Amjad Elham, Asnaashari Solmaz, Jahanban-Esfahlan Ali, Sokouti Babak
Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Biochem Biophys Rep. 2023 Dec 14;37:101606. doi: 10.1016/j.bbrep.2023.101606. eCollection 2024 Mar.
Papillary thyroid cancer (PTC) is a prevalent kind of thyroid cancer (TC), with the risk of metastasis increasing faster than any other malignancy. So, understanding the role of PTC in pathogenesis requires studying the various gene expressions to find out which particular molecular biomarkers will be helpful. The authors conducted a comprehensive search on the PubMed microarray database and a meta-analysis approach on the remaining ones to determine the differentially expressed genes between PTC and normal tissues, along with the analyses of overall survival (OS) and recurrence-free survival (RFS) rates in patients with PTC. We considered the associated genes with MAPK, Wnt, and Notch signaling pathways. Two GEO datasets have been included in this research, considering inclusion and exclusion criteria. Nineteen genes were found to have higher differences through the meta-analysis procedure. Among them, ten genes were upregulated, and nine genes were downregulated. The expression of 19 genes was examined using the GEPIA2 database, and the Kaplan-Meier plot statistics were used to analyze RFS and the OS rates. We discovered seven significant genes with the validation: PRICKLE1, KIT, RPS6KA5, GADD45B, FGFR2, FGF7, and DTX4. To further explain these findings, it was discovered that the mRNA expression levels of these seven genes and the remaining 12 genes were shown to be substantially linked with the results of the experimental literature investigations on the PTC. Our research found nineteen panels of genes that could be involved in the PTC progression and metastasis and the immune system infiltration of these cancers
乳头状甲状腺癌(PTC)是一种常见的甲状腺癌(TC),其转移风险的增长速度比任何其他恶性肿瘤都要快。因此,了解PTC在发病机制中的作用需要研究各种基因表达,以找出哪些特定的分子生物标志物会有所帮助。作者对PubMed微阵列数据库进行了全面搜索,并对其余数据库采用了荟萃分析方法,以确定PTC与正常组织之间的差异表达基因,同时分析PTC患者的总生存率(OS)和无复发生存率(RFS)。我们考虑了与MAPK、Wnt和Notch信号通路相关的基因。根据纳入和排除标准,本研究纳入了两个GEO数据集。通过荟萃分析程序发现有19个基因存在较高差异。其中,10个基因上调,9个基因下调。使用GEPIA2数据库检测了这19个基因的表达,并使用Kaplan-Meier绘图统计分析RFS和OS率。我们验证了7个显著基因:PRICKLE1、KIT、RPS6KA5、GADD45B、FGFR2、FGF7和DTX4。为了进一步解释这些发现,研究发现这7个基因和其余12个基因的mRNA表达水平与PTC的实验文献研究结果密切相关。我们的研究发现了19组可能参与PTC进展和转移以及这些癌症的免疫系统浸润的基因