Laura Mannarino

Genomic instability analysis in DNA from Papanicolaou test provides proof-of-principle early diagnosis of high-grade serous ovarian cancer

Late diagnosis and the lack of screening methods for early detection define high-grade serous ovarian cancer (HGSOC) as the gynecological malignancy with the highest mortality rate. In the work presented here, we investigated a retrospective and multicentric cohort of 250 archival Papanicolaou (Pap) test smears collected during routine gynecological screening. Samples were taken at different time points (from 1 month to 13.5 years before diagnosis) from 113 presymptomatic women who were subsequently diagnosed with HGSOC (pre-HGSOC) and from 77 healthy women. Genome instability was detected through low-pass whole-genome sequencing of DNA derived from Pap test samples in terms of copy number profile abnormality (CPA). CPA values of DNA extracted from Pap test samples from pre-HGSOC women were substantially higher than those in samples from healthy women. Consistently with the longitudinal analysis of clonal pathogenic TP53 mutations, this assay could detect HGSOC presence up to 9 years before diagnosis. This finding confirms the continual shedding of tumor cells from fimbriae toward the endocervical canal, suggesting a new path for the early diagnosis of HGSOC. We integrated the CPA score into the EVA (early ovarian cancer) test, the sensitivity of which was 75% (95% CI, 64.97 to 85.79), the specificity 96% (95% CI, 88.35 to 100.00), and the accuracy 81%. This proof-of-principle study indicates that the early diagnosis of HGSOC is feasible through the analysis of genomic alterations in DNA from endocervical smears.

Multimodal tumor-agnostic ctDNA analysis for minimal residual disease detection and risk stratification in ovarian cancer: results from the MITO16a/MaNGO-OV2 trial

Advanced-stage epithelial ovarian cancer (EOC) remains a therapeutic challenge due to high relapse rates and limited survival, while standard post-surgical parameters such as residual tumor (RT) incompletely capture minimal residual disease (MRD) and offer limited insight into tumor evolution. To address this gap, we investigated whether a multimodal, tumor-agnostic analysis of circulating tumor DNA (ctDNA)-integrating tumor fraction (TF) and genome-