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Analysis of aberrant pathways using HCC candidate biomarkers identified from high-throuput omics studies

机译:使用从高通量组学研究中鉴定的NCC候选生物标记物分析异常途径

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Various omics studies have led to identification of a large number of disease-associated biomarkers at different molecular levels (e.g. DNA, mRNA, protein, metabolites). For example, hundreds of candidate biomarkers of human hepatocellular carcinoma (HCC) have been reported in the literature. However, the molecular mechanism and etiology of HCC have not been adequately determined. In this study, we investigate aberrant key pathways that may be altered in the progression of HCC by using text-mining and pathway centric analysis of diverse biomarkers identified from previous omics studies. The results show that Wnt/p-catenin signaling is the most significantly enriched pathway in these biomarkers. Also, we observe that cancer and gastrointestinal disease are the two most significant biological functions associated with these biomarkers. We believe that integration of candidate HCC biomarkers through text-mining and pathway-centric approaches help improve our understanding of the molecular pathogenesis of HCC and identify key drug targets.
机译:各种组学研究已导致鉴定出许多在不同分子水平(例如DNA,mRNA,蛋白质,代谢物)的与疾病相关的生物标记。例如,文献中已经报道了数百种人类肝细胞癌(HCC)候选生物标志物。但是,肝癌的分子机制和病因尚未得到充分确定。在这项研究中,我们通过使用文本挖掘和从以前的组学研究中鉴定出的各种生物标志物的途径中心分析来研究可能在肝癌进展中改变的异常关键途径。结果表明,Wnt / p-catenin信号传导是这些生物标志物中最显着的富集途径。此外,我们观察到癌症和胃肠道疾病是与这些生物标记物相关的两个最重要的生物学功能。我们认为,通过文本挖掘和以路径为中心的方法整合候选HCC生物标志物有助于提高我们对HCC分子发病机制的了解,并确定关键的药物靶标。

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