Identification of potential functional genes in papillary thyroid cancer by co‑expression network analysis

Abstract

Interactions between multiple genes are involved in the development of complex diseases. However, there are few analyses of gene interactions associated with papillary thyroid cancer (PTC). Weighted gene co-expression network analysis (WGCNA) is a novel and powerful method that detects gene interactions according to their co-expression similarities. In the present study, WGCNA was performed in order to identify functional genes associated with PTC using R package. First, differential gene expression analysis was conducted in order to identify the differentially expressed genes (DEGs) between PTC and normal samples. Subsequently, co-expression networks of the DEGs were constructed for the two sample groups, respectively. The two networks were compared in order to identify a poorly preserved module. Concentrating on the significant module, validation analysis was performed to confirm the identified genes and combined functional enrichment analysis was conducted in order to identify more functional associations of these genes with PTC. As a result, 1062 DEGs were identified for network construction. A brown module containing 118 highly related genes was selected as it exhibited the lowest module preservation. After validation analysis, 61 genes in the module were confirmed to be associated with PTC. Following the enrichment analysis, two PTC-related pathways were identified: Wnt signal pathway and transcriptional misregulation in cancer. LRP4, KLK7, PRICKLE1, ETV4 and ETV5 were predicted to be candidate genes regulating the pathogenesis of PTC. These results provide novel insights into the etiology of PTC and the identification of potential functional genes.

<p>Exploration of the Potential Biomarkers of Papillary Thyroid Cancer (PTC) Based on RT² Profiler PCR Arrays and Bioinformatics Analysis</p>

“…KEGG pathway analysis indicated that these genes were enriched in pathways in cancer, which is similar to other researches. 36 In our results, the transcriptional misregulation pathway seemed to be especially different, which corresponds to our GO analysis results which presented that it may exert important functions in PTC. And a PPI network with 13 nodes of these genes was further constructed.…”

“…Hence to further investigate the functional relevance of the identified genes in disease, functional annotation and enrichment analyses were very important. 36 In this study, in addition to combining the two methods to screen out more accurate differential gene expression analysis, a total of 29 DEGs screened by these two methods were used to establish a co-expression network for PTC samples. Exploring gene-gene interactions among these networks may help to identify pathways of dissonance in the disease process.…”

MYCT1 Inhibits the Adhesion and Migration of Laryngeal Cancer Cells Potentially Through Repressing Collagen VI

“…WGCNA is an innovative statistical tool used to cluster sets of genes with similar expression patterns and to analyze the correlation between genes and clinical features. WGCNA has been widely used in the analysis of cancer, such as lung ( 24 ), breast ( 25 ), colorectal ( 26 ), liver ( 27 ), thyroid ( 28 ), and HNSCC ( 29 – 31 ). However, WGCNA-related studies on laryngeal cancer metastasis have seldom been reported.…”

Gene Expression Patterns Unveil New Insights in Papillary Thyroid Cancer

“…These findings were also verified through functional and pathway enrichment analyses. Comparing the gene–gene and gene–miRNA interactions of the genes exhibiting an altered expression level is a useful method for both discerning dysregulated pathways in the process of the disease [15] and pointing out the crosstalk between signaling pathways, as can be seen in Figure 2. Expanding evidence shows that p53 family members lead to the advancement of thyroid cancer [16], and our research also identified activated genes related to this signaling pathway.…”