Integrated Bioinformatics Analysis of DNA Methylation Biomarkers in Thyroid Cancer Based on TCGA Database

Area of Science:

• Oncology
• Genetics
• Bioinformatics

Background:

• Aberrant promoter methylation is linked to tumor suppressor gene silencing in thyroid cancer (TC).
• Previous studies focused on individual genes, necessitating a broader analysis of methylation changes during TC progression.

Purpose of the Study:

• To investigate the onset and pattern of DNA methylation changes throughout thyroid cancer progression using bioinformatics analysis.
• To identify novel methylation-driven differentially expressed genes (DEGs) and associated pathways as potential biomarkers for TC.

Main Methods:

• Downloaded and analyzed DNA methylation and RNA sequencing data from The Cancer Genome Atlas (TCGA) for TC.
• Identified abnormally methylated DEGs, performed pathway enrichment analysis (KEGG, GO), and constructed gene-drug interaction networks.
• Utilized the Human Protein Atlas to identify feature DNA methylation biomarkers.

Main Results:

• Identified 2170 methylation-driven DEGs (1054 hypermethylated-low-expression, 1116 hypomethylated-high-expression).
• Screened eight feature DNA methylation biomarkers: RXRG, MET, PDGFRA, FCGR3A, VEGFA, CSF1R, FCGR1A, and C1QA.
• Pathway analysis revealed associations with transcriptional misregulation in cancer, MAPK signaling, and intrinsic apoptotic signaling in TC.

Conclusions:

• Novel aberrantly methylated genes and pathways associated with thyroid cancer have been identified.
• These findings suggest potential utility as biomarkers for the precise diagnosis and treatment of TC.
• The study highlights the importance of comprehensive methylation profiling in understanding TC pathogenesis.