Consensus subtypes of hepatocellular carcinoma associated with clinical outcomes and genomic phenotypes

肝细胞癌 转录组 索拉非尼 表型 生物 染色体不稳定性 基因组不稳定性 癌症研究 干细胞 免疫系统 基因 生物信息学 免疫学 遗传学 基因表达 DNA DNA损伤 染色体
作者
Sung Hwan Lee,Sun Young Yim,Yun Seong Jeong,Qi‐Xiang Li,Seongwon Kang,Bo Hwa Sohn,Shria Kumar,Ji‐Hyun Shin,You Rhee Choi,Jae‐Jun Shim,Hayeon Kim,Jihoon Kim,Shin Kim,Sheng Guo,Randy L. Johnson,Ahmed O. Kaseb,Koo Jeong Kang,Yun Shin Chun,Hyun‐June Jang,Byoung Gill Lee,Hyun Goo Woo,Min Jin Ha,Rehan Akbani,Lewis R. Roberts,David A. Wheeler,Ju Seog Lee
出处
期刊:Hepatology [Wiley]
卷期号:76 (6): 1634-1648 被引量:8
标识
DOI:10.1002/hep.32490
摘要

Although many studies revealed transcriptomic subtypes of HCC, concordance of the subtypes are not fully examined. We aim to examine a consensus of transcriptomic subtypes and correlate them with clinical outcomes.By integrating 16 previously established genomic signatures for HCC subtypes, we identified five clinically and molecularly distinct consensus subtypes. STM (STeM) is characterized by high stem cell features, vascular invasion, and poor prognosis. CIN (Chromosomal INstability) has moderate stem cell features, but high genomic instability and low immune activity. IMH (IMmune High) is characterized by high immune activity. BCM (Beta-Catenin with high Male predominance) is characterized by prominent β-catenin activation, low miRNA expression, hypomethylation, and high sensitivity to sorafenib. DLP (Differentiated and Low Proliferation) is differentiated with high hepatocyte nuclear factor 4A activity. We also developed and validated a robust predictor of consensus subtype with 100 genes and demonstrated that five subtypes were well conserved in patient-derived xenograft models and cell lines. By analyzing serum proteomic data from the same patients, we further identified potential serum biomarkers that can stratify patients into subtypes.Five HCC subtypes are correlated with genomic phenotypes and clinical outcomes and highly conserved in preclinical models, providing a framework for selecting the most appropriate models for preclinical studies.
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