Serum metabolomic analysis identified serum biomarkers predicting tumour recurrence after Bacillus Calmette-Guérin therapy in patients with non-muscle invasive bladder cancer

Background Metabolomic research and metabolomics-based biomarkers predicting treatment outcomes in bladder cancer remain limited.Objective We explored the serum metabolites potentially associated with the risk of recurrence after intravesical Bacillus Calmette-Gu & eacute;rin (BCG) therapy.Methods Two independent cohorts, a discovery cohort (n = 23) and a validation cohort (n = 40), were included in this study. Blood was collected before the induction of BCG therapy (pre-BCG blood; both discovery and validation cohorts) and after six doses of BCG (post-BCG blood; only discovery cohort). Metabolome analysis of serum samples was conducted using capillary electrophoresis time-of-flight mass spectrometry. The endpoint was intravesical recurrence-free survival, which was analysed using Kaplan-Meier estimates, the log-rank test, and the Cox proportional hazard model.Results Of the 353 metabolites quantified, nine (2.5%) and four (1.1%) were significantly upregulated and downregulated, respectively. The heatmap of hierarchical clustering analysis and principal coordinate analysis for the fold changes and in serum metabolites differentiated 10 recurrent cases and 13 non-recurrent cases in the discovery cohort. A metabolome response-based scoring model using 16 metabolites, including threonine and N6,N6,N6-trimethyl-lysine effectively stratified the risk of post-BCG recurrence. Additionally, pre-BCG metabolome-based score models using six metabolites, octanoylcarnitine, S-methylcysteine-S-oxide, theobromine, carnitine, indole-3-acetic acid, and valeric acid, were developed from the discovery cohort. Univariate and multivariate analyses confirmed a high predictive accuracy in the validation and combination cohorts.Conclusions We demonstrated that numerous types of serum metabolites were altered in response to intravesical BCG and developed high-performance score models which might effectively differentiated the risk of post-BCG tumour recurrence.