Microenvironment characterization and multi-omics signatures related to prognosis and immunotherapy response of hepatocellular carcinoma

作者：Furong Liu, Qin Lu, Zhibin Liao, Jia Song, Chaoyi Yuan, Yachong Liu, Yu Wang, Heze Xu, Qiaofeng Zhang, Youliang Pei, Hongwei Zhang, Yonglong Pan, Xiaoping Chen, Zhanguo Zhang, Wanguang Zhang, Bixiang Zhang · 发表于：Experimental Hematology and Oncology · 年份：2020 · DOI：10.1186/s40164-020-00165-3 · 被引用次数：198 · 研究领域：Ferroptosis and cancer prognosis、Cancer Immunotherapy and Biomarkers、Immune cells in cancer

BACKGROUND: Immune cell infiltration in the tumor microenvironment (TME) affects tumor initiation, patients' prognosis and immunotherapy strategies. However, their roles and interactions with genomics and molecular processes in hepatocellular carcinoma (HCC) still have not been systematically evaluated. METHODS: We performed unsupervised clustering of total 1000 HCC samples including discovery and validation group from available public datasets. Immune heterogeneity of each subtype was explored by multi-dimension analysis. And a support vector machine (SVM) model based on multi-omics signatures was trained and tested. Finally, we performed immunohistochemistry to verify the immune role of signatures. RESULTS: We defined three immune subtypes in HCC, with diverse clinical, molecular, and genomic characteristics. Cluster1 had worse prognosis, better anti-tumor characteristics and highest immune scores, but also accompanied by immunosuppression and T cell dysfunction. Meanwhile, a better anti-PD1/CTLA4 immunotherapeutic response was predicted in cluster1. Cluster2 was enriched in TAM-M2 and stromal cells, indicating immunosuppression. Cluster3, with better prognosis, had lowest CD8 T cell but highest immune resting cells. Further, based on genomic signatures, we developed an SVM classifier to identify the patient's immunological status, which was divided into Type A and Type B, in which Type A had poorer prognosis, higher T cell dysfunction despite higher T cell infiltration, an...