F10 Gene Expression and Ethnic Disparities Present in Papillary Thyroid Carcinoma.
Tyrel PorterLilia Y KucheryavykhPublished in: Journal of personalized medicine (2024)
Papillary thyroid carcinoma (PTC) presents a significant health concern, particularly among Hispanic women in the United States, who exhibit a disproportionately higher chance of developing an advanced disease when compared to the non-Hispanic population. Emerging evidence suggests coagulation factor X, encoded by the F10 gene, has a potential role in inhibiting cancer cell migration. However, comprehensive investigations into the differential expression patterns of F10 in Hispanic versus non-Hispanic females remain limited. RNA-sequencing data were acquired from the TCGA database for white female patients, 166 non-Hispanic and 25 Hispanic. A statistically significant ( p < 0.05) 2.06-fold increase in F10 expression levels was detected in disease-free tumors compared to recurrent PTC tumors. Furthermore, an increase in F10 gene expression levels was also observed, corresponding to approximately a 1.74-fold increase in non-Hispanic patients compared to Hispanic patients. The probability of tumor recurrence was 1.82 times higher in the cohort with low expression of F10 compared to the high-expression cohort, correlating with the lower disease-free rates observed in the Hispanic patient cohort when compared to non-Hispanics. This finding underscores the relevance of ethnic disparities in molecular profiles for understanding cancer susceptibility. Identifying F10 as a potential prognostic biomarker highlights avenues for targeted interventions and contributes to improving diagnostic and treatment strategies for diverse patient populations.
Keyphrases
- end stage renal disease
- gene expression
- african american
- chronic kidney disease
- ejection fraction
- poor prognosis
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- dna methylation
- lymph node
- healthcare
- public health
- pregnant women
- lymph node metastasis
- long non coding rna
- single cell
- type diabetes
- squamous cell carcinoma
- genome wide
- mental health
- skeletal muscle
- big data
- physical activity
- machine learning
- drug delivery
- adipose tissue
- health information
- risk assessment
- electronic health record
- copy number
- health insurance
- pregnancy outcomes
- climate change
- single molecule
- cancer therapy
- free survival