Two precision medicine predictive tools for six malignant solid tumors: from gene-based research to clinical application

Background: The current study aimed to construct competing endogenous RNA (ceRNA) regulation network and develop two precision medicine predictive tools for colorectal cancer (CRC). Methods: Differentially expressed (DE) analyses were performed between CRC tissues and normal tissues. A ceRNA regulation network was constructed based on DElncRNAs, DEmiRNAs, and DEmRNAs. Results: Fifteen mRNAs (ENDOU, MFN2, FASLG, SHOC2, VEGFA, ZFPM2, HOXC6, KLK10, DDIT4, LPGAT1, BEX4, DENND5B, PHF20L1, HSP90B1, and PSPC1) were identified as prognostic biomarkers for CRC by multivariate Cox regression. Then a Fifteen-mRNA signature was developed to predict overall survival for CRC patients. Concordance indexes were 0.817, 0.838, and 0.825 for 1-, 2- and 3-year overall survival. Patients with high risk scores have worse OS compared with patients with low risk scores. Conclusion: The current study provided deeper understanding of prognosis-related ceRNA regulatory network for CRC. Two precision medicine predictive tools named Smart Cancer Survival Predictive System and Gene Survival Analysis Screen System were constructed for CRC. These two precision medicine predictive tools can provide valuable precious individual mortality risk prediction before surgery and improve the individualized treatment decision-making.