# Insights into the role of MSLN-positive circulating tumor cell as an auxiliary diagnostic biomarker in epithelial ovarian cancer

**Authors:** Hang Xu, Min Wang, Shuting Wu, Qinke Li, Jinlong Wang, Siying Zhang, Qiongming Liu, Mengting Wang, Ruifang Li, Zhiyuan Hu, Yi Liu, Zhu Yang

PMC · DOI: 10.3389/fonc.2025.1563095 · Frontiers in Oncology · 2025-07-28

## TL;DR

This study shows that MSLN-positive circulating tumor cells can help distinguish between benign and malignant ovarian tumors, improving diagnostic accuracy when combined with CA125.

## Contribution

MSLN(+)CTCs are introduced as a novel, highly specific biomarker for epithelial ovarian cancer diagnosis.

## Key findings

- MSLN is highly expressed in EOC cells and tissues but not in normal ovarian epithelium.
- MSLN(+)CTCs showed 95% specificity and 66.67% sensitivity in differentiating benign and malignant ovarian lesions.
- Combining MSLN(+)CTCs with CA125 improved diagnostic sensitivity to 92.86% while maintaining 94.74% specificity.

## Abstract

Epithelial ovarian cancer (EOC) currently lacks highly specific biomarkers for clinical screening. This study aimed to identify and validate novel auxiliary diagnostic markers for EOC.

Through integrated analysis of transcriptome sequencing data and single-cell RNA sequencing from public databases, we identified mesothelin (MSLN) as an EOC-specific target. MSLN expression was subsequently validated in EOC cell lines and clinical specimens by flow cytometry, immunofluorescence, and immunohistochemistry. The capture efficacy of Pep@MNPs (Magnetic nanoparticles functionalised with EpCAM peptides) on EOC cells was verified by scanning electron microscopy, Prussian blue staining and cell spiked-blood capture experiments. In a prospective cohort of 35 patients with undiagnosed ovarian masses, we employed immunofluorescence staining to detect MSLN-positive circulating tumor cells (MSLN(+)CTCs) and assessed their diagnostic performance using receiver operating characteristic (ROC) analysis.

MSLN was highly expressed in EOC cell line and tissues but lowly expressed in normal ovarian surface epithelial tissues. EOC cells can be captured by Pep@MNPs with high sensitivity and specificity. ROC curves analysis showed that MSLN(+)CTCs differentiated between benign and malignant lesions of the ovary with a sensitivity of 66.67% and a specificity of 95% (p = 0.0014), which was more specific than cancer antigen 125 (CA125) (sensitivity: 71.43%; specificity: 94.47%; p < 0.0001) and human epididymis protein 4 (HE4) (sensitivity: 84.62%; specificity: 89.47%; p = 0.0002). When MSLN(+)CTCs were combined with CA125, the sensitivity was 92.86% and the specificity was 94.74%, p < 0.0001, which greatly improved the diagnostic sensitivity while preserving high specificity.

MSLN(+)CTCs represent a highly specific auxiliary biomarker for differentiating benign and malignant ovarian lesions. The combination of MSLN(+)CTCs with CA125 provides an optimal balance between sensitivity and specificity, offering promising clinical utility for EOC diagnosis.

## Linked entities

- **Genes:** MSLN (mesothelin) [NCBI Gene 10232]
- **Proteins:** MUC16 (mucin 16, cell surface associated), WFDC2 (WAP four-disulfide core domain 2), MSLN (mesothelin)
- **Diseases:** epithelial ovarian cancer (MONDO:0005140), ovarian cancer (MONDO:0005140)

## Full-text entities

- **Genes:** MUC16 (mucin 16, cell surface associated) [NCBI Gene 94025] {aka CA125}, MSLN (mesothelin) [NCBI Gene 10232] {aka MPF, SMRP}, WFDC2 (WAP four-disulfide core domain 2) [NCBI Gene 10406] {aka BENP, EDDM4, HE4, WAP5, dJ461P17.6}, EPCAM (epithelial cell adhesion molecule) [NCBI Gene 4072] {aka Ber-Ep4, BerEp4, DIAR5, EGP-2, EGP314, EGP40}
- **Diseases:** tumor (MESH:D009369), ovarian lesions (MESH:D010049), EOC (MESH:D000077216), lesions of the ovary (MESH:D010051)
- **Chemicals:** Pep@MNPs (-), Prussian blue (MESH:C000170)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12336444/full.md

## References

45 references — full list in the complete paper: https://tomesphere.com/paper/PMC12336444/full.md

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Source: https://tomesphere.com/paper/PMC12336444