Therapeutic targets associated with conserved subtypes of hepatocellular carcinoma

Abstract

Background and aims: While many studies revealed clinically relevant conserved subtypes of hepatocellular carcinoma (HCC), their discovery is not translated to the clinic yet due to lack of associated therapeutic intervention for subtypes. We aim to examine consensus of discovered subtypes and uncover their clinical significance and to identify potential therapeutic targets for each subtype. Method: We integrated 16 previously established transcriptomic signatures for HCC to uncover consensus subtypes. We also developed and validated a robust predictor of consensus subtype with 100 genes (PICS100). Informatics and statistics approaches were applied to find clinical relevant association of genomic features. Patient derived xenograft (PDX) models were used for testing hypothesis from analysis of transcriptomic data. Results: Integrative analysis of genomic and proteomic data uncovered five subtypes of HCC with substantial difference in clinical outcomes. 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. High expression of IGF2 is another unique feature of CIN ubtype, suggesting that CIN subtype might have benefit of treatment targeting IGF2/IGFR pathway. IMH (IMmune High) is best characterized by its high TCR diversity and high baseline immune activity. BCM (Beta-Catenin with high Male predominance) is characterized by prominent beta-catenin activation, low miRNA expression, hypomethylation, and high sensitivity to sorafenib. Interestingly, subtype BCM had a significantly higher male-tofemale ratio than the other subtypes. Another unique molecular characteristic of subtype D was miRNA downregulation. DLP (Differentiated and Low Proliferation) is differentiated with high HNF4A activity. We also identified potential serum biomarkers that can stratify patients into 5 subtypes. Our PICS100 predictor is available in the website (https://kasaha1.shinyapps.io/pics100/) with test data set for those who wish to run genomic predictor. Multistep analysis of genomic and proteomic data identified therapeutic targets for poorest prognostic STM subtype and their therapeutic potential was further validated in cell line and mouse models. Conclusion: Newly discovered subtypes are associated with response to standard and experimental treatments and highly conserved in pre-clinical models such as cell lines and PDX tumors. Therefore, our study may provide a framework for selecting the most appropriate models for preclinical studies of new drugs and potentially for future clinical trials.