Genetic and Epigenetic Association of FOXP3 with Papillary Thyroid Cancer Predisposition.
Charoula AchillaAngeliki ChortiTheodosios PapavramidisLefteris AngelisAnthoula ChatzikyriakidouPublished in: International journal of molecular sciences (2024)
Papillary thyroid cancer (PTC) is the most common type of thyroid malignancy with an increased female incidence ratio. The specific traits of X chromosome inheritance may be implicated in gender differences of PTC predisposition. The aim of this study was to investigate the association of two X-linked genes, Forkhead Box P3 ( FOXP3 ) and Protein Phosphatase 1 Regulatory Subunit 3F ( PPP1R3F ), with PTC predisposition and gender disparity. One hundred thirty-six patients with PTC and an equal number of matched healthy volunteers were enrolled in the study. Genotyping for rs3761548 ( FOXP3 ) and rs5953283 ( PPP1R3F ) was performed using polymerase chain reaction-restriction fragment length polymorphism assay (PCR-RFLP). The methylation status of FOXP3 was assessed using the combined bisulfite restriction analysis (COBRA) method. The SPSS software was used for statistical analyses. Gender stratification analysis revealed that the CA and AA genotypes and the A allele of FOXP3 rs3761548 variant are associated with PTC predisposition only in females. Moreover, different methylation status was observed up to the promoter locus of FOXP3 between PTC female patients, carrying the CA and CC genotype, and controls. Both revealed associations may explain the higher PTC incidence in females through reducing FOXP3 expression as reported in immune related blood cells.
Keyphrases
- papillary thyroid
- regulatory t cells
- lymph node metastasis
- genome wide
- dna methylation
- transcription factor
- dendritic cells
- end stage renal disease
- gene expression
- risk factors
- single cell
- chronic kidney disease
- peritoneal dialysis
- binding protein
- ejection fraction
- mental health
- newly diagnosed
- poor prognosis
- protein kinase
- induced apoptosis
- prognostic factors
- small molecule
- cell death
- squamous cell
- data analysis