Discovery and validation of bladder cancer related excreted nucleosides biomarkers by dilution approach in cell culture supernatant and urine using UHPLC-MS/MS.

The exploration of nucleoside changes in human biofluids has profound potential for cancer diagnosis. Herein, we developed a rapid methodology to quantify 17 nucleosides by UHPLC-MS/MS. Five pairs of isomers were successfully separated within 8 min. The ME was mostly eliminated by sample dilution folds of 1000 for urine and 40 for CCS. The optimized method was firstly applied to screen potential nucleoside biomarkers in CCS by comprising bladder cancer cell lines (5637 and T24) and normal human bladder cell line SV-HUC-1 together with student's t-test and OPLS-DA. Nucleosides with significant differences in the supernatant of urine samples were also uncovered comparing BCa with the non-tumor group, as well as a comparison of BCa recurrence group with the non-recurrence group. By intersecting the differential nucleosides in CCS and urine supernatant, and then further confirmed using validation sets, the combination of m3C and m1A with AUC of 0.775 was considered as a potential biomarker for bladder cancer diagnosis. A panel of m3C, m1A, m1G, and m22G was defined as potential biomarkers for bladder cancer prognosis with an AUC of 0.819. Above all, this method provided a new perspective for diagnosis and recurrence monitoring of bladder cancer. SIGNIFICANCE: The exploration of nucleoside changes in body fluids has profound potential for the diagnosis and elucidation of the pathogenesis of cancer. In this study, we developed a rapid methodology for the simultaneous quantitative determination of 17 nucleosides in the supernatant of cells and urine samples using UHPLC-MS/MS to discover and validate bladder cancer related excreted nucleoside biomarkers. The results of this paper provide a new strategy for diagnosis and postoperative recurrence monitoring of bladder cancer and provide theoretical support for the exploration of its pathogenesis.

A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.

PURPOSE: Bladder cancer (BLCA) is one of the most common cancers worldwide. In a large proportion of BLCA patients, disease recurs and/or progress after resection, which remains a major clinical issue in BLCA management. Therefore, it is vital to identify prognostic biomarkers for treatment stratification. We investigated the efficiency of CpG methylation for the potential to be a prognostic biomarker for patients with BLCA. PATIENTS AND METHODS: Overall, 357 BLCA patients from The Cancer Genome Atlas (TCGA) were randomly separated into the training and internal validation cohorts. Least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) were used to select candidate CpGs and build the methylation risk score model, which was validated for its prognostic value in the validation cohort by Kaplan-Meier analysis. Hazard curves were generated to reveal the risk nodes throughout the follow-up. Gene Set Enrichment Analysis (GSEA) was used to reveal the potential biological pathways associated with the methylation model. Quantitative real-time polymerase chain reaction (PCR) and western blotting were performed to verify the expression level of the methylated genes. RESULTS: After incorporating the CpGs obtained by the two algorithms, CpG methylation of eight genes corresponding to TNFAIP8L3, KRTDAP, APC, ZC3H3, COL9A2, SLCO4A1, POU3F3, and ADARB2 were prominent candidate predictors in establishing a methylation risk score for BLCA (MRSB), which was used to divide the patients into high- and low-risk progression groups (p < 0.001). The effectiveness of the MRSB was validated in the internal cohort (p < 0.001). In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. Furthermore, a nomogram comprising MRSB, age, sex, and tumor clinical stage was developed to predict the individual progression risk, and it performed well. Survival analysis implicated the effectiveness of MRSB, which remains significant in all the subgroup analysis based on the clinical features. A functional analysis of MRSB and the corresponding genes revealed potential pathways affecting tumor progression. Validation of quantitative real-time PCR and western blotting revealed that TNFAIP8L3 was upregulated in the BLCA tissues. CONCLUSION: We developed the MRSB, an eight-gene-based methylation signature, which has great potential to be used to predict the post-surgery progression risk of BLCA.