Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma

Abstract

Background Currently, the most predominant type of liver cancer is hepatocellular carcinoma (HCC), which is also the fourth leading cause of cancer-related death in the global population. Pyroptosis is an emerging form of cell death that affects the prognosis of cancer patients by modulating tumor cell migration, proliferation and invasion. However, the evaluation of pyroptosis in the prognosis of HCC is still insufficient. Methods A total of 365 HCC patients from the TCGA-LIHC cohort were classified into two distinct subtypes using consensus clustering of pyroptosis-related genes (PRGs). Following univariate Cox analysis of differentially expressed genes between subtypes, we established a prognostic model (PRGs-score, PRGS) by LASSO Cox analysis. We further tested the predictive power of the prognostic model in the ICGC (LIRI-JP) and GEO (GSE14520) cohorts. The tumor microenvironment (TME) was studied using the CIBERSORT. The enrichment scores for immune cells and immune functions in low- and high-PRGS groups were assessed using ssGSEA. The IMvigor210 cohort was used to investigate the immunotherapy efficacy. Furthermore, we validated the expression of prognostic genes in PRGS by RT-qPCR in vitro. Results The subtyping of HCC based on PRGs exhibited distinct clinical characteristics. We developed a prognostic model PRGS by differentially expressed genes between different subtypes. The results showed that PRGS could well forecast the survival of HCC patients in different cohorts and was associated with the immune microenvironment. Moreover, PRGS was considered to be an independent prognostic risk factor and superior to other pyroptosis-related signatures. Low-PRGS implied greater immune cell infiltration and better overall survival with immunotherapy. The results of RT-qPCR also showed that prognostic genes were significantly dysregulated in HCC. Conclusions PRGS has promising application in forecasting the prognosis of HCC patients, and its relationship with the immune microenvironment provides a basis for the subsequent treatment and research of HCC.

GIMAP8 is a promising prognostic biomarker correlated with immune infiltration in lung adenocarcinoma

“…To predict the sensitivity of H-GG and L-GG to LUAD immunotherapy, we obtained immunophenotype score (IPS) data for LUAD from The Cancer Immunome Atlas (TCIA; https://tcia.at/). IPS is a measure of the immunogenicity of an individual solid tumor, with a higher score representing a better response to immunotherapy [11]. IPSs of CTLA-4 and PD-1 blockers were used to predict the immunotherapy e cacy of the patient's response to anti-CTLA-4 and anti-PD-1 antibodies.…”