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

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• Colorectal cancer (CRC) poses a significant health challenge.
• Understanding the complex regulatory networks in CRC is crucial for improving patient outcomes.

Purpose of the Study:

• To construct a competing endogenous RNA (ceRNA) regulation network for colorectal cancer (CRC).
• To develop predictive tools for precision medicine in CRC.
• To identify prognostic biomarkers for CRC survival.

Main Methods:

• Differential expression (DE) analyses were conducted on CRC and normal tissues.
• A ceRNA network was built using differentially expressed lncRNAs, miRNAs, and mRNAs.
• Multivariate Cox regression identified fifteen mRNAs as prognostic biomarkers.

Main Results:

• A fifteen-mRNA signature was developed to predict overall survival (OS) in CRC patients.
• The signature demonstrated high concordance indexes for 1-, 2-, and 3-year OS (0.817, 0.838, 0.825).
• High-risk scores correlated with worse OS, indicating prognostic value.

Conclusions:

• The study enhances understanding of prognosis-related ceRNA networks in CRC.
• Two precision medicine tools, Smart Cancer Survival Predictive System and Gene Survival Analysis Screen System, were created.
• These tools provide valuable individual mortality risk predictions, aiding treatment decisions.