Identification of genes associated with lymph node metastasis in papillary thyroid carcinoma by weighted gene co-expression network analysis

Abstract Background: Thyroid cancer (TC) is the most common endocrine malignant tumor, in which thyroid papillary carcinoma has the highest incidence of (PTC). However, some patients will relapse or even die because of tumor metastasis. Therefore, for the treatment of PTC, it is extremely important to find gene targets and their potential biomarkers. We obtained the RNA sequence matrix of PTC and the clinical information of the corresponding samples in the TCGA database. Methods: The weighted gene co-expression network analysis was utilized to construct the co-expression network, and the gene modules with high correlation among genes and the relationship between genes and clinical traits were established. Results: We utilized the screened 5271 genes for WGCNA analysis and constructed 19 gene modules. Genes in the magenta module with the highest correlation with lymph node metastasis were selected for enrichment analysis to construct a protein interaction network. After that, we selected 12 hub genes of this module by using the intersection of the differential genes in the data set of cytoscape and GEO database. 12 genes were visualized in GEPIA. After that, the gene expression was verified on the oncomine page, and 8 genes with high correlation with TC lymph metastasis (ARNTL, CDH3, CLDN1, COL8A1, COL8A2, IL1RAP, LPAR5) were screened. Conclusion: In this paper, the differential genes are screened by combining the datasets of TCGA, GEO and Oncomine in TC for the first time, which makes the screened differential genes have more biological significance. These genes may offer new insights for the treatment of PTC lymph node metastasis.