Differentially expressed RBP (DERBP) identification
The research design is shown in Fig. 1a. In this study, we performed a comprehensive analysis of crucial functions and prognostic significance of RBPs in BLCA. Data regarding BLCA were acquired from TCGA, including 411 bladder cancer samples and 19 normal bladder samples. Relevant packages in R were utilized to process the data and select the DERBPs. A total of 388 (out of 1542) RBPs  fulfilled the screening criteria of the study, consisting of 219 upregulated and 169 downregulated RBPs. The heatmap and volcano map of DERBPs are displayed in Fig. 1b, c.
PPI network establishment and module selection
To demonstrate the functions of DERBPs in BLCA, we established the PPI network using STRING database and Cytoscape software, which consisted of 4145 edges and 376 nodes (Fig. 2a). The PPI network was analyzed using MCODE to determine top three important modules, which consisted of 3302 edges and 104 nodes (Fig. 2b).
GO and KEGG enrichment analysis
We performed GO and KEGG functional enrichment analysis of DERBPs using R software and correlation packages. The downregulated DERBPs were remarkably enriched in the GO analysis related to RNA splicing, and regulation of mRNA metabolic process, cytoplasmic ribonucleoprotein granule, ribonucleoprotein granule, translation factor activity, RNA binding, and mRNA 3'-UTR binding (Fig. 3a); the upregulated DERBPs were remarkably enriched in ncRNA processing, tRNA metabolic process, cytoplasmic ribonucleoprotein granule, ribonucleoprotein granule, and catalytic activity, acting on RNA, and catalytic activity, acting on a tRNA (Fig. 3c). We found the downregulated DERBPs to be mainly enriched in KEGG analysis related to mRNA surveillance pathway, RNA transport, and RNA degradation (Fig. 3b) while the upregulated DERBPs were remarkably enriched in RNA transport, spliceosome, and mRNA surveillance pathway (Fig. 3d). Further, we performed GO and KEGG functional enrichment analysis of key modules, results of which are shown in Table 1.
Prognosis-related RBP screening
A total of 388 DERBPs were identified. In order to study the prognostic value of these RBPs, univariate Cox regression analysis was performed, and 19 candidate hub RBPs related to prognosis were obtained (Fig. 3e). Multivariate Cox regression analysis was performed on the 19 RBPs, of which 9 hub RBPs were identified as independent predictors of BLCA (Fig. 3f, Table 2).
Prognosis-related model construction and analysis
A total of 404 patients with BLCA were randomly divided into training group (202 patients) and testing group (202 patients). The 9 prognosis-related hub RBPs were utilized to establish a predictive model based on training-group data. We calculated the risk score of every patient based on the following formula:
Risk score = (0.2707 × ExpTRIM71) + (-0.1148 × ExpYTHDC1) + (0.0417 × DARS2) + (0.0272 × ExpXPOT) + (0.1341 × ExpZNF106) + (0.2806 × ExpFTO) + (-0.023 × ExpIPO7) + (0.0521 × ExpEFTUD2) + (-0.0812 × ExpCTU1)
Next, we aimed to evaluate the predictive ability. Results in the training group indicated patients in high-risk cohort to have worse OS than those in the low-risk cohort (Fig. 4b). ROC analysis demonstrated prognostic value of the nine hub RBPs. Area under the ROC curve (AUC) of the model was 0.752 in the training group (Fig. 4c), suggesting it to have better diagnostic capability. In the training group, Fig. 4a showed the expression heatmap, patient survival status, and risk scores for the low- and high-risk cohorts based on nine RBPs. In order to evaluate whether the risk score model had the same prognostic significance in the testing group, the same formula was used in the latter; high-risk cohort patients were found to have worse OS than those in the low-risk cohort, and area under the ROC curve was 0.701 (Fig. 5a–c). It thus suggested better sensitivity and specificity of the model for predicting prognosis.
A nomogram based on nine RBPs
In order to develop a quantitative approach for predicting prognosis in bladder cancer, nine RBPs were integrated to construct a nomogram (Fig. 6a). Based on multivariate Cox regression analysis, the point scale in nomogram was used to assign values to individual variables. By drawing a vertical line between the prognosis axis and total-point axis, we could calculate the estimated survival rate of 1 year, 3 years, and 5 years, which could eventually help doctors to make clinical decisions for patients with BLCA.
Mutation analysis and prognostic value of clinical parameters
Mutation analysis of the hub genes TRIM71, YTHDC1, DARS2, XPOT, ZNF106, FTO, IPO7, EFTUD2, and CTU1 was performed using the cBioPortal platform. Results indicated that in 226 samples from 404 patients with BLCA, the 9 hub RBPs had changed (56%) (Fig. 6b, c). The high mRNA levels of DARS2 was the maximum alteration among the 9 hub RBPs.
Cox regression analysis was used to evaluate the effect of different clinical characteristics on the prognosis of patients with BLCA. Univariate Cox regression analysis results suggested age, stage, and risk score to be related to OS of patients with BLCA, in both training and testing groups (Fig. 6d, f). Multivariate Cox regression analysis results indicated age, stage, and risk score to be independent prognostic factors associated with OS in the training and testing groups (Fig. 6e, g).
Survival analysis and expression level of hub RBPs
To demonstrate prognostic significance of the nine hub RBPs in BLCA, the overall survival of every hub RBP was analyzed to draw Kaplan-Meier curve; p-value was calculated using UCSC online tool. Results showed that patients with BLCA, having high DARS2, FTO, IPO7, XPOT, and ZNF106 expression (Fig. 7b, d, e, g, i) and low CTU1 and YTHDC1 expression (Fig. 7a, h) were correlated with worse OS. We used the immunohistochemical results of Human Protein Atlas database to explore the expression of hub RBPs in BLCA, and found that DARS2, EFTUD2, FTO, TRIM71, and ZNF106 levels (Fig. 8b-d, f, h) in bladder cancer tissues were significantly higher than in normal bladder tissues. However, the antibody staining levels of CTU1, IPO7, and YTHDC1 (Fig. 8a, e, g) in bladder cancer tissues were relatively reduced.