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A minimal connected network of transcription factors regulated in human tumors and its application to the quest for universal cancer biomarkers.

机译:在人类肿瘤中调节的转录因子的最小连接网络及其在寻求通用癌症生物标记物中的应用。

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摘要

A universal cancer biomarker candidate for diagnosis is supposed to distinguish, within a broad range of tumors, between healthy and diseased patients. Recently published studies have explored the universal usefulness of some biomarkers in human tumors. In this study, we present an integrative approach to search for potential common cancer biomarkers. Using the TFactS web-tool with a catalogue of experimentally established gene regulations, we could predict transcription factors (TFs) regulated in 305 different human cancer cell lines covering a large panel of tumor types. We also identified chromosomal regions having significant copy number variation (CNV) in these cell lines. Within the scope of TFactS catalogue, 88 TFs whose activity status were explained by their gene expressions and CNVs were identified. Their minimal connected network (MCN) of protein-protein interactions forms a significant module within the human curated TF proteome. Functional analysis of the proteins included in this MCN revealed enrichment in cancer pathways as well as inflammation. The ten most central proteins in MCN are TFs that trans-regulate 157 known genes encoding secreted and transmembrane proteins. In publicly available collections of gene expression data from 8,525 patient tissues, 86 genes were differentially regulated in cancer compared to inflammatory diseases and controls. From TCGA cancer gene expression data sets, 50 genes were significantly associated to patient survival in at least one tumor type. Enrichment analysis shows that these genes mechanistically interact in common cancer pathways. Among these cancer biomarker candidates, TFRC, MET and VEGFA are commonly amplified genes in tumors and their encoded proteins stained positive in more than 80% of malignancies from public databases. They are linked to angiogenesis and hypoxia, which are common in cancer. They could be interesting for further investigations in cancer diagnostic strategies.
机译:通用的癌症生物标志物候选物应该在广泛的肿瘤范围内区分健康患者和患病患者。最近发表的研究已经探索了某些生物标记物在人类肿瘤中的普遍用途。在这项研究中,我们提出了一种综合方法来寻找潜在的常见癌症生物标志物。使用TFactS网络工具以及通过实验建立的基因法规目录,我们可以预测305种覆盖大量肿瘤类型的不同人类癌细胞系中调控的转录因子(TFs)。我们还确定了在这些细胞系中具有显着的拷贝数变异(CNV)的染色体区域。在TFactS目录的范围内,鉴定了88个TF,它们的活性状态通过其基因表达和CNV得以鉴定。它们与蛋白质相互作用的最小连接网络(MCN)在人类管理的TF蛋白质组中形成了重要的模块。该MCN中包含的蛋白质的功能分析显示,癌症途径和炎症均富集。 MCN中十个最主要的蛋白质是TF,它们可以反式调节157个已知编码分泌蛋白和跨膜蛋白的基因。在可公开获得的来自8,525个患者组织的基因表达数据中,与炎症性疾病和对照相比,癌症中有86个基因受到不同的调控。根据TCGA癌症基因表达数据集,在至少一种肿瘤类型中,有50个基因与患者存活率显着相关。富集分析表明,这些基因在常见的癌症途径中机械相互作用。在这些癌症生物标志物候选物中,TFRC,MET和VEGFA通常是肿瘤中的扩增基因,其编码蛋白在公共数据库中超过80%的恶性肿瘤中呈阳性染色。它们与癌症中常见的血管生成和缺氧有关。它们对于癌症诊断策略的进一步研究可能很有趣。

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