It is crucial to grasp the characteristics of tumour immune microenvironment to improve effects of immunotherapy. In this study, the immune and stromal scores of 371 cases were calculated for quantitative analysis of immune and stromal cell infiltration in the tumour microenvironment of hepatocellular carcinoma (HCC). The weighted gene co-expression network analysis and protein-protein interaction network were analysed to identify immune microenvironment-related genes. The results showed that patients with high immune scores had a higher 4-year recurrence-free rate. TP53, CTNNB1, and AXIN1 mutations significantly varied with immune scores. In immune score-related modules analysis, Kyoto encyclopaedia of genes and genomes pathways and gene ontology terms were closely related to immune processes, tumorigenesis, and metastasis. Twelve new immune microenvironment-related genes were identified and had significantly positive correlations with seven immune checkpoint genes. In prognostic analysis, eleven immune microenvironmentrelated genes exhibited high expression, nine of which were validated in the GSE62232 dataset and were significantly associated with a good prognosis. Our findings suggest that calculating immune score and stromal score could help to determine tumour purity and immune cell infiltration in the tumour microenvironment. Nine immune microenvironment-related genes identified in this study had potential as prognostic markers for HCC.

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Background: Gastric cancer is a common lethal cancer worldwide. We aimed to develop a reliable, individualized, immune-related prognostic signature that can be used to stratify and estimate prognosis in patients with gastric cancer. Methods: This retrospective study analyzed the gene expression profiles of gastric cancer with tumor tissue samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, which included 676 cases in total. Immune genes from the InnateDB database were selected to develop and validate an immune-related prognostic model for gastric cancer patients. Results: An immune-related gene pair (IRGP) model was constructed that enabled us to stratify patients into high- and low-risk immune risk groups in the training set. Patients with a low risk score had a significantly longer median survival time than those with a high risk score. Further, we compared the predictive accuracy of the IRGP model with clinical characteristics, including TNM, grade, age, and stage. The results showed that the model had the highest mean C-index (0.69) compared with grade (0.55) or stage (0.60) in survival prediction. Then, we constructed a nomogram that integrated the IRGP model with independent clinical characteristics, which showed the best prognostic accuracy compared with other signatures. Conclusion: A clinical-immune signature based on IRGP is a promising prognostic biomarker in gastric cancer. Prospective studies are needed to further validate its accuracy and to test its clinical utility in individualized treatment.