CXCR3 Pathway Score Can Be Used as a Predictor of Response to Immunotherapy in mUC Patients.
To explore the effect of CXCR3 pathway activation on response to immunotherapy in mUC patients, we selected clinical variables related to ICI treatment and CXCR3 pathway score and performed univariate Cox regression analysis (Fig. 1A). Simultaneously, after eliminating the influence of multicollinearity factors, variables with statistical and clinical significance and P < 0.05 were analyzed by multivariate COX regression analysis. The multivariate Cox regression analysis found that the CXCR3 score (HR = 0.731(95%CI 0.560–0.902), p = 0.004) was independent of TNB (HR = 0.833 (95% CI 0.5740–1.092), p = 0.154), TMB (HR = 0.993 (95% CI 0.949–1.036), p = 0.717) and smoking (HR = 0.820 (95% CI 0.475–1.164), p = 0.195) and was a predictor of prognosis for mUC patients with ICI therapy (Fig. 1B). This indicated that greater CXCR3 pathway activation predicted a better response to immunotherapy in mUC patients.
To evaluate whether CXCR3 pathway activation can predict the prognosis of mUC patients and the efficacy of ICI treatment, we divided the patients into responders (complete or partial response, CR or PR) and non-responders (stable or progressive disease, SD or PD) according to their response to treatment. The responders had higer CXCR3 pathway activation levels than the non-responders (Wilcoxon test, p < 0.001, Fig. 1D). According to the median value of CXCR3 pathway ssGSEA scores, we grouped the patients into CXCR3-high and CXCR3-low groups, which represent the high and low activation level of CXCR3 pathway. The results showed there were more ICI responders in the CXCR3-high group than in the CXCR3-low group (two-tailed Fisher's exact test, p = 0.0042, Fig. 1C). We then performed survival analysis on the ICI cohort and found that patients with high CXCR3 pathway activation levels had better prognosis than those with low CXCR3 pathway activation levels (log-rank test, HR 0.56 [95% CI: 0.42–0.75], p = 1e-04, Fig. 1E). A similar survival analysis was performed on the TCGA-BLCA cohort, and the survival trend was similar to that for the ICI cohort but did not reach statistical significance (log-rank test, HR 0.85 [95% CI: 0.63–1.14], p = 0.281, Supplementary Fig. 4D). These results may demonstrate that the predictive capacity of CXCR3 pathway activation is more reliable for mUC patients treated with ICI therapy.
Analysis of Gene Mutations and Clinical Features
To explore the potential mechanism for how CXCR3 pathway activation impacts the efficacy of ICIs, we investigated the relationship between CXCR3 pathway activation and genomic alterations in mUC patients (Fig. 2). The gene mutation landscape showed the alteration types and frequencies of the top 20 driver genes in the ICI and TCGA cohorts. We observed a total of eight genes with significant differences in mutation frequencies between CXCR3-high and CXCR3-low patients, which were TP53 (61% vs 37%, p < 0.05), FGFR3 (11% vs 29%, p < 0.05), MDM2 (4% vs 12%, p < 0.05) 0.05), and FBXW7 (9% vs 1%, p < 0.05) in the ICI cohort; and TP53 (48% vs 36%, p < 0.05) 0.05), EP300 (17% vs 9%, p < 0.05), FGFR3 (6% vs 21%, p < 0.05), RB1 (17% vs 8%, p < 0.05), KMT2A (14% vs 6%, p < 0.05) p < 0.05), and CREBPP (13% vs 6%, p < 0.05) in the TCGA BLCA cohort. Detailed results for gene mutation frequency are shown in Supplementary Table 1.
We also compared differences in clinical variables among patients with different levels of CXCR3 pathway activation. We noticed that patients in the two cohorts with higher levels of CXCR3 pathway activation had higher tumor neoantigen burdens (Fig. 2A, B, p < 0.05). We also found statistically significant differences in the expression of PDL-1 in tumor cells (TC) and immune cells (IC) between groups with different CXCR3 pathway activation levels (Kruskal–Wallis test, p < 0.001, Supplementary Fig. 4A, B). TC and IC represent the expression of PD-L1 of tumor cells and immune cells (TC0/IC0 indicates PD-L1 level < 1%, TC1/IC1 indicates PD-L1 level 1–5%, and TC2+/IC2 + indicates PD-L1 level > 5%). Smoking has previously been reported to affect the prognosis of bladder cancer patients , but there were no differences of CXCR3 pathway activation between the different smoking status groups (Wilcoxon test, p = 0.57, Supplementary Fig. 4C). Interestingly, in the TCGA-BLCA cohort, ethnicity was significantly different between the CXCR3-high and CXCR3-low groups.
