基于甲状腺乳头状癌差异表达基因的生物标志物鉴定。
Identification of Biomarkers Based on Differentially Expressed Genes in Papillary Thyroid Carcinoma.
机构信息
Department of Endoerinology and Metabolism, The Second Affiliated Hospital, Harbin Medical University, Harbin, 150001, China.
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
出版信息
Sci Rep. 2018 Jul 2;8(1):9912. doi: 10.1038/s41598-018-28299-9.
The incidence of papillary thyroid carcinoma (PTC) is increasing rapidly throughout the world. Hence, there is an urgent need for identifying more specific and sensitive biomarkers to explorate the pathogenesis of PTC. In this study, three pairs of stage I PTC tissues and matched normal adjacent tissues were sequenced by RNA-Seq, and 719 differentially expressed genes (DEGs) were screened. KEGG pathway enrichment analyses indicated that the DEGs were significantly enriched in 28 pathways. A total of 18 nodes consisting of 20 DEGs were identified in the top 10% of KEGG integrated networks. The functions of DEGs were further analysed by GO. The 13 selected genes were confirmed by qRT-PCR in 16 stage I PTC patients and by The Cancer Genome Atlas (TCGA) database. The relationship interactions between DEGs were analysed by protein-protein interaction networks and chromosome localizations. Finally, four newly discovered genes, COMP, COL3A1, ZAP70, and CD247, were found to be related with PTC clinical phenotypes, and were confirmed by Spearman's correlation analyses in TCGA database. These four DEGs might be promising biomarkers for early-stage PTC, and provide an experimental foundation for further exploration of the pathogenesis of early-stage PTC.
甲状腺乳头状癌（PTC）的发病率在全球范围内迅速上升。因此，迫切需要鉴定更特异和敏感的生物标志物来探索 PTC 的发病机制。在这项研究中，通过 RNA-Seq 对 3 对 I 期 PTC 组织和匹配的正常相邻组织进行了测序，筛选出了 719 个差异表达基因（DEGs）。KEGG 通路富集分析表明，DEGs 显著富集于 28 条通路。在 KEGG 综合网络的前 10%中，共鉴定到由 20 个 DEG 组成的 18 个节点。通过 GO 进一步分析 DEGs 的功能。在 16 名 I 期 PTC 患者和 The Cancer Genome Atlas（TCGA）数据库中，通过 qRT-PCR 验证了 13 个选定基因。通过蛋白质-蛋白质相互作用网络和染色体定位分析了 DEGs 之间的关系相互作用。最后，通过 TCGA 数据库中的 Spearman 相关性分析，发现了 COMP、COL3A1、ZAP70 和 CD247 这四个新发现的基因与 PTC 的临床表型有关。这四个 DEG 可能是早期 PTC 的有前途的生物标志物，为进一步探索早期 PTC 的发病机制提供了实验基础。
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