Identification of candidate genes associated with papillary thyroid carcinoma pathogenesis and progression by weighted gene co-expression network analysis

BACKGROUND: The genes and genetic mechanisms underlying the occurrence and progression of papillary thyroid carcinoma (PTC) are still unknown. This study aimed to find candidate genes related to the pathogenesis and progression of PTC. METHODS: RNA sequencing (RNA-seq) data of PTC and normal tissues were downloaded from The Cancer Genome Atlas (TCGA) database with clinical stage data to form a test, validation, and clinical-stage data matrix. We used the test data set to analyze differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) to find those gene clusters highly correlated with PTC. We then verified the expression of genes in the interested modules using the validation matrix. The quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the reliability of the expression of selected genes. Five key genes (GDF15, LCN2, KCNN4, SH3BGRL3, and MMP2) were used to analyze the connection between gene expression and the American Joint Committee on Cancer (AJCC) stage. The upregulated and downregulated DEGs, along with the modules of interest, were subjected to Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). RESULTS: We used WGCNA to find two modules of interest, the yellow module, which was positively associated with PTC, and the blue module, which was negatively correlated with PTC. Four genes (GDF15, LCN2, KCNN4, and SH3BGRL3) from the yellow module were determined to be highly expressed in PTC in the test data matrix and were verified in both the validation data matrix and quantitative real-time PCR, which indicated that these four genes were highly correlated with the occurrence of the PTC. Furthermore, these four genes also had a significantly higher expression in the advanced levels of pathological T, N, and AJCC stage, meaning that they were correlated with the progression of PTC. Genes in the yellow module and upregulated DEGs were significantly enriched in three vital signaling pathways, including focal adhesion, extracellular matrix (ECM)-receptor interaction, and the PI3K-Akt signaling pathway. CONCLUSIONS: Four candidate genes (GDF15, LCN2, KCNN4, and SH3BGRL3) may be potential biomarkers for the PTC’s pathogenesis and may be useful for predicting the disease stage.