Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma - Yang, Yuan; Wu, Guozhi; Li, Qiang; Zheng, Ya; Liu, Min; Zhou, Lingshan; Chen, Zhaofeng; Wang, Yuping; Guo, Qinghong; Ji, Rui; Zhou, Yongning (Frontiers in Molecular Biosciences, 2021)
Background: Hepatocellular carcinomas (HCC) is one of the highly heterogeneous cancers that lacks effective risk model for prognosis prediction. Therefore, we searched for angiogenesis related immune genes that affected the prognosis of HCC to construct a risk model and studied the role of this model in HCC. Methods: In this study, we collected the transcriptome data of HCC from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) database. Pearson correlation analysis was performed to identify the association between immune genes and angiogenesis related genes. Consensus clustering was applied to divide patients into clusters A and B. Subsequently, we studied the differentially angiogenesis related immune genes (DEari-genes) that affected the prognosis of HCC. The most significant features were identified by Least Absolute Shrinkage and Selection Operator (LASSO) regression, and a risk model was constructed. The reliability of the risk model was evaluated in the TCGA discovery cohort and the ICGC validation cohort. In addition, we compared the novel risk model to the previous models based on ROC analysis. ssGSEA analysis was used for function evaluation, and pRRophetic was utilized to predict the sensitivity of administrating chemotherapeutic agents. Results: Cluster A patients had favorable survival rates. A total of 23 DEari-genes were correlated with the prognosis of HCC. A 5-gene (including BIRC5, KITLG, PGF, SPP1 and SHC1) signature-based risk model was constructed. After regrouping the HCC patients by the median score, we could effectively discriminate between them based on adverse survival outcome, unique tumor immune microenvironment, and low chemosensitivity. Conclusions: The 5-gene signature-based risk score established by ari-genes showed a promising clinical prediction value.