/ Tumor microenvironment
/ Tumorigenesis
/ Tumors
2021
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Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma
by
Xiang, Shixin
, Li, Mingxing
, Li, Jing
, Cho, Chi Hin
, Yi, Tao
, Yang, Xiao
, Zheng, Yuan
, Du, Fukuan
, Wu, Xu
, Shen, Jing
, Kaboli, Parham Jabbarzadeh
, Xiao, Zhangang
, Zhao, Yueshui
, Wen, Qinglian
in
Algorithms
/ Bioinformatics
/ Biomarkers
/ Cancer therapies
/ ESTIMATE algorithm
/ Gene set enrichment analysis
/ Genes
/ Hepatocellular carcinoma
/ Immune response
/ Immunology
/ Immunomodulation
/ Immunotherapy
/ Infiltration
/ Liver cancer
/ Medical prognosis
/ Metabolism
/ Metastases
/ Metastasis
/ Mortality
/ Mutation
/ Patients
/ Prognosis
/ Regression analysis
/ Signal transduction
/ Survival analysis
/ TCGA
/ Transcriptomes
/ Tumor microenvironment
/ Tumorigenesis
/ Tumors
2021
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Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma
Journal Article
Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma
2021
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Overview
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.
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