CSMD3 mutation

Spatial transcriptomics revealed topological profiles of the tumor microenvironment, identifying dominant but tumor-excluded inflammatory signals in immune-hot cases and immune foci even in otherwise immune-cold cases. In conclusion, spatial transcriptomics reveal the tumor immune landscape of angiosarcoma, and in combination with multi-omic information, may improve implementation of treatment strategies.

Distribution of mutated genes among Group III patients differed according to the existence of EZH2 mutation, with high frequency of mutated USH2A (p=0.019) and MGAM (p=0.019) genes in those with EZH2 mutation, whereas mutations in TP53 were observed only in those without (p=0.072).[Conclusion] Methylation-score could be helpful in distinguishing patients with and without EZH2 mutations and enables clinicians to identify candidates for EZH2 inhibition medications. Combination of EZH2- and Methylation-scores predicts clinical outcomes after the 1st immunochemotherapy, which also could potentially identify genetically distinct population in the heterogeneous FL cohort.

Next, the P-TMB calculated from genes in these pathways was significantly related to patient response with prediction AUC 0.74-0.82 in all collected datasets. In conclusion, our work provides new insights into the application of TMB in predicting patient response, which will benefit to immunotherapy research.

Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies.

RB1 and CSMD3 mutations had small p-value (p < 0.1) in both chi-squared tests and survival analysis. The drug sensitivity analysis of key mutation showed when RB1 mutation occurs, the efficacy of six anti-tumour drugs has changed significantly (p < 0.05).

Gene set enrichment analysis (GSEA) and CIBERSORT analysis indicated that OC samples with CSMD3 mutations had significant involvement of pathways related to the immune response. In summary, we found that CSMD3 mutation is highly correlated with increased TMB and poor clinical prognosis and that it might function as a biomarker for predicting prognosis and choosing an immunotherapy regimen.