Additional file 9 of Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer

Additional file 9: Table S1. Basic characteristics of datasets enrolled in this study for identifying pyroptosis-associated genes (PYAGs) signatures. Table S2. Demographic and clinical characteristics of 1334 ovarian cancer patients from TCGA-OV and  five GEO cohorts. Table S3. Summary of 51 recognized  PYAGs. Table S4. Summary of DNA methylation modifications of 51  PYAGs with DiseaseMeth 2.0. Table S5. The prognostic values of 49 PYAGs in OC patients of TCGA-OV and  five GEO cohorts. Table S6. Spearman correlation analysis of the 49  PYAGs in OC. Table S7. The activation states of biological pathways in distinct pyroptosis-associated clusters (PACs) by GSVA enrichment analysis. Table S8. The TME score and tumor purity of OC samples were analyzed with ESTIMATETable S9. Functional annotation of the differentially expressed genes（DEGs） between the two PACs.. Table S9. Functional annotation of the differentially expressed genes（DEGs） between the two PACs.Table S9. Functional annotation of the differentially expressed genes（DEGs） between the two PACs. Table S9. Functional annotation of the differentially expressed genes（DEGs） between the two PACs. Table S10. Prognostic analysis of 889 DEGs using a univariate Cox analysis. Table S11. Distribution of PYAG scores in the different pyroptosis subtypes (Kruskal-Wallis H test, P<0.01).  Table S12. Relationships between the expressions of CD8, GSDMD, GZMB and clinicopathological parameters of 65 ovarian cancer patients. Table S13. Correlation between Pyrsig score and expressions of GSDMD, GZMB in 65 ovarian cancer patients.