A New Risk Score Based on Eight Hepatocellular Carcinoma- Immune Gene Expression Can Predict the Prognosis of the Patients

Abstract

BackgroundHepatocellular carcinoma (HCC) is one of the malignant tumors with high morbidity and mortality worldwide. Immunotherapy has emerged as an increasingly important cancer treatment modality. However, the potential relationship between immune genes and HCC still needs to be explored. The purpose of this study is to construct a new prognostic risk signature to predict the prognosis of HCC patients based on the expression of immune-related genes (IRGs) and explore its potential mechanism.MethodsWe analyzed the gene expression data of 332 HCC patient samples and 46 adjacent normal tissues samples (Solid Tissue Normal including cirrhotic tissue) in The Cancer Genome Atlas (TCGA) database and clinical characteristics. We analyzed the gene expression data, identified differentially expressed IRGs in HCC tissues, filtered IRGs with prognostic value to construct an IRG signature, and classified patients into high and low gene expression groups based on the expression of IRGs in their tumor tissues. We also investigated the potential molecular mechanisms of IRGs through a bioinformatics approach using Protein-Protein Interaction (PPI) network, Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis and Gene Ontology (GO) database analysis. Differentially expressed IRGs associated with significant clinical outcomes (SIRGs) were identified by univariate Cox regression analysis. An immune-related risk score model (IRRSM) was established based on Lasso Cox regression analysis and multivariate Cox regression analysis. Based on the IRRSM, the immune score of the patients was calculated, and the patients were divided into high-risk and low-risk patients according to the median score, and the differences in survival between the two groups were compared. Then, the correlation analysis between the IRRSM and clinical characteristics was performed, and the IRRSM was validated using the International Cancer Genome Consortium (ICGC) database.ResultsThe IRRSM was eventually constructed and confirmed to be an independent prognostic model for HCC patients. The IRRSM was shown to be positively correlated with the infiltration of four types of immune cells.ConclusionOur results showed that some SIRGs have potential value for predicting the prognosis and clinical outcomes of HCC patients. IRGs affect the prognosis of HCC patients by regulating the tumor immune microenvironment (TIME). This study provides a new insight for immune research and treatment strategies in HCC patients.

Identification of a glycolysis-related gene signature for predicting prognosis in patients with hepatocellular carcinoma

“…Compared to these gene signatures, our gene signature had the following features: first, our gene signature was established based on five GRGs that were independently associated with HCC prognosis. Considering the vital role of glycolysis in tumor development and progression, our gene signature is surely to have a better predictive performance than the previous predictive models [ 58 – 61 ]; second, some of the previous gene signatures lacked external validation using other datasets [ 60 ], consequently, we used the ICGC-LIRI—JP as an external validation cohort to verify the results of this study, which showed that the gene signature had good predictive performance.…”

“…Many gene signatures have been constructed to predict HCC patient survival [ 58 – 61 ]. Compared to these gene signatures, our gene signature had the following features: first, our gene signature was established based on five GRGs that were independently associated with HCC prognosis.…”

Decoding Immune Signature to Detect the Risk for Early-Stage HCC Recurrence

“…They identified nine lnRNAs closely related to disease-free survival which could be validated as potential biomarkers to predict HCC recurrence [126]. Similarly, Ye et al compared gene expression data of HCC patients and normal tissue samples and selected differentially expressed immune related genes in HCC samples, and constructed an immune-related gene signature based on eight genes such as CHGA, RAETIE, FGF9, GIP, NROB1, IL20RA, ESRRG, and GNNRH2 to predict the HCC prognosis [127]. Another research team designed 15 immune-related gene signatures as a prognostic model for an HCC-based TGCA dataset using Cox regression analysis [128].…”