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Additional file 5: Figure S5.The distinct prognosis of significant driver gene mutations in SCLC. The univariable Cox regression model includes clinical characteristics and driver gene mutations (mutation rate ≥ 10%) in the East Asian (a) and Caucasian (b) cohorts. Several driver gene mutations (mutation rate ≥ 10%) were associated with a distinct prognosis between the East Asian (c) and Caucasian (d) cohorts.

Additional file 4: Figure S4. A Differences in CXCR3 pathway activation between patients with different immune cells’PD-L1 expression in the ICI cohort. B Differences in CXCR3 pathway activation between patients with different tumor cells’PD-L1 expression in the ICI cohort. C Differences in tumor stages in patients with different levels of CXCR3 pathway activation in the ICI cohort. D Differences in patients’ smoking history for different levels of CXCR3 pathway activation in the ICI cohort. E Kaplan-Meier survival curves for OS in CXCR3-high (n =202) and CXCR3-low (n =204) patients in TCGA BLCA cohort. F Differences in tumor stages in patients with different levels of CXCR3 pathway activation in the TCGA BLCA cohort. G Differences in CXCR3 pathway activation levels between patients with different tumor stages in ICI cohort. H Differences in CXCR3 pathway activation levels between patients with different tumor stages in TCGA BLCA cohort.

Additional file 5: Figure S5. Histogram showing that the ssGSEA score of the immune-related and lipid metabolism-related signaling pathways set was different in CXCR3-high and CXCR3-low patients from TCGA BLCA cohort (logFC < 0, p < 0.05). ES > 0 means that the corresponding pathway is significantly enriched in CXCR3-high patients, while ES

Additional file 6: Figure S6. Related to Additional file 5: Fig. S5; heatmap depicting the mean differences in drug sensitivity (GDSC database) between the top 20 mutated genes and the corresponding wild-type gene in the East Asian (a) and Caucasian (b) cohorts. The y-axis indicates different drugs in the GDSC database, and the x-axis of the heatmap indicates different mutation statuses of the top 20 mutated genes. Red indicates upregulation, while blue indicates downregulation.

Additional file 1: Figure S1. A–C Flow chart of the data processing of this study.

Additional file 13: Table S4. Related to Additional file 2: Fig. S2b. The results of the co-occurrence/mutual exclusivity of oncogenes/TSGs in the Caucasian cohort (significantly mutated driver genes).

Additional file 7: Figure S7. Related to Fig. 6a; heatmap depicting the mean differences in the contents of 22 immune cells between different clinical characteristics and mutation status in the East Asian (a) and Caucasian (b) cohorts. The y-axis indicates different immune cells calculated by the CIBERSORT algorithm, and the x-axis of the heatmap indicates clinical characteristics and mutation status. Red indicates upregulation, while blue indicates downregulation.

Additional file 6: Figure S6. Histogram showing that the ssGSEA score of the immune-related and lipid metabolism-related signaling pathways set was different in CXCR3-high and CXCR3-low patients from ICI cohort (logFC < 0, p < 0.05). ES > 0 means that the corresponding pathway is significantly enriched in CXCR3-high patients while ES < 0 means the opposite.

Additional file 9: Figure S9. Heatmap depicting the correlation rho between the proportion of immune cells and mutations in each DDR pathway and TMB in the East Asian (a) and Caucasian (b) cohorts.

Additional file 1. The Additional file 1 contains Figures S1 and S2, Tables S1 and S2. Figure S1 shows the mean unsigned error of the frequencies of the 20 amino acids between the pocket and overall structure. Figure S2 shows the ROC curve for the cross docking case. Table S1 shows the list of crystallographic additives. Table S2 shows the detailed docking scores of the cross docking case.

Additional file 8: Figure S8. Related to Fig. 6b; heatmap depicting the mean differences in the contents of immune-related gene mRNA expression between different clinical characteristics and mutation statuses in the East Asian (a) and Caucasian (b) cohorts. The y-axis indicates immune-related gene mRNA expression, and the x-axis of the heatmap indicates clinical characteristics and mutation status. Red indicates upregulation, while blue indicates downregulation.

Additional file 2: Figure S2. Related to Fig. 3c; heatmap showing mutually exclusive and co-occurring mutations in the East Asian (a) and Caucasian (b) cohorts.

Additional file 1.Supplementary Materials and Figures.

Additional file 4: Figure S4. Top 20 mutated drivers and alterations in several key biological pathways in SCLC. An overview of the top 20 mutated driver genes in the East Asian (a) and Caucasian (b) cohorts. c Significantly mutated genes in the key biological signaling pathways between the East Asian and Caucasian cohorts.

Additional file 2: Figure S2. Validation of relationship between CXCR3 pathway activation and efficacy of ICIs in cancer patients. A–F The differences in the proportions of mUC patients with different responses to ICIs between CXCR3-high and CXCR3-low patients in the other six ICI cohorts. Light blue color represents the responders; dark blue color represents the non-responders. G–L The differences in activation of the CXCR3 pathway in CXCR3-high and CXCR3-low patients from the other six ICI cohorts. NR no response, R response.

Additional file 3: Figure S3. Related to Fig. 4; the correlation between the ssGSEA scores of each DDR signaling pathway and TMB in the East Asian (a) and Caucasian (b) cohorts.

Additional file 3: Figure S3. A–F Receiver operating characteristic (ROC) curve for the predictive value of ssGSEA scores of CXCR3 pathway in the other six validation cohorts.