Identification of neuronal synapse-related signatures and potential therapeutic drugs in colorectal cancer based on machine learning algorithms and molecular docking.

ABSTRACT:

Background

Nervous system-cancer interactions can regulate tumorigenesis, invasion, and metastasis. However, specific biomarkers for targeting neuron synapse in colorectal cancer (CRC) remain unexplored. This study aims to develop a neuronal synapse-related signature (NSRS) to predict survival in CRC patients, identify potential therapeutic drugs, and explore its clinical applications.

Methods

We collected neuronal synapse genes (NSGs) from the Molecular Signatures Database (MSigDB) and published mass spectrometry data. Using weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator Cox regression (LASSO-Cox), we identified prognostic NSGs and constructed a NSRS through multivariate Cox regression. Functional enrichment analysis

SUBMITTER: Wu WJ 

PROVIDER: S-EPMC12169985 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature