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首页> 外文会议>IEEE International Conference on Bioinformatics and Bioengineering >Identification of signaling pathways related to drug efficacy in hepatocellular carcinoma via integration of phosphoproteomic, genomic and clinical data
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Identification of signaling pathways related to drug efficacy in hepatocellular carcinoma via integration of phosphoproteomic, genomic and clinical data

机译：通过整合磷酸化蛋白质组学，基因组学和临床数据，鉴定与肝细胞癌药物疗效相关的信号通路

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Hepatocellular Carcinoma (HCC) is one of the leading causes of death worldwide, with only a handful of treatments effective in unresectable HCC. Most of the clinical trials for HCC using new generation interventions (drug-targeted therapies) have poor efficacy whereas just a few of them show some promising clinical outcomes [1]. This is amongst the first studies where the mode of action of some of the compounds extensively used in clinical trials is interrogated on the phosphoproteomic level, in an attempt to build predictive models for clinical efficacy. Signaling data are combined with previously published gene expression and clinical data within a consistent framework that identifies drug effects on the phosphoproteomic level and translates them to the gene expression level. The interrogated drugs are then correlated with genes differentially expressed in normal versus tumor tissue, and genes predictive of patient survival. Although the number of clinical trial results considered is small, our approach shows potential for discerning signaling activities that may help predict drug efficacy for HCC.
机译：肝细胞癌（HCC）是全球主要的死亡原因之一，只有极少数的治疗方法对无法切除的HCC有效。大多数使用新一代干预措施（药物靶向疗法）进行的肝癌临床试验的疗效均较差，而只有少数临床试验显示出一些有希望的临床结果[1]。这是第一批研究，其中在磷酸蛋白质组学水平上对在临床试验中广泛使用的某些化合物的作用方式进行了研究，试图建立临床疗效的预测模型。信号数据与先前发表的基因表达和临床数据在一个一致的框架内结合在一起，该框架可识别药物对磷酸蛋白质组学水平的影响并将其转化为基因表达水平。然后将被询问的药物与在正常组织与肿瘤组织中差异表达的基因相关联，并预测患者生存的基因。尽管考虑的临床试验结果数量很少，但我们的方法显示出辨别信号活性的潜力，这可能有助于预测HCC的药物疗效。

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