Bladder cancer is the most common tumor in the urinary system, with approximately 420,000 new cases and 160,000 deaths per year. The European Organization for Research and Treatment of Cancer (EOTRC) classifies non-muscular invasive bladder cancer (NMIBC) into low-risk, medium-risk and high-risk groups based on a comprehensive analysis of NMIBC pathological parameters and the risk of recurrence and progression to muscular invasive bladder cancer (MIBC). Traditional classification systems are based on pathologic grading, staging systems, and clinical prognosis. However, the pathological parameters of the tumor cannot fully reflect the "intrinsic characteristics" of bladder cancer, and tumors with a similar pathology exhibit different biological behaviors. Furthermore, although the traditional classification system cannot accurately predict the risk of recurrence or the progression of bladder cancer patients (BCs) individually, this method is widely used in clinical practice because of its convenient operation. With the development of sequencing and other technologies, the genetics-based molecular subtyping of bladder cancer has become increasingly studied. Compared with the traditional classification system, it provides more abundant tumor biological information and is expected to assist or even replace the traditional typing system in the future.

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.

Objectives: B7 family members were identified as co-stimulators or co-inhibitors of the immune response and played important roles in cancer immunotherapy; however, their dysregulation in gastric cancer is still unclear. Methods: Data were obtained from TCGA and GTEX database. B7 mutations, association with DNA methylation and affected proteins were analyzed in cBioportal. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Ontology (GO) project was studied by DAVID to find the downstream signaling pathway and important metabolic process, respectively. Protein-protein interaction network was analyzed in STRING and Cytoscape. A total of 160 paired specimens in tissue microarray from patients with gastric cancer were used to detect the expression levels of seven B7 family members via immunohistochemical analysis. Results: Bioinformatics studies revealed dysregulation of B7 members in gastric cancer. Gene and protein alteration were found in B7 family members. Furthermore, DNA methylation and gene alteration may be both involved in B7 member dysregulation in gastric cancer. Importantly, the high expression of B7-H6 is associated with good overall patient survival. B7 family members primarily affect the EGFR tyrosine kinase inhibitor resistance signaling pathway in gastric cancer and TP53 may be an important target of the family. The low expression of B7-1 and high expression of B7-H3 and B7-H7 were validated by IHC staining. Conclusions: Our results provide insight into B7 family member expression in gastric cancer and stress their importance in stomach tumorigenesis, which may be beneficial for designing future cancer treatments.

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