Potential novel modules and hub genes as prognostic candidates of thyroid cancer by weighted gene co-expression network analysis

Abstract

Background: Although thyroid cancer (THCA) is one of the most common type of endocrine malignancy, its highly complex molecular mechanisms of carcinogenesis are not completely known. Materials and Methods: In this study, weighted gene co-expression network analysis (WGCNA) was utilized to construct gene co-expression networks and evaluate the relations between modules and clinical traits to identify potential prognostic biomarkers for THCA patients. RNA-seq data and clinical data were downloaded from The Cancer Genome Atlas (TCGA). Other independent datasets from the Gene Expression Omnibus (GEO) database and the Human Protein Atlas database were performed to validate findings. Results: Finally, 11 co-expression modules were constructed and four hub genes, CCDC146, SLC4A4, TDRD9 and MUM1L1, were identified and validated statistically, which were considerably interrelated to worse survival of THCA patients. Conclusion: This research study revealed four hub genes may be considered candidate prognostic biomarkers and potential therapeutic targets for THCA patients in the future.