A novel risk score based on immune-related genes for hepatocellular carcinoma as a reliable prognostic biomarker and correlated with immune infiltration

Abstract

BackgroundImmunological-related genes (IRGs) play a critical role in the immune microenvironment of tumors. Our study aimed to develop an IRG-based survival prediction model for hepatocellular carcinoma (HCC) patients and to investigate the impact of IRGs on the immune microenvironment.MethodsDifferentially expressed IRGs were obtained from The Genomic Data Commons Data Portal (TCGA) and the immunology database and analysis portal (ImmPort). The univariate Cox regression was used to identify the IRGs linked to overall survival (OS), and a Lasso-regularized Cox proportional hazard model was constructed. The International Cancer Genome Consortium (ICGC) database was used to verify the prediction model. ESTIMATE and CIBERSORT were used to estimate immune cell infiltration in the tumor immune microenvironment (TIME). RNA sequencing was performed on HCC tissue specimens to confirm mRNA expression.ResultsA total of 401 differentially expressed IRGs were identified, and 63 IRGs were found related to OS on the 237 up-regulated IRGs by univariate Cox regression analyses. Finally, five IRGs were selected by the LASSO Cox model, including SPP1, BIRC5, STC2, GLP1R, and RAET1E. This prognostic model demonstrated satisfactory predictive value in the ICGC dataset. The risk score was an independent predictive predictor for OS in HCC patients. Immune-related analysis showed that the immune infiltration level in the high-risk group was higher, suggesting that the 5-IRG signature may play an important role in mediating immune escape and immune resistance in the TIME of HCC. Finally, we confirmed the 5-IRG signature is highly expressed in 65 HCC patients with good predictive power.ConclusionWe established and verified a new prognosis model for HCC patients based on survival-related IRGs, and the signature could provide new insights into the prognosis of HCC.

Unleashing the potential of gene signatures as prognostic and predictive tools: A step closer to personalized medicine in hepatocellular carcinoma (HCC)

“…Of note, this IRG signature was able to distinguish high‐risk and low‐risk HCC patients with an AUC of 0.784, 0.720, and 0.697 at 1‐, 3‐, and 5‐year survival, respectively. Additionally, the study found that high‐risk patients had higher levels of Tregs, M0 macrophages, and resting DCs, while low‐risk patients had lower levels of CD8 + T cells, naive B cells, and activated DCs 61 …”

“…68 Studies have investigated various biomarkers that could impact the prognosis of HCC by regulating apoptosis-related genes. [59][60][61] To this end, a gene signature composed of apoptosis-related genes was examined for its prognostic value in HCC patients. Five differentially expressed apoptosis-related genes, including PPP2R5B, TOP2A, SQSTM1, LGALS3, and BMF, were identified as having prognostic value based on mRNA sequence data from 50 normal tissues and 374 HCC tissues.…”

“…Additionally, the study found that high-risk patients had higher levels of Tregs, M0 macrophages, and resting DCs, while low-risk patients had lower levels of CD8 + T cells, naive B cells, and activated DCs. 61 The role of IRGs in HCC pathogenesis was assessed in another study. Notably, TP53 exhibited the highest rate of mutations among various genes in HCC cases.…”

Identification of oncogenes and tumor-suppressor genes with hepatocellular carcinoma: A comprehensive analysis based on TCGA and GEO datasets

“…There is an urgent need to find new targets for the diagnosis and treatment of liver cancer in the direction of a breakthrough in the current treatment limitations. Some previous studies used TCGA and GEO databases to screen oncogenes and identify prognostic or immune-related genes ( Chen et al, 2020 ; Gao et al, 2021 ; Yan et al, 2021 ; Shen et al, 2022a ; Shen et al, 2022b ; Ding et al, 2022 ; Gao et al, 2022 ; Long et al, 2022 ; Yang et al, 2022 ). However, in this study, four GSE datasets, GSE36376, GSE102079, GSE54236, and GSE45267, were summarized for analysis, hoping to find the mechanism of cancer-promoting and tumor-suppressor factors in liver cancer from the perspective of improving the accuracy of the research results.…”

“…Currently, public data and bioinformatic analysis methods have provided us with invaluable resources to find HCC-related oncogenes and tumor-suppressor genes. Some studies searched cancer-related target genes through public databases, whether prognostic oncogene identification ( Gao et al, 2021 ; Yan et al, 2021 ; Shen et al, 2022a ; Gao et al, 2022 ), single-gene research studies ( Ding et al, 2022 ; Yang et al, 2022 ), or immune-related oncogenes ( Chen et al, 2020 ; Shen et al, 2022b ; Long et al, 2022 ), all of which provided a strong basis for targeted therapy and precise treatment of liver cancer. However, many studies only consider the differential expression of oncogenes in tumors, ignoring the important role and potential association of tumor-suppressor genes.…”