Identification of key genes involved in papillary thyroid cancer by bioinformatics tools

Abstract

Study Objectives: Thyroid cancer is the sixth most common type of cancer among women worldwide, with an increasing incidence. It is the most common endocrine cancer and it is seen in 1.7% of all cancers. We aimed to detect genes whose expression level varies in this pathology by using gene expression data obtained from papillary thyroid cancer tissue. Methods: Microarray data selected for bioinformatic analysis is Gene Expression data stored with GSE35570 code in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Thyroid cancer and healthy control groups were compared, then variance filtering was applied and as a result, gene lists with different expression levels were obtained between the compared groups. Totally, 1209 genes were differentially expressed between these two groups. Results: We have determined that SFTPB, HMGA2, ARHGAP36, SYTL5, LRRK2, PRR15, DPP4, TENM1, SCEL genes were upregulated in papillary thyroid cancer group and CCL21, COL9A3, FBLN1, LRP1B, PROM1, NEB, CDH16, TFCP2L1 genes were downregulated. Conclusion: We have concluded that these identified genes can be used as candidate biomarker genes for diagnosis of papillary thyroid cancer.