NMR-based metabolomics for early detection of prostate cancer biomarker/s

Motivation: Current diagnostic methods cannot predict the aggressiveness of prostate cancer (PCa) at a treatable stage of disease. Goal(s): To interrogate tumorigenesis of PCa and AI/ML techniques to NMR-based targeted blood plasma metabolomic profiling analysis for prediction of PCa. Approach: Use AI/ML approaches to NMR metabolic profiling for PCa patient blood plasma data analysis Results: Phosphocreatine, choline, 3-hydroxybutyrate, taurine and glucose showed highest discriminate using CFS, PLS-DA, OPLS-DA, random forest models. Impact: It will pave way to enhance understanding of cancer pathogenesis and biomarker/s identification and early detection systems.