1. Additional file 1 of A tumor microenvironment-based prognostic index for osteosarcoma
- Author
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Wu, Changwu, Gong, Siming, Duan, Yingjuan, Deng, Chao, Kallendrusch, Sonja, Berninghausen, Laura, Osterhoff, Georg, and Schopow, Nikolas
- Abstract
Additional file 1: Table S1. Clinical characteristics of patients with osteosarcoma in each dataset. Table S5. Univariate and multivariate Cox regression analysis of overall survival, relapse free survival and metastasis free survival in each data set. Figure S1. The flow diagram of this study. Figure S2. ImmuneScore and StromalScore associate with clinical features and outcomes. Figure S3. Analysis of network topology for various soft-thresholding powers. Figure S4. OS prediction value of 4 genes in the TMEindex. Figure S5. RFS prediction value of 4 genes in the TMEindex. Figure S6. Differences in survival time and TMEindex genes expression between high and low TMEindex groups. Figure S7. Stratified analysis to further determine the prognostic value of the TMEindex based on the clinical characteristics of patients. Figure S8. Progonsis prediction value of the TMEindex in osteoblastic and chondroblastic osteosarcoma in the GSE21257 cohort. Figure S9. Validation of the prognostic value of the TMEindex in GSE33382. Figure S10. GSEA enrichment plots base on KEGG gene set showing the relatively enriched pathways in TMEindex-high (A) and TMEindex-low (B) group. Figure S11. GO enrichment and KEGG pathway analysis of DEGs identified between high and low TMEindex groups. Figure S12. Pan-cancer analysis of the prognostic predictive value of TMEindex. Figure S13. Univariate Cox regression analysis reveals the association of TMEindex with the PFS of 32 tumor types.
- Published
- 2023
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