Background/Objectives: Cervical Pap smears are routinely used to detect cellular abnormalities as a cervical cancer screening tool and to assess the presence of HPV for risk stratification of the disease. Here, we aimed to extend the applications of this sampling procedure by combining it with multicolor flow cytometry to characterize cell populations across cervical cancer disease stages. Methods: Cervical Pap smears from 30 patients with various disease stages ranging from normal to intraepithelial neoplasia up to treated cancers were analyzed as biofluids using multicolor flow cytometry. Individual samples were evaluated, and statistical analyses were performed over all sample stages. Cancer cell lines (CaSki, SiHa, HeLa, A549, U2OS) were examined as tumor cell controls. Results: Cervical biofluids were subdivided into cell populations according to their scattering properties and the expression of specific biomarkers: EpCAM and cytokeratin 8 for epithelial cells from tumors as well as healthy ectocervical and endocervical regions, and CD45 for immune cells. Discrimination of tumor cells was facilitated with cancer cell lines. Statistical analysis revealed that the composition of cell populations differs among disease stages, whereas treated cancer samples were consistently associated with a reduction in squamous epithelial cells and an increase in immune cells compared to normal samples. Conclusions: Herein, we identified the major cell populations in cervical biofluid samples and demonstrated that this method can detect changes in the cellular composition across different disease stages. This approach could be further exploited in cancer research and potentially serve as a companion diagnostic tool in tumor development, progression and during treatment.
Noninvasive Cell Population Profiling of Normal and Dysplastic Cervical Biofluids by Multicolor Flow Cytometry as a Promising Tool for Companion Diagnostics.
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作者:Berger Christoph, Dietrich Wolf, Richter Manuela, Kellner Florian, Kühne Christian, Strasser Katharina
| 期刊: | Cancers | 影响因子: | 4.400 |
| 时间: | 2025 | 起止号: | 2025 Oct 15; 17(20):3328 |
| doi: | 10.3390/cancers17203328 | ||
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