Smart Cancer Predictive System

Smart Cancer Predictive System predicts overall survival in hepatocellular carcinoma by constructing an eight-mRNA prognostic nomogram from mRNA expression data to support precision oncology.

Key Features:

• Prognostic Nomogram Development: An Eight-mRNA prognostic nomogram was developed from 24,991 mRNA expression data points from 348 HCC patients using LASSO Cox regression.
• Biomarker Identification: The nomogram is based on eight mRNAs—N4BP3, ADRA2B, E2F8, MAPT, PZP, HOXD9, COL15A1, and NDST3—selected via multivariate Cox proportional regression analyses.
• Predictive Accuracy: The nomogram achieved a concordance index (C-index) of 0.765 (95% CI 0.724–0.806) for overall survival in the model cohort and a Harrell's C-index of 0.715 (95% CI 0.658–0.772) in the validation cohort.
• Risk Stratification: Patients are stratified into high-risk and low-risk groups based on mRNA expression profiles, with survival curves showing significantly poorer overall survival in the high-risk group.

Scientific Applications:

• Personalized Medicine: Predicts individual mortality risk probabilities to inform personalized treatment regimens for HCC patients.
• Research Utility: Provides prognostic mRNA biomarkers and molecular insights for oncology research and therapeutic target investigation.
• Clinical Decision Support: Supplies prognostic risk estimates to support clinical decision-making and patient management in HCC.

Methodology:

Data collection and preprocessing of mRNA expression data; LASSO Cox regression to identify prognostic mRNAs followed by multivariate Cox proportional regression to construct the Eight-mRNA prognostic nomogram; validation of predictive performance in a separate cohort.