Identification of Gene Coexpression Modules and Prognostic Genes Associated with Papillary Thyroid Cancer.

ABSTRACT: Thyroid cancer is a great part of the endocrine tumor with an increasing incidence. Papillary thyroid carcinoma (PTC) is the most common subtype. With the enormous pace taken in the microarray technology, bioinformatics is applied in data mining more frequently. Weighted gene coexpression network analysis (WGCNA) can perform analysis combining clinic information. We performed WGCNA for prognostic genes associated with PTC. From the GEO profile, we got ten modules. We identified a key module that was closest to patients' survival time. Then, we screened five hub genes (ATRX, BOD1L1, CEP290, DCAF16, and NEK1) from the key module based on the clinical information from TCGA. These five genes not only significantly differ between the normal and tumor groups but have prognostic value. The receiv

SUBMITTER: Shen Y 

PROVIDER: S-EPMC9553521 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature