The Gene Expression Profile of Patients with Anaplastic Thyroid Cancer Based on Chip Data Mining

Abstract

Background: Epidemiological research indicates that the incidence of thyroid cancer has increased
each year over the past decade, and the etiology of anaplastic thyroid cancer is complex and includes
environmental and genetic factors. However, its exact pathogenesis remains unclear.
Objective: To investigate the pathogenesis of anaplastic thyroid carcinoma (ATC) with data mining
techniques, and to screen for potential biomarkers to facilitate the early diagnosis and treatment of
ATC.
Design: Gene microarray data from the thyroid tissue of patients with ATC and from healthy controls
were obtained from the Gene Expression Omnibus database.
Setting: we searched the Gene Expression Omnibus (GEO) in PubMed, and downloaded the
GSE53072 chip data.
Method: R, STRING, Network Analyst and Genclip were used to analyze the gene expression
profile, gene function and protein-protein interaction network, and to screen for the key genes that
affect thyroid cancer
Main outcome measure: The gene expression profile of thyroid tissue in the ATC group was
significantly different from the healthy group.
Sample size: It consisted of nine human thyroid tissue samples comprising four normal tissues and
five samples from patients with ATC
Results: The top 100 differentially expressed genes in thyroid tissue were mainly related to thyroid
hormone production and metabolism, and iodoperoxidase activity.