ImmuneScore of eight-gene signature predicts prognosis and survival in patients with endometrial cancer

Pan-cancer analysis reveals correlation between RAB3B expression and tumor heterogeneity, immune microenvironment, and prognosis in multiple cancers

RAB3B is essential for the transportation and secretion within cells. Its increased expression is linked to the development and progression of various malignancies. However, understanding of RAB3B's involvement in carcinogenesis is mostly limited to specific cancer subtypes. Hence, exploring RAB3B's regulatory roles and molecular mechanisms through comprehensive cancer datasets might offer innovative approaches for managing clinical cancer. To examine the potential involvement of RAB3B in the development of cancer, we analyzed data from various sources including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), cBioPortal, HPA, UALCAN, and tissue microarray (TAM). Using bioinformatics techniques, we examined the correlation between RAB3B expression and prognosis, tumor heterogeneity, methylation modifications, and immune microenvironment across different cancer types. Our findings indicate that elevated RAB3B expression can independently predict prognosis in many tumors and has moderate accuracy for diagnosing most cancers. In most cancer types, we identified RAB3B mutations that showed a significant correlation with tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and microsatellite instability (MSI). Abnormal DNA methylation patterns were also observed in most cancers compared to normal tissues. Additionally, we found significant correlations between RAB3B expression, immune cell infiltration, and immune scores across various cancers. Through pan-cancer analysis, we observed significant differences in RAB3B expression levels between tumors and normal tissues, making it a potential primary factor for cancer diagnosis and prognosis. The IHC results revealed that the expression of RAB3B in six types of tumors was consistent with the results of the pan-cancer analysis of the database. Furthermore, RAB3B showed potential associations with tumor heterogeneity and immunity. Thus, RAB3B can be utilized as an auxiliary diagnostic marker for early tumor detection and a prognostic biomarker for various tumor types.

Exploration of the prognostic effect of costimulatory genes in bladder cancer

BACKGROUND

A prognostic model of bladder cancer was constructed based on costimulatory molecules, and its stability and accuracy were verified in different datasets.

METHOD

The expression profile of bladder cancer RNA and the corresponding clinical data in The Cancer Genome Atlas (TCGA) database were analyzed employing computational biology, and a prognostic model was constructed for costimulating molecule-related genes. The model was applied in GSE160693, GSE176307, Xiangya_Cohort, GSE13507, GSE19423, GSE31684, GSE32894, GSE48075, GSE69795 and GSE70691 in TCGA dataset and Gene Expression Omnibus database. The role of costimulating molecules in bladder cancer tumor subtypes was also explored. By consistent cluster analysis, bladder cancer in the TCGA dataset was categorized into two subtypes: C1 and C2. The C1 subtype exhibited a poor prognosis, high levels of immune cell infiltration and significant enrichment of natural killer cells, T cells and dendritic cells in the C1 subtype. In addition, the ImmuneScore calculated by the ESTIMATE algorithm differed greatly between the two subtypes, and the ImmuneScore of the C1 subtype was greater than the C2 subtype in a significant manner.

RESULTS

This study also assessed the relationship between costimulating molecules and immunotherapy response. The high-risk group responded poorly to immunotherapy, with significant differences in the amount of most immune cells between the two groups. Further, three indices of the ESTIMATE algorithm and 22 immune cells of the CIBERSORT algorithm were significantly correlated with risk values. These findings suggest the potential value of costimulating molecules in predicting immunotherapy response.

CONCLUSION

A costimulatory molecule-based prognostic model for bladder cancer was established and validated across multiple datasets. This model introduces a novel mode for tailoring treatments to each individual with bladder cancer, and offers valuable insights for informed clinical choices. Simultaneously, this research also delved into the significance of costimulating molecules within distinct bladder cancer subtypes, shedding novel insights into improving immunotherapy strategies for the treatment of bladder cancer.