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Updated: Jun 15, 2025

Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
Published on: September 19, 2018
Expression characteristics of TBC1D4 activating protein molecule and identification of key module genes for
Na Wu1, Zuoqian Jing2, Huina Lv3
1Department of Infectious Diseases, The First Hospital of China Medical University, Shenyang, Liaoning 110001, China.
Abstract:
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.
Insights
Thyroid cancer progression may be hindered by identifying key genes. This study found that ARHGAP6, TBC1D4, and TC2N are important genes for thyroid cancer prevention.
Area of Science:
- Endocrinology
- Molecular Biology
- Bioinformatics
Background:
- Thyroid carcinoma incidence is rising, lacking effective predictive biomarkers.
- Understanding molecular mechanisms is crucial for thyroid cancer prevention.
- TBC1D4 protein is involved in cell metabolism and signal transduction.
Purpose of the Study:
- Investigate TBC1D4 expression characteristics.
- Identify key genes and networks for preventing thyroid cancer progression.
- Elucidate molecular mechanisms in thyroid cancer.
Main Methods:
- Downloaded and analyzed Gene Expression Omnibus (GEO) dataset GSE65144.
- Utilized R package "limma" to identify differentially expressed genes (DEGs).
- Applied Weighted Gene Co-expression Network Analysis (WGCNA) to construct gene networks and identify hub genes.
- Performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis.
- Used Lasso regression and GEPIA database for gene validation and survival analysis.
Main Results:
- Identified 3220 DEGs in thyroid cancer.
- Key gene modules associated with thyroid cancer were darkred, darkturquoise, and green.
- Venn diagram analysis revealed 639 overlapping hub genes.
- KEGG pathway analysis highlighted "Cytokine-cytokine receptor interaction" as a primary pathway.
- Identified 14 key hub genes, with ARHGAP6, TBC1D4, and TC2N being particularly significant.
Conclusions:
- ARHGAP6, TBC1D4, and TC2N are identified as crucial genes in thyroid cancer progression.
- Gene screening and functional enrichment analysis provide insights into TBC1D4-related mechanisms.
- The study constructed a protein-protein interaction network for identified key genes.
- Findings contribute to understanding molecular mechanisms for thyroid cancer prevention and biomarker development.
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