Department of Infectious Diseases, The First Hospital of China Medical University, Shenyang, Liaoning 110001, China.
Department of Ophthalmology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, China.
Int J Biol Macromol. 2024 Oct;278(Pt 4):134986. doi: 10.1016/j.ijbiomac.2024.134986. Epub 2024 Aug 22.
Endocrine tumors like thyroid carcinoma are becoming more frequent. No clinically informative predictors were found. Thus, effective gene networks and representative biomarkers can illuminate thyroid cancer prevention molecular mechanisms. TBC1D4 is an activating protein molecule that plays an important role in regulating cell metabolism and signal transduction. The aim of this study was to investigate the expression characteristics of TBC1D4 activating protein molecules and identify key module genes that prevent thyroid cancer progression. GSE65144 data were downloaded from GEO. "limma" in R found DEGs with a false discovery rate < 0.05 and a log2 fold change <1. WGCNA builds gene co-expression networks, screens key modules, and filters hub genes. Overlapping genes become hub genes. Hub genes underwent GO and KEGG pathway enrichment analysis. We used Lasso to extract hub gene expression results' distinctive genes. Key genes. GEPIA database determined expression and survival impact. A total of 3220 DEGs. Thyroid cancer was mostly associated with darkred, darkturquoise, and green modules. Venn screened 639 hub genes. Cytokine-cytokine receptor interaction was the primary KEGG enrichment. Hub genes were 14. Finally, ARHGAP6, TBC1D4, and TC2N were important genes. Through gene screening and functional enrichment analysis, we identified a group of genes related to TBC1D4 activating protein and constructed the corresponding protein interaction network.
内分泌肿瘤如甲状腺癌的发病率越来越高，但目前尚未发现具有临床意义的预测指标。因此，有效的基因网络和有代表性的生物标志物可以阐明甲状腺癌预防的分子机制。TBC1D4 是一种激活蛋白分子，在调节细胞代谢和信号转导中起着重要作用。本研究旨在探讨 TBC1D4 激活蛋白分子的表达特征，并鉴定预防甲状腺癌进展的关键模块基因。从 GEO 下载 GSE65144 数据。R 中的“limma”发现具有错误发现率<0.05 和 log2 倍数变化<1 的差异表达基因。WGCNA 构建基因共表达网络，筛选关键模块，并筛选枢纽基因。重叠基因成为枢纽基因。对枢纽基因进行 GO 和 KEGG 通路富集分析。我们使用 Lasso 提取枢纽基因表达结果的特征基因。关键基因。GEPIA 数据库确定表达和生存影响。共 3220 个差异表达基因。甲状腺癌与暗红色、深青色和绿色模块关联最大。Venn 筛选 639 个枢纽基因。细胞因子-细胞因子受体相互作用是主要的 KEGG 富集。枢纽基因 14 个。最后，ARHGAP6、TBC1D4 和 TC2N 是重要基因。通过基因筛选和功能富集分析，我们鉴定了一组与 TBC1D4 激活蛋白相关的基因，并构建了相应的蛋白质相互作用网络。
