Novel methodology for the digital analysis of circulating tumor cells in ovarian cancer

Purpose Ovarian cancer (OC) is the deadliest gynecological cancer, with late-stage diagnosis and frequent relapse. Improved monitoring tools are urgently needed. Circulating tumor cells (CTCs) are promising biomarkers, but current immunostaining methods are not sensitive enough. This study aimed to develop an ultrasensitive digital PCR (dPCR) assay and define a gene expression signature to track tumor burden and recurrence. Methods We identified candidate mRNA markers using in silico analysis and literature review. Sensitivity was evaluated using spike-in experiments, where ovarian cancer cell lines (OVCAR-3, OVCAR-5, IGROV-1) were added to 3 mL of healthy donor blood at defined numbers (0, 5, 10 or 100). CTCs were isolated with the CD-Prime platform, followed by RNA extraction, reverse transcription, and dPCR quantification. A four-gene panel ( EpCAM, FOLR1, WFDC2, PPIC ) was optimized based on performance. Although SLC34A2 showed limited sensitivity in clinical samples, it was retained for technical compatibility due to co-amplification with WFDC2 . The assay was then tested in paired pre- and postoperative blood samples from five patients with high-grade serous OC and five healthy controls. Results Spike-in experiments confirmed assay sensitivity, with no markers detected in 0-cell controls and significant detection at 100-cell samples (p < 0.05). All patient samples tested positive for at least one marker at both time points, while all controls remained negative. Conclusion The RNA-based four-gene dPCR panel enables highly sensitive detection of CTCs in OC. Its ability to detect CTCs pre- and postoperatively supports its potential as a non-invasive tool for monitoring and early relapse detection.