Fig. 5

Role of the TTKPI in predicting immunotherapeutic benefits. a Association between risk score signature and immune checkpoint molecules. b Association between the 8 genes and immune checkpoint molecules. c Correlation among TIMP1, KIF11, and CTLA4 expression. Correlation among TIMP1, KIF11, and PD-L2 expression. d KM survival curve in the IMvigor210 group (urothelial cancer, n = 298). e Risk scores in groups with different anti-PD-L1 clinical response status in the IMvigor210 group. f Proportion of patients with response to PD-L1 blockade therapy in the high-risk and low-risk score groups in the IMvigor210 group. g KM survival curve in the GSE91061 (melanoma, n = 39). h Proportion of patients with response to PD-L1 blockade therapy in the high-risk and low-risk score groups in the GSE91061. i KM survival curve in the GSE135222 (NSCLC, n = 24). j Proportion of patients with response to PD-L1 blockade therapy in the high-risk and low-risk score groups in the GSE135222. Statistical analysis is performed with Pearson correlation analysis (a–c), Log-rank test (d, g, i), Student's t-test (e) and Fisher’s exact test (f, h, i). ns: no significance, **P < 0.01, ***P < 0.001. CR: complete remission, PR: partial response, SD: stable disease, PD: progressive disease, DCB: durable clinical benefit, NDB: non-durable benefit