To obtain the expression pattern of CXCL10 in BLCA, we conducted a comprehensive expression analysis that incorporated different clinical variables from TCGA-BLCA cohort. It was observed that CXCL10 was significantly upregulated in tumor tissues (Fig. 1A; p = 0.003). Upregulation of CXCL10 expression was also observed in non-papillary tumors (Fig. 1D; p = 7.2e−08) and in higher grades (Fig. 1E; p = 5e−05). However, no statistically significant differences were observed with regards to gender (Fig. 1B, p = 0.46), age (Fig. 1C, p = 0.5), or T (Fig. 1F; p = 0.95), N (Fig. 1G; p = 0.73), and M staging (Fig. 1H, p = 0.51). Furthermore, we examined the impact of CXCL10 on the prognosis of BLCA patients. Analysis of TCGA-BLCA, Imvigor210, and GSE70691 datasets revealed that the survival analysis of CXCL10 in BLCA showed statistically significant differences (Figs. 2A–C) (log-rank test, p < 0.05), suggesting that patients with high CXCL10 expression may have a better prognosis.

The expression of CXCL10 in BLCA. Expression of CXCL10 in different A tissues, B genders, C age, D subtypes, E grades, F T stage, G N stage, H M stage, and I BLCA cell lines

The overall survival rate of BLCA patients in CXCL10 subgroups. A TCGA-BLCA cohort. B IMvigor 210 cohort. C GSE70691 cohort

In addition, we verified the expression of CXCL10 in different human bladder cancer cells by qRT‑PCR. The findings revealed a significant upregulation of CXCL10 in a variety of bladder cancer cells, including sw780, T24, 5637, RT4, and RT112, compared with normal bladder cell(Sv-huc) (Fig. 1I, all p < 0.05 Table 1).

Genomic instability is known to play a critical role in the development of cancer [19]. To understand whether CXCL10 is associated with genomic instability in BLCA, we first conducted an analysis using cBioPortal. The results showed that the types of gene alterations of CXCL10 in BLCA mainly included mutation, amplification, and deep deletion (Fig. 3A). Furthermore, we found that patients with high CXCL10 expression in TCGA-BLCA have a higher tumor mutation burden (TMB) (Fig. 3C, p < 0.001), however, our analysis indicated no significant difference in microsatellite instability (MSI) within the CXCL10 subgroups (Fig. 3D, p = 0.29). In addition, between the high and low CXCL10 expression groups, several genes (TP53, RB1, FGFR3, EP300, RYR2, FLGz) exhibited significantly different mutation frequencies. In the high CXCL10 group, there was a significant gain in chromosome 5p15.33, while 3p14.2, 8p23.3, 8p21.3, 9p23, 9p21.3, 11p15.5, and 13q14.2 showed significant loss (Fig. 3B, p < 0.05).

CXCL10 is involved in the genomic instability of BLCA. A Gene alterations of CXCL10 in BLCA mainly included mutation, amplification, and deep deletion. B Gene mutation and chromosome gain/loss between CXCL10 subgroups. The C TMB and D MSI between CXCL10 subgroups

To further explore the role of CXCL10 in BLCA, we grouped genes based on CXCL10 expression values and explored differentially expressed genes. We then subjected these genes to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to determine their biological functions. The results revealed that in the group with high expression of CXCL10, several immune pathways were enriched, including those related to immune response and the generation of immune cells (Fig. 4A, B). These pathways are essential for immune responses. On the other hand, the group with low expression of CXCL10 was primarily enriched in processes such as substance metabolism and energy conversion (Fig. 4C, D). It is thus inferred that CXCL10 plays an important role in the immune processes of BLCA and may be involved in the progression of BLCA through multiple immune pathways.

Functional analysis of CXCL10 in BLCA. A, C KEGG. B, D GO

TME comprises various components, including tumor cells, immune cells, inflammatory cells, stem cells, vascular system, fibrous tissue, and extracellular matrix (ECM), and TME has been demonstrated to play a crucial role in the occurrence and progression of BLCA [20]. Given that CXCL10 may influence BLCA through multiple immune processes, we conducted an analysis of the role of CXCL10 in the TME. Firstly, employing the ESTIMATE algorithm, we found a significant correlation between CXCL10 and both stromal score and immune score (Figs. 5A–C, all p < 0.05). Next, we explored the relationship between CXCL10 and different immune cells. The results showed that in the group with high CXCL10 expression, there were higher abundances of CD8 T cells, CD4 T cells, and M1 macrophages (Fig. 5D, p < 0.05), all of which play important roles in anti-tumor immune processes. In recent years, the effectiveness of immune checkpoint inhibitors in the field of immunotherapy has become increasingly evident. Therefore, we investigated the relationship between CXCL10 and different immune checkpoints. Surprisingly, the group with high CXCL10 expression exhibited significantly elevated levels of immune checkpoint expression, including CTLA4 and PD1 (Fig. 5E, all p < 0.001).

CXCL10 mediates the TME of BLCA patients. A–C ESTIMATE analysis of CXCL10 in BLCA. D CIBERSORT. E Immune checkpoints in CXCL10 subgroups

The response to immunotherapy varies among different BLCA patients. Predicting the response to immunotherapy based on potential biomarkers can help achieve personalized treatment and optimize resources utilization [21]. Combining multiple BLCA immunotherapy cohorts, we focused on exploring the impact of CXCL10 on immune therapy response. Firstly, in multiple immunotherapy cohorts (IMvigor210, Lauss, Kim, and Hwang cohort), the immune therapy-responsive group exhibited higher expression of CXCL10 compared to the non-responsive group (Fig. 6A, all p < 0.05). Moreover, in patients who received immune therapy, including anti-PD-1/PD-L1 and CAR-T therapies, the high expression group of CXCL10 showed better overall survival and progression-free survival (Fig. 6B, all p < 0.05). CXCL10 also demonstrated a certain level of accuracy in predicting the response of BLCA patients to immune therapy (IMvigor210 cohort: Lauss, Kim, and Hwang cohort) (Fig. 6C).

CXCL10 could predict the immune response of BLCA patients. A Immune response between CXCL10 subgroups. B Survival analysis of BLCA patients after receiving immune therapies between CXCL10 subgroups. C ROC curves of CXCL10 predicting the immune responses