Wu Yanmeizhi, Han Jun, Vladimirovna Kazakova Elena, Zhang Shumei, Lv Wenhua, Zhang Yan, Jamaspishvili Esma, Sun Jingxue, Fang Qingxiao, Meng Jingjing, Qiao Hong
Department of Endocrinology, No.2 Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, People's Republic of China.
Department of Epigenetics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang Province, People's Republic of China.
Onco Targets Ther. 2019 Oct 14;12:8479-8489. doi: 10.2147/OTT.S226426. eCollection 2019.
PTC is not generally considered a lethal disease, but prone to recurrence as the prognosis. Hashimoto's thyroiditis (HT) is an important factor that affects the prognosis of papillary thyroid carcinoma (PTC). It is crucial to find biomarkers to identify the combination of HT with PTC and to predict the prognosis.
RNASeq data from the Cancer Genome Atlas (TCGA) database was used to screen differentially expressed genes (DEGs) of PTC with HT via the edgeR package of R software version 3.3.0. Also, the DEGs were applied to the DAVID web-based tool to determine the enrichment of gene functions via Gene Ontology (GO) analysis and to identify associated pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. By constructing protein interaction networks within Cytoscape software, we screened candidate genes and explored possible relationships with the clinical phenotype of PTC. Finally, additional thyroid tissue samples were collected to verify the results above.
After analyzing the RNA-Seq data of PTC patients from the Cancer Genomic Atlas, 497 differentially expressed PTC genes were found to be associated with HT, of which protein tyrosine phosphatase receptor type C (PTPRC), KIT, and COL1A1 were associated with tumor size and lymph node metastasis (p < 0.05). Verification of these results with another 30 thyroid tissues of clinical PTC patients revealed that the expression level of PTPRC in the PTC with HT group was higher than that in the PTC without HT group (p < 0.05) and the ROC curve showed a good discrimination (area under the curve = 0.846). However, the correlation with the clinical phenotype was not statistically significant (p > 0.05).
These data suggest that upregulation of PTPRC enhances the incidence of HT associated with PTC and is also predictive of a poor prognosis.
甲状腺乳头状癌（PTC）一般不被认为是一种致命性疾病，但作为预后情况，它易于复发。桥本甲状腺炎（HT）是影响甲状腺乳头状癌（PTC）预后的一个重要因素。找到生物标志物以识别HT与PTC的组合并预测预后至关重要。
使用来自癌症基因组图谱（TCGA）数据库的RNA测序数据，通过R软件版本3.3.0的edgeR软件包筛选出伴有HT的PTC的差异表达基因（DEG）。此外，将这些DEG应用于基于DAVID的网络工具，通过基因本体论（GO）分析确定基因功能的富集情况，并在京都基因与基因组百科全书（KEGG）数据库中识别相关途径。通过在Cytoscape软件中构建蛋白质相互作用网络，我们筛选出候选基因，并探索其与PTC临床表型的可能关系。最后，收集额外的甲状腺组织样本以验证上述结果。
在分析来自癌症基因组图谱的PTC患者的RNA测序数据后，发现497个差异表达的PTC基因与HT相关，其中蛋白酪氨酸磷酸酶受体C型（PTPRC）、KIT和I型胶原蛋白α1（COL1A1）与肿瘤大小和淋巴结转移相关（p<0.05）。用另外30例临床PTC患者的甲状腺组织对这些结果进行验证，结果显示伴有HT的PTC组中PTPRC的表达水平高于不伴有HT的PTC组（p<0.05），并且ROC曲线显示出良好的区分度（曲线下面积=0.846）。然而，与临床表型的相关性无统计学意义（p>0.05）。
这些数据表明，PTPRC的上调增加了与PTC相关的HT的发生率，并且也预示着预后不良。
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