Noninvasive Cell Population Profiling of Normal and Dysplastic Cervical Biofluids by Multicolor Flow Cytometry as a Promising Tool for Companion Diagnostics

TL;DR

This study shows that multicolor flow cytometry can analyze cervical biofluids to detect changes in cell populations across different stages of cervical cancer, offering a potential new diagnostic tool.

Contribution

The study introduces a noninvasive method using multicolor flow cytometry for profiling cervical cell populations in biofluids as a companion diagnostic tool.

Findings

Cervical biofluids can be subdivided into epithelial and immune cell populations using biomarkers like EpCAM, cytokeratin 8, and CD45.

Cellular composition changes with disease stage, with treated cancers showing reduced squamous epithelial cells and increased immune cells.

The method shows potential for monitoring tumor development, progression, and treatment outcomes.

Abstract

Cervical biofluids collected during routine Pap smears contain a mixture of epithelial and immune cells that reflect cervical health and disease. This study demonstrates proof-of-concept that multicolor flow cytometry can be applied to these samples to identify and characterize cell populations in normal cervical samples as well as in different stages of cervical cancer. Our analysis identified major cell populations, including different types of epithelial cells and immune cells, and revealed that their composition within the samples changes with disease stage. We observed variability in both cellular composition and marker expression, highlighting the need for additional markers and larger patient cohorts. Nonetheless, this minimally invasive approach could potentially be used to monitor tumor cells, immune responses, and therapeutic outcomes over time.

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.

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