Human Wings Apart-Like Protein as a Serum Diagnostic Biomarker in Cervical Cancer: An Integrative Bioinformatics...

Cervical cancer remains a major threat to women's health worldwide, and reliable serum biomarkers for early detection and therapeutic stratification remain limited. Human wings-apart-like (hWAPL) protein has been implicated in cervical carcinogenesis, but its diagnostic and clinical value has not been fully elucidated. To address this gap, this study integrated public multi-omics datasets, including The Cancer Genome Atlas, GEPIA2, the Human Protein Atlas, and single-cell transcriptomic data, to characterize hWAPL expression, clinicopathological associations, immune infiltration, co-expression networks, post-translational modifications, and drug sensitivity predictions. These findings were evaluated in an independent single-center serum cohort comprising 89 patients with histologically confirmed cervical squamous cell carcinoma and 89 healthy female controls. Serum hWAPL and squamous cell carcinoma antigen (SCC) levels were measured, and diagnostic performance was assessed by receiver operating characteristic curve analysis. In silico, hWAPL was broadly upregulated across multiple malignancies, particularly cervical cancer, enriched in malignant epithelial cells and monocytes/macrophages, and associated with shorter progression-free interval, predicted reduced sensitivity to cisplatin, paclitaxel, and 5-fluorouracil, and predicted sensitivity to MCL-1 and Wee1 inhibitors. In the serum cohort, hWAPL levels were significantly higher in patients than controls and discriminated cervical cancer with an area under the curve of 0.961, exceeding SCC alone. Combining hWAPL with SCC further improved diagnostic performance (area under the curve, 0.974; sensitivity, 93.3%; specificity, 95.5%). These findings suggest that serum hWAPL is a potential novel diagnostic biomarker for cervical squamous cell carcinoma whose performance is enhanced by SCC, whereas the observed associations with chemoresistance and immune microenvironment remodeling are hypothesis-generating and require experimental confirmation.