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

Content Provider	Europe PMC
Author	Chen, Xiaomin Wang, Ruoyu Xu, Tianze Zhang, Yajing Li, Hongyan Du, Chengcheng Wang, Kun Gao, Zairong
Copyright Year	2021
Abstract	BackgroundThe 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.MethodsRNA 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).ResultsWe 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.ConclusionsFour 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.
ISSN	2218676X
Journal	Translational Cancer Research
Volume Number	10
PubMed Central reference number	PMC8798968
Issue Number	2
PubMed reference number	35116402
e-ISSN	22196803
DOI	10.21037/tcr-20-2866
Language	English
Publisher	AME Publishing Company
Publisher Date	2021-02-01
Access Restriction	Open
Rights License	Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/. 2021 Translational Cancer Research. All rights reserved.
Subject Keyword	Papillary thyroid carcinoma (PTC) weighted gene co-expression network analysis (WGCNA) pathogenesis candidate genes
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Cancer Research Oncology