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生物信息学筛选 ETV4 转录因子致癌基因并鉴定小分子抗癌药物。

Bioinformatics screening of ETV4 transcription factor oncogenes and identifying small-molecular anticancer drugs.

机构信息

Department of Computational Biology and Bioinformatics, University of Kerala, Thiruvananthapuram, Kerala, India.

出版信息

Chem Biol Drug Des. 2022 Feb;99(2):277-285. doi: 10.1111/cbdd.13981. Epub 2021 Nov 22.

DOI:10.1111/cbdd.13981
PMID:34757684
Abstract

This bioinformatics study aimed to identify ETV4 transcription factor oncogenes and outline anticancer drugs for these genes. First, we collected known 61 ETV4 cancer targets that were framed as two classes of queries to screen against the multiomics resources in GeneMANIA. This method accessed and added functionally similar 20 genes to each set. These data were interpreted by hub genes, network clustering, gene ontology, and pathway analyses, and the results confirmed that all resultant genes were cancer promoters. The ETS-binding motifs were identified from the promoter regions of these genes. Thus, 23 ETV4 targets were figured and those involved in oncogenesis were filtered as the following 16 putative nodes: MMP8, MMP14, KDR, BRIP1, CXCR1, GRB14, SHC2, SHC4, SH2B1, SH2B2, INPPL1, PTPN3, GNG12, SEMA4D, RHOA, and SPSB2. The transcriptional regulation of these oncogenes was coordinated by an extensive miRNA network that found to deregulate many cancer pathways. Using DgIb database, the high quality 6 oncogene-drug combinations (MMP8-CHEMBL1231240, MMP8-Aminomethylamide, CXCR1-Reparixin, SEMA4D-Pepinemab, RHOA-Clausine E, and SPSB2-CHEMBL175296) were proposed. These findings may advance our understanding of novel neoplastic gene nexus of ETV4 and design treatment strategies for its modulation.

摘要

本生物信息学研究旨在鉴定 ETV4 转录因子致癌基因,并为这些基因勾勒出抗癌药物。首先,我们收集了已知的 61 个 ETV4 癌症靶点,将其分为两类查询,以筛选 GeneMANIA 中的多组学资源。该方法访问并向每一组添加了 20 个功能相似的基因。这些数据通过枢纽基因、网络聚类、基因本体和途径分析进行解释,结果证实所有结果基因均为癌症促进基因。从这些基因的启动子区域鉴定出 ETS 结合基序。因此,确定了 23 个 ETV4 靶点,并将那些参与致癌作用的靶点过滤为以下 16 个假定节点:MMP8、MMP14、KDR、BRIP1、CXCR1、GRB14、SHC2、SHC4、SH2B1、SH2B2、INPPL1、PTPN3、GNG12、SEMA4D、RHOA 和 SPSB2。这些致癌基因的转录调控由广泛的 miRNA 网络协调,该网络发现可失调许多癌症途径。使用 DgIb 数据库,提出了 6 种高质量的癌基因-药物组合(MMP8-CHEMBL1231240、MMP8-Aminomethylamide、CXCR1-Reparixin、SEMA4D-Pepinemab、RHOA-Clausine E 和 SPSB2-CHEMBL175296)。这些发现可能有助于我们理解 ETV4 的新型肿瘤基因网络,并设计其调节的治疗策略。

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