多组学整合揭示结直肠癌中的免疫-代谢异质性:针对ANGPTL4/FABP4/RBP7的预后模型及治疗策略OA

Objective To explore the heterogeneity of tumor immune microenvironment(TIME)in colorectal cancer(CRC)and the resultant treatment resistance and develop a prognostic model for predicting the treatment outcomes of CRC.Methods The multi-omics data including transcriptomic,somatic mutation and single-cell RNA sequencing data of a total of 1136 CRC samples from a TCGA cohort(n=568)and a GEO cohort(n=568)were integrated.The TCGA cohort was divided into Immunity_High and Immunity_Low subtypes by single-sample gene set enrichment analysis(ssGSEA)and t-SNE algorithm.A prognostic model was constructed using univariate Cox regression combined with LASSO-Cox regression,and the functions of the core genes including ANGPTL4,FABP4 and RBP7 were verified by single cell RNA-seq,molecular docking,kinetic simulations and qPCR/IHC experiments.Results The Immunity_High subtype of CRC was enriched with CD8+T cells and had significantly longer patient survival,while the Immunity_Low subtype was characterized by M0 macrophage infiltration.The prognostic model constructed based on 12 genes including ANGPTL4,FABP4 and RBP7 showed good predictive performance,with the AUC of 3-year survival rate reaching 0.765,an overall AUC of 0.76 in the TCGA cohort,and an overall AUC of 0.70 in the GEO cohort.Mechanistically,ANGPTL4 regulated macrophage polarization,FABP4 mediated fibroblast reprogramming,and RBP7 up-regulated PD-L1 expression.Molecular docking and kinetic simulations confirmed stable binding of retinoic acid and rosiglitazone to the core targets with the minimum binding energy of-8.3 kcal/mol.Conclusion The constructed prognostic model and the identified potential therapeutic targets provide new strategies to address immune therapy resistance for CRC.