Construction and validation of consensus clustering-derived metabolism- and immune-associated genes model for prognosis prediction in cancer patients with liver metastases.

Abstract

Liver metastasis (LM) is a cancer hallmark linked to poor prognosis and high mortality. Immune and metabolic shifts play critical roles in LM progression. This study aims to explore the prognostic value of immune- and metabolism-associated genes for LM and investigate their potential mechanisms. Here, we established a prognostic model based on Consensus Clustering-derived Metabolism- and Immune-associated genes (CCMI). Both the CCMI model and each hub gene demonstrated predictive value for LM patients at RNA and protein levels. Moreover, patients with high CCMI scores showed worse prognosis, elevated mutation frequency and heterogeneity, enrichment of cancer-promoting pathways, and increased neutrophil infiltration. Mechanistically, functional studies showed that CKB and ARG2 enhanced the proliferation, self-renewal, migration and invasion of cancer cells via activating MAPK or PI3K-AKT signaling pathways. MAFF was validated to play a key role in inducing neutrophil recruitment and infiltration through upregulating expression of CXCL1, thereby accelerating LM progression. In conclusion, this study presented a practical prognostic CCMI model for LM patients and investigated associated molecular and immune signatures. Our results uncovered the regulatory mechanisms of CCMI hub genes that promote LM progression, highlighting their potential as biomarkers for precision diagnosis and treatment of LM.