Prognostic Risk Modeling Based on Integrated Multi-Omics Analysis Identifies CRY2 as a Key Regulator in Tumor Immunity and Patient Survival in Colorectal Cancer​

Background: Colorectal cancer (CRC) prognosis is driven by metabolic heterogeneity. This study integrates ferroptosis and lipid metabolism to develop a robust prognostic signature and evaluates the role of CRY2 in CRC progression.Methods: Using TCGA-COAD and GSE39582 cohorts, we identified gene modules via WGCNA. A machine learning framework identified StepCox[forward] + Random Survival Forest as the optimal model. The immune landscape was assessed using CIBERSORT and TIDE. CRY2 was validated through siRNA knockdown, functional assays, and a murine xenograft model.Results: The resulting RiskScore was an independent prognostic factor (HR > 1.1, P < 0.001). High-risk patients showed poorer overall survival and an immunosuppressive microenvironment (elevated Tregs/Th2 cells, depleted CD4+ T cells), alongside higher TIDE scores suggesting immunotherapy resistance. GSEA linked high-risk scores to cell cycle and oxidative phosphorylation pathways. CRY2 emerged as a key oncogenic driver. High CRY2 expression correlated with advanced tumor stages. In vitro, CRY2 knockdown inhibited proliferation and migration while inducing G1 phase arrest. In vivo, silencing CRY2 significantly suppressed xenograft growth and Ki-67 expression.Conclusion: We established a novel ferroptosis- and lipid-related signature that effectively stratifies CRC survival and immune response. Furthermore, we identified CRY2 as a critical regulator of tumor growth, highlighting its potential as a therapeutic target and biomarker.