Systems biology perspective of gender biases in papillary thyroid cancer diagnosis, prognosis and therapy

Abstract

Papillary thyroid cancer (PTC) represents the most prevalent form of thyroid malignancy, and its early detection holds paramount importance for effective treatment. Numerous factors, including age, gender, and exposure to radiation, can contribute to an increased risk of thyroid cancer. Although thyroid cancer can manifest at any age, women in their 40s or 50s face a higher risk compared to men, who typically present with the disease in their 60s or 70s. Additionally, thyroid cancer occurs approximately three times more frequently in women than in men. This study endeavors to elucidate the potential biomolecular signatures responsible for the gender disparity observed in PTC patients. To achieve this, four microarray datasets containing normal thyroid and PTC samples were utilized to identify gene expression signatures. Through a meta-analysis, common differentially expressed genes were discerned independently for both genders. Reporter molecules were then determined by mapping mRNA expression data across various biological levels, including transcriptional regulatory networks, protein-protein interactions, and metabolic pathways. Functional enrichment analysis was subsequently employed to identify relevant biological processes, molecular functions, signaling pathways, and metabolic routes. The study further explored the prognostic potential of the identified reporter molecules through survival analyses. Consequently, this investigation reports candidate biomolecules in each gender cohort that may serve as valuable prognostic biomarkers or potential therapeutic targets for personalized medical interventions in PTC patients.