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Integrative transcriptomic identification of potential common biomarkers between non-obstructive azoospermia and
Arash Safarzadeh1, Golfam Sadeghian1, Soudeh Ghafouri-Fard1
1Department of Medical Genetics, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background:
Emerging evidence suggests potential mechanistic links between non-obstructive azoospermia (NOA) and papillary thyroid carcinoma (PTC) through shared signaling pathways. However, no integrative transcriptomic study has systematically examined common molecular signatures between these disorders.
Methods:
We performed transcriptomic analyses using multiple independent public datasets from GEO and TCGA. Differential expression analysis identified shared mRNAs, lncRNAs, and miRNAs between NOA and PTC. Protein-protein interaction networks were constructed followed by hub gene identification. Five machine learning algorithms (LASSO, Random Forest, Boruta, XGBoost, and AdaBoost) were applied for biomarker selection, with subsequent validation in independent cohorts. A competing endogenous RNA (ceRNA) network was constructed, and chemical-gene interactions were explored through the Comparative Toxicogenomics Database.
Results:
We identified 110 shared mRNAs, 37 lncRNAs, and 7 miRNAs with consistent dysregulation patterns between NOA and PTC. Functional enrichment revealed significant associations with cilium-related processes, acrosome reaction, and calcium channel activity. PPI network analysis coupled with machine learning identified CNN1, FBLN1, ITGA6 (for NOA) and AK7, MET, FBLN1, MYH11 (for PTC) as robust biomarkers, with AUC values reaching 0.95 and 0.93, respectively. The MIR222HG/hsa-miR-222-3p/MET|ITGA6 ceRNA axis emerged as a candidate regulatory module. Chemical-gene interaction analysis identified Bisphenol A, Aristolochic Acid I, and Cadmium Chloride as common environmental factors potentially modulating these hub genes.
Conclusions:
This study reveals transcriptomic convergence between NOA and PTC, centered on cilium-associated genes and extracellular matrix remodeling. The identified biomarkers and regulatory networks provide a molecular framework for investigating the reported epidemiological association between male infertility and thyroid cancer risk, while warranting further experimental validation.