Analysis of Immune Microenvironment
To compare differences in the immune microenvironment for different CXCR3 pathway activation levels, we analyzed immune-related genes, immune cell infiltrations, and immunogenicity of patients with different CXCR3 pathway activation levels. Immunotherapy targets immune checkpoints, and therefore, expression of immune checkpoint genes is important for response to ICIs. In the ICI and TCGA cohorts, we found that expression of LAG3, PDCD1, and PD-L1 (CD274) was significantly elevated in the CXCR3-high patients; however, Vascular Endothelial Growth Factor A (VEGFA), a molecule that promotes tumor angiogenesis, was significantly downregulated in CXCR3-high patients (all p < 0.05; Fig. 3A). Other immune-related genes, such as cytotoxicity markers (GZMB) and cytokine-related genes (e.g. IFNG), were significantly upregulated in the CXCR3-high group (all p < 0.05). Infiltration of effector immune cells, such as CD8 + and CD4 + T cells and M1 macrophages, was higher in the CXCR3-high group (Fig. 3B, C), whereas Tregs and activated dendritic cell infiltration were higher in the CXCR3-low group. Further correlation analysis indicated that CD8 + T cell infiltration was positively correlated with CXCR3 pathway activation (ICI cohort: p < 0.001, r = 0.36; TCGA cohort: p < 0.001, r = 0.29, Fig. 3D, F), but Tregs infiltration was negatively correlated with CXCR3 pathway activation (ICI cohort: p < 0.001, r=-0.23; TCGA cohort: p < 0.001, r=-0.3, Fig. 3E, G).
Gene Set Enrichment Analysis (GSEA) was used to detect crosstalk between the CXCR3 pathway and other signaling pathways to influence the tumor microenvironment. We discovered that immune activation related pathways (such as adaptive immune response, T cell activation, and antigen processing and presentation) were significantly enriched in the CXCR3-high patients, while lipid metabolism and glucose metabolism signaling pathways were enriched in CXCR3-low patients (Supplementary Fig. 5, 6).
To elucidate the effect of the CXCR3 pathway on tumor immunogenicity, we compared differences in TNB, TMB, and DDR-related pathway mutation status between the CXCR3-high and CXCR3-low groups. For both the ICI and TCGA cohorts, the TMB was higher in CXCR3-high patients than in CXCR3-low patients, but this difference was only statistically significant for the TCGA cohort (ICI cohort: p > 0.05, TCGA cohort: p < 0.05, Fig. 4A, D). Similarly, in the ICI cohort, the mutation counts of the DDR-related pathways was significantly higher in CXCR3-high group. The TCGA-cohort showed the same trend but without statistical significance (ICI cohort: p < 0.05, TCGA cohort: p > 0.05, Fig. 4C, F). In both cohorts, TNB was elevated in CXCR3-high patients compared to CXCR3-low patients (ICI cohort: p < 0.001, TCGA cohort: p < 0.0001, Fig. 4B, E). The subsequent correlation analysis of TMB, TNB and CXCR3 pathway activation in the ICI cohort showed that both TMB and TNB were positively correlated with CXCR3 score (ICI cohort: p = 0.112, rSpearman = 0.1; p = 9.19e-04, rSpearman = 0.22; Fig. 4H,I). The MANTIS score was used to evaluate the microsatellite instability status (MSI) of patients, The higher the score is, the microsatellite instability status is closer to MSI-H. We found that in the TCGA cohort, MANTIS scores were higher in CXCR3-high patients than in TCGA-low patients, but this difference was not statistically significant (TCGA cohort: p > 0.05, Fig. 4G).
Analysis of Drug Sensitivity
Drug sensitivity analysis can help to transform findings from research into clinical application by identifying potential drug treatment options for future application. We used the Genomics of Drug Sensitivity in Cancer (GDSC) database, the CLUE database, and the RNA transcriptome data from two bladder cancer cohorts to perform drug sensitivity analysis. Mechanism of action (MoA) analysis was used to summarize and screen the drugs’ potential mechanisms of action.
First, we used the pRRophetic algorithm, the GDSC database, and the gene expression profiles from the ICI and TCGA cohorts to construct a ridge regression model to predict the IC50 values of 138 small and medium molecule drugs. We selected 18 drugs with 14 different mechanisms of action from the ICI and TCGA cohorts (Fig. 5A). We then performed cMap analysis on the differentially expressed genes from the two cohorts and screened 28 targeted drugs according to scores p < 0.05 and ES > 0 in the CLUE database (Fig. 5B). This identified drugs that altered the mRNA profiles of cell lines to more closely resemble those of the CXCR3-high patients. These findings suggested that mUC patients were more sensitive to ICI treatment when treated with the identified drugs, which provides useful insight for ICI combination therapy.
MoA analysis revealed the molecular mechanisms of action for the drugs identified in our screen. We identified four tubulin inhibitors  (docetaxel, paclitaxel, parbendazole, mebendazole) and two ATPase inhibitors (helveticoside, thapsigargin) from the CLUE database and the GDSC database. Some studies have revealed the anti-tumor mechanisms of above drugs. We speculate that these drugs may enhance the response to ICI therapy, but further in vitro and in vivo studies are needed to confirm this hypothesis. Detailed findings from this analysis are shown in Supplementary Table 2
CXCR3 Pathway Activation is Also a Predictor of Response to Immunotherapy in Patients with Other Cancers
Finally, we validated our findings on the relationship between CXCR3 pathway activation and ICI effectiveness in cohorts of other types of cancer. We found that CXCR3 pathway activation can not only predict the effectiveness of ICIs in patients with metastatic urothelial carcinoma, but it can also predict the effectiveness of immunotherapy in patients with melanoma, non-small cell lung cancer, and liver cancer. We analyzed CXCR3 pathway ssGSEA scores in patients with liver cancer, melanoma, and non-small cell lung cancer who received immunotherapy and found that CXCR3 pathway scores in the responder groups were significantly higher than those in the non-responder groups (Wilcoxon's test, GSE35640, p = 0.006; GSE14091, p = 0.0034; GSE93157, p = 0.095; GSE126044, p = 0.027; GSE13522, p = 0.084; PRJ23709, p = 8.8e-06; Supplementary Fig. 2G-L). To achieve the best validation effect, we used ROC curve analysis to obtain the optimal threshold (Supplementary Fig. 3) and divided patients into CXCR3-high and CXCR3-low groups according to the optimal threshold. We found that there were more responders in the CXCR3-high group than in the CXCR3-low group (Fisher's exact test, GSE35640, p = 0.0061; GSE14091, p = 0.034; GSE93157, p = 0.04; GSE126044, p = 0.026; GSE13522, p = 0.033; PRJ23709, p = 5e-06; Supplementary Fig. 2A-F). These conclusions validate our findings from mUC patients and suggest an association between CXCR3 pathway activation and response to immunotherapy.
To investigate the clinical significance of CXCR3 pathway activation and response to immunotherapy in patients with urothelial bladder carcinoma, we performed immunohistochemical analysis on two urothelial carcinoma patients treated with ICI therapy at Zhujiang hospital. Immunohistochemistry showed that three core proteins associated with the CXCR3 pathway, CXCR3, CXCL9, CXCL10, and were more highly expressed in cancer tissues from the immunotherapy-responder group than in tissues from the immunotherapy non-responder group (n = 1 per group) (Fig. 1F).
We used Image J software to quantify the immunochemistry-stained results of three CXCR3 pathway core protein, and use GraphPad Prism to visualize the results (T-test, CXCL9,p = 0.0005;CXCL10,p = 0.0001, CXCR3,p = 0.0007;Figure 1G). In conclusion, from analyzing publicly available datasets and our own clinical immunohistochemistry specimens, we conclude that higher levels of CXCR3 pathway activation are correlated with a better response to immunotherapy in patients with urothelial bladder carcinoma.