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Protein Biomarkers Enable Sensitive and Specific Cervical Intraepithelial Neoplasia (CIN) II/III+ Detection: One Step
Samrin F Habbani1, Sayeh Dowlatshahi2, Nathanael Lichti3
1Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA.
Background/Objectives:
Cervical cancer (CC) is a significant global health challenge, particularly in low- and middle-income countries (LMICs), where limited access to human papillomavirus (HPV) vaccination and effective CC screening results in a majority of cases and fatalities among women. Moreover, existing vaccines do not target HPV-independent cancers. Current screening methods are expensive and time-consuming, with a limited emphasis on CC protein biomarkers. Therefore, we aimed to validate critical markers that allow the development of affordable point-of-care screening tests for resource-limited settings.
Methods:
This study first optimized a cell lysis and protein extraction protocol for CC cell lines and clinical cervical swabs. Subsequently, four proteins-topoisomerase II alpha (TOP2A), minichromosome maintenance complex component 2 (MCM2), valosin-containing protein (VCP), and cyclin-dependent kinase inhibitor 2A (p16INK4a)-were quantified in the resulting lysates using enzyme-linked immunosorbent assays, as well as in cervical tumors and squamous intraepithelial lesions (SILs) using immunohistochemistry for further validation.
Results:
Acetone precipitation allowed for efficient cell isolation, and radioimmunoprecipitation assay buffer yielded the highest protein recovery. VCP and p16INK4a were overexpressed across all cancer cell lines compared to primary cells. All four biomarkers were overexpressed in high-grade SIL (HSIL) swab specimens and tumor samples, including CC subtypes, G1-G3 tumor grades, and HSILs. Lastly, we showed that the proteins could accurately classify swabs and tissue specimens into clinically relevant groups.
Conclusions:
The quantitative analysis of these biomarkers, along with the subsequent sensitive and specific clinical classification, highlights their potential application in SIL early detection and CC prevention, particularly in LMICs.

