Abstract
BACKGROUND: Nodal involvement constitutes a pivotal prognostic indicator in colorectal carcinoma, yet the transcriptional machinery governing lymphatic dissemination and tumor-microenvironment crosstalk remains poorly elucidated. Conventional bulk sequencing methodologies lack sufficient resolution to deconvolve functionally distinct malignant subclones that drive the metastatic cascade. METHODS: We employed an integrative analytical framework combining tissue-level gene expression profiling from TCGA and GEO repositories with eight single-cell transcriptomic datasets comprising 266,995 individual cells. A phenotype-guided computational algorithm was implemented to delineate metastasis-driving malignant populations through correlating clinical parameters with cellular transcriptional profiles. Gene regulatory networks and transcription factor activity inference systematically decoded the molecular programs underlying metastatic phenotypes. Ligand-receptor pairing analysis mapped intercellular communication architectures between neoplastic cells and microenvironmental constituents. Experimental validation encompassed genetic perturbation studies, functional characterization assays, and pharmacological response evaluation in preclinical systems. RESULTS: We discovered a phenotypically distinct malignant population exhibiting robust associations with lymph node involvement and adverse clinical outcomes across nine independent validation cohorts. Regulatory network dissection identified IRF9 as the master transcriptional orchestrator of this metastatic program through coordination of a discrete gene module. Relative to their nonmetastatic counterparts, these aggressive cells establish markedly expanded intercellular communication networks, characterized by prominent VEGF-driven angiogenic signaling to endothelial compartments and integrin-laminin-mediated adhesion with stromal elements. EFNA1 emerged as a key signaling mediator demonstrating preferential enrichment in this metastatic subset. Elevated EFNA1 levels correlated with progressive disease stages and microsatellite-stable subtypes while showing inverse relationships with PD-L1 expression and T cell infiltration density-suggesting a unique immunoevasion mechanism. Genetic ablation of Efna1 substantially impaired cellular proliferation, motility, and invasion capabilities, while simultaneously augmenting Linifanib sensitivity, indicating synergistic therapeutic potential. CONCLUSIONS: Our investigation reveals a transcriptionally defined malignant population under IRF9 control that orchestrates immunosuppressive microenvironmental reprogramming via EFNA1-mediated signaling networks. The EFNA1-Linifanib combination may represent a potential therapeutic approach to mitigate anti-angiogenic resistance and restrain metastatic progression in colorectal carcinoma.