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通过对微阵列数据集的综合分析筛选胆管癌的潜在生物标志物。

Screening of potential biomarkers for cholangiocarcinoma by integrated analysis of microarray data sets.

机构信息

Department of Gastrointestinal Surgery, Yantai Yuhuangding Hospital, Yantai, Shan Dong Province, China.

Department of General Surgery, Qingdao Municipal Hospital, Qingdao, Shan Dong Province, China.

出版信息

Cancer Gene Ther. 2016 Feb-Mar;23(2-3):48-53. doi: 10.1038/cgt.2015.66. Epub 2015 Dec 18.

DOI:10.1038/cgt.2015.66
PMID:26679756
Abstract

Cholangiocarcinoma (CCA) continues to harbor a difficult prognosis and it is difficult to diagnose in its early stages. The molecular mechanisms of CCA oncogenesis and progression are poorly understood. This study aimed to identify candidate biomarkers for CCA. Integrated analysis of microarray data sets was performed to identify differentially expressed genes (DEGs) between CCA and normal tissues. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then performed to identify the functions of DEGs. Furthermore, the protein-protein interaction (PPI) network of DEGs was constructed. The expressions of DEGs were validated in human CCA tissues by qRT-PCR. A set of 712 DEGs were identified in CCA compared with normal tissues, including 306 upregulated and 406 downregulated DEGs. It can be shown from the KEGG pathway analysis that some pathways may have important roles in pathology of CCA, including peroxisome proliferator-activated receptor signaling pathway, bile secretion, cell cycle, fat digestion and absorption. PPI network indicated that the significant hub proteins were PKM, SPP1 and TPM1. The abnormally overexpression PKM, SPP1 and TPM1 were closely related to oncogenesis and progression of CCA. PKM, SPP1, TPM1, COL1A1 and COL1A2 may serve as candidate biomarkers for diagnosis and prognosis of CCA.

摘要

胆管癌(CCA)的预后仍然较差,且早期诊断困难。CCA 发生和发展的分子机制尚不清楚。本研究旨在鉴定 CCA 的候选生物标志物。对 CCA 和正常组织的微阵列数据集进行了综合分析,以鉴定差异表达基因(DEGs)。然后进行基因本体论(GO)富集分析和京都基因与基因组百科全书(KEGG)通路富集分析,以鉴定 DEGs 的功能。此外,构建了 DEGs 的蛋白质-蛋白质相互作用(PPI)网络。通过 qRT-PCR 验证了 DEGs 在人 CCA 组织中的表达。与正常组织相比,CCA 中鉴定出了一组 712 个 DEGs,包括 306 个上调和 406 个下调的 DEGs。KEGG 通路分析表明,一些通路可能在 CCA 的病理学中具有重要作用,包括过氧化物酶体增殖物激活受体信号通路、胆汁分泌、细胞周期、脂肪消化和吸收。PPI 网络表明,显著的枢纽蛋白为 PKM、SPP1 和 TPM1。PKM、SPP1 和 TPM1 的异常过表达与 CCA 的发生和发展密切相关。PKM、SPP1、TPM1、COL1A1 和 COL1A2 可能作为 CCA 诊断和预后的候选生物标志物。

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