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Exploring subclass-specific therapeutic agents for hepatocellular carcinoma by informatics-guided drug screen

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单位: [1]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Dept Liver Surg, Shanghai, Peoples R China [2]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Shanghai Canc Inst,State Key Lab Oncogenes & Rela, Shanghai, Peoples R China [3]Sun Yat Sen Univ, Zhongshan Sch Med, Dept Immunol, Guangzhou, Peoples R China [4]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Minist Hlth,Div Gastroenterol & Hepatol, Shanghai, Peoples R China [5]Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Hepat Surg Ctr, Wuhan, Peoples R China
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关键词: hepatocellular carcinoma molecular classification precision medicine drug repurposing

摘要:
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.

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出版当年[2020]版:
大类 | 1 区 生物
小类 | 1 区 生化研究方法 1 区 数学与计算生物学
最新[2025]版:
大类 | 2 区 生物学
小类 | 1 区 数学与计算生物学 2 区 生化研究方法
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出版当年[2019]版:
Q1 BIOCHEMICAL RESEARCH METHODS Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
最新[2023]版:
Q1 BIOCHEMICAL RESEARCH METHODS Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2019版] 出版当年五年平均 出版前一年[2018版] 出版后一年[2020版]

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第一作者单位: [1]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Dept Liver Surg, Shanghai, Peoples R China [2]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Shanghai Canc Inst,State Key Lab Oncogenes & Rela, Shanghai, Peoples R China
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通讯机构: [1]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Dept Liver Surg, Shanghai, Peoples R China [2]Shanghai Jiao Tong Univ, Renji Hosp, Sch Med, Shanghai Canc Inst,State Key Lab Oncogenes & Rela, Shanghai, Peoples R China
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