Pan-cancer analysis of tumor mutation burden sensitive tumors reveals tumor-specific subtypes and hub genes related to immune infiltration.

Background: High tumor mutation burden (TMB) failed to serve as a favorable prognostic biomarker for immunotherapy across all tumors. This study aimed to explore TMB-sensitive tumors on a pan-cancer level and construct their immune infiltration phenotypes in TMB-high groups.

Methods: Pan-cancer patients were separated into TMB-high and TMB-low groups based on the median TMB values per tumor. TMB-related genes were identified using differently expressed genes (DEGs) and differently mutated genes (DMGs) between the above two TMB groups. CIBERSORT algorithm was used to estimate the abundance of 22 tumor immune infiltrating cells (TIICs). Consensus clustering analysis was applied to predict molecular subtypes. Cox regression analysis was performed to evaluate the correlations between hub genes and TIICs and immunomodulator genes.

Results: Nine TMB-sensitive tumors were identified by high-frequency of TMB-related genes. A total of 126 tumor-specific hub genes (1 in BLCA, 19 in BRCA, 4 in COAD, 4 in HNSC, 25 in LUAD, 2 in LUSC, 27 in SKCM, 37 in STAD, and 7 UCEC) were identified. In five out of nine TMB-sensitive tumors, the molecular subtypes based on hub gene expression were characterized by TMB values, prognostic values and tumor-specific TIICs levels. In TMB-high groups, hub genes associated immune infiltration phenotypes were constructed with key TIICs and immunomodulators spanning TMB-sensitive tumors.

Conclusions: Our tumor-specific analysis revealed hub genes associated immune infiltration features may serve as potential therapeutic targets and prognostic markers of immunotherapy, providing the potential underlying mechanism of immune infiltration in TMB-high groups across TMB-sensitive tumors.