Exploring subclass-specific therapeutic agents for hepatocellular carcinoma by informatics-guided drug screen. Issue 4 (9th November 2020)

• Record Type: Journal Article
• Authors: Yang, Chen; Chen, Junfei; Li, Yan; Huang, Xiaowen; Liu, Zhicheng; Wang, Jun; Jiang, Hua; Qin, Wenxin; Lv, Yuanyuan; Wang, Hui; Wang, Cun
• Is Part Of: Briefings in bioinformatics. Volume 22:Issue 4(2021)
• Publication Date: 2020-11-09
• Subjects: hepatocellular carcinoma -- molecular classification -- precision medicine -- drug repurposing; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbaa295
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Almost all currently approved systemic therapies for hepatocellular carcinoma (HCC) failed to achieve satisfactory therapeutic effect. Exploring tailored treatment strategies for different individuals provides an approach with the potential to maximize clinical benefit. Previously, multiple studies have reported that hepatoma cell lines belonging to different molecular subtypes respond differently to the same treatment. However, these studies only focused on a small number of typical chemotherapy or targeted drugs across limited cell lines due to time and cost constraints. To compensate for the deficiency of previous experimental researches as well as link molecular classification with therapeutic response, we conducted a comprehensive in silico screening, comprising nearly 2000 compounds, to identify compounds with subclass-specific efficacy. Here, we first identified two transcriptome-based HCC subclasses (AS1 and AS2) and then made comparison of drug response between two subclasses. As a result, we not only found that some agents previously considered to have low efficacy in HCC treatment might have promising therapeutic effects for certain subclass, but also identified novel therapeutic compounds that were not routinely used as anti-tumor drugs in clinic. Discovery of agents with subclass-specific efficacy has potential in changing the status quo of population-based therapies in HCC and providing new insights into precision oncology.