Abstract
Background/Aim: Ovarian cancer is predominantly diagnosed in the late stages of the disease. Ascites can be collected before the start of neoadjuvant treatment or during the treatment course and may serve as a potential biological surrogate for tumor tissue (TT), representing metastases located in the peritoneal cavity. The minimally invasive nature of ascites collection makes it an alternative to tumor biopsies. The aim was to investigate ascites samples alongside corresponding fresh frozen TT to clarify the potential of ascites in reflecting the genetic composition of TT. Secondly, we wanted to investigate if ascites can be used as biological material for molecular analyses, predicting possible molecular targets associated with FDA-approved drugs.
Materials and Methods: We used next-generation sequencing, natural language processing, and network analysis to assess the recall of genetic variants between corresponding TT and ascites samples in a cohort of 32 patients with ovarian cancer.
Results: Patients median age was 68.5 years. Seventy two percent were diagnosed at late stage disease. Overall, the analysis showed that 156 (76%) of the identified variants overlapped between ascites and TT. Ascites had 28 (14%) unique identified variants, while TT had 21 (10%). We identified 25 (76%) pathogenic or likely pathogenic variants in TT that were also present in the corresponding ascites sample. Three variants (9%) were unique for the ascites samples, while five (15%) were unique for the TT samples.
Conclusion: We identified all pathogenic and likely pathogenic actionable variants within a clinical perspective in ascites. Clinicians may consider using ascites, particularly for patients with fluid accumulation who are not candidates for surgery at the time of diagnosis.
- Ovarian cancer
- ascites
- ctDNA
- targeted therapeutics
- next-generation sequencing
- bioinformatics
- natural language processing
- Received August 4, 2025.
- Revision received September 11, 2025.
- Accepted October 9, 2025.
- Copyright © 2026 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
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