Identification of hub genes in papillary thyroid carcinoma: robust rank aggregation and weighted gene co-expression network analysis

Abstract

Background: Papillary thyroid carcinoma (PTC), which is the most common endocrine malignancy, has been steadily increasing worldwide in incidence over the years, while mechanisms underlying the pathogenesis and diagnostic for PTC are incomplete. The purpose of this study is to identify potential biomarkers for diagnosis of PTC, and provide new insights into pathogenesis of PTC.Methods: Based on weighted gene co-expression network analysis, Robust Rank Aggregation, functional annotation, GSEA and DNA methylation, were employed for investigating potential biomarkers for diagnosis of PTC.Results: Black and turquoise modules were identified in the gene co-expression network constructed by 1807 DEGs that from 6 eligible gene expression profiles of Gene Expression Omnibus database based on Robust Rank Aggregation and weighted gene co-expression network analysis. Hub genes were significantly down-regulated and the expression levels of the hub genes were different in different stages in hub gene verification. ROC curves indicated all hub genes had good diagnostic value for PTC (except for ABCA6 AUC = 89.5%, the 15 genes with AUC > 90%). Methylation analysis showed that hub gene verification ABCA6, ACACB, RMDN1 and TFPI were identified as differentially methylated genes, and the decreased expression level of these genes may relate to abnormal DNA methylation. Moreover, the expression levels of 8 top hub genes were correlated with tumor purity and tumor-infiltrating immune cells. These findings, including functional annotations and GSEA provide new insights into pathogenesis of PTC. Conclusions:The hub genes and methylation of hub genes may as potential biomarkers provide new insights for diagnosis of PTC, and all these findings may be the direction to study the mechanisms underlying of PTC in the future.

PGK1 contributes to tumorigenesis and sorafenib resistance of renal clear cell carcinoma via activating CXCR4/ERK signaling pathway and accelerating glycolysis

“…Hub genes are genes that play crucial roles in biological processes. We constructed the coexpression network of overlapped DEGs to screen KIRC-related hub genes according to previous reports [ 49 , 50 ], and the results showed that both PGK1 and CXCR4 are KIRC-related hub genes and highly expressed in KIRC tissues, and there is a strong interaction between PGK1 and CXCR4. The KIRC clinical samples with high mRNA level of PGK1 often own high mRNA expression of CXCR4 correspondingly.…”

Identification of prognostic biomarkers for papillary thyroid carcinoma by a weighted gene co‐expression network analysis

“…Zhai et al collected data for 10,428 genes and obtained three modules associated with N staging, including 11 recurrence‐related genes 19 . Using the Gene Expression Omnibus (GEO) database, Liu et al screened staging‐related hub genes by WGCNA and further showed that these hub genes were correlated with DNA methylation and tumor‐infiltrating immune cells 20 . Tang et al used WGCNA to identify five hub genes related to the progression of PTC within GSE27155 21 .…”

Upregulation of ATIC in multiple myeloma tissues based on tissue microarray and gene microarrays

“…To identify the differentially expressed mRNA (DEmRNA) in MM, the SVA package was used to remove the batch effect of the microarray data, and microarrays from the same platform were integrated. The Limma package was used for differential expression analysis of the mRNA expression profiles of each platform, and the DEmRNA in MM was obtained by the Robust Rank Aggregation method 15‐18 …”