AUTHOR=Yang Yuan , Wu Guozhi , Li Qiang , Zheng Ya , Liu Min , Zhou Lingshan , Chen Zhaofeng , Wang Yuping , Guo Qinghong , Ji Rui , Zhou Yongning 

TITLE=Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=8

YEAR=2021

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2021.690206

DOI=10.3389/fmolb.2021.690206

ISSN=2296-889X

ABSTRACT=<p><bold>Background:</bold> Hepatocellular carcinoma (HCC) is one of the highly heterogeneous cancers that lacks an 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.</p><p><bold>Methods:</bold> In this study, we collected the transcriptome data of HCC from The <italic>Cancer</italic> Genome Atlas (TCGA) and the International <italic>Cancer</italic> 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 expressed 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 administering chemotherapeutic agents.</p><p><bold>Results:</bold> Cluster A patients had favorable survival rates. A total of 23 DEari-genes were correlated with the prognosis of HCC. A five-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 the adverse survival outcome, the unique tumor immune microenvironment, and low chemosensitivity.</p><p><bold>Conclusion:</bold> The five-gene signature-based risk score established by ari-genes showed a promising clinical prediction value.</p>