Integrated Analysis of Angiogenesis-Mediated Tumor Immune Microenvironment Pattern in Hepatocellular Carcinoma (HCC) and a Novel Prognostic Model Construction to Predict Patient Outcome

BACKGROUND Hepatocellular carcinoma (HCC) is a malignant tumor which is famous for its high heterogeneity and complex pathogenesis. Angiogenesis is an important driver of tumor progression and immune-suppressive microenvironment formation. MATERIAL AND METHODS A training set was acquired from the TCGA-LIHC cohort. An angiogenesis-active subtype was identified by consensus clustering analysis. The tumor subtype's immune microenvironment pattern was analyzed using quanTIseq. DEGs-mediated biology function was analyzed by enrichment analysis based on GO and KEGG. A prognostic model was constructed using LASSO Cox regression analysis and validated by 2 external datasets derived from GEO and ICGC. Quantitative real-time PCR assay was conducted to analyze CDCA8's expression status in the HCC line and normal liver cell line. RESULTS In HCC, patients with the angiogenesis-active subtype had a poor prognosis. Angiogenesis can shape the tumor microenvironment into high-M2 microphage infiltration and activity pattern. Here, we identified an angiogenesis-active HCC subtype and constructed an angiogenesis feature-based prognostic model to predict patient outcome. The external validation sets were enrolled to verify the accuracy of this model. CONCLUSIONS Our research demonstrated angiogenesis can confer the tumor immune-suppressive characteristic. We provide a robust method to evaluate the HCC's angiogenesis potential and help identify the angiogenesis-active subtype. Validation in the external validation cohort further confirmed the accuracy of our prognostic model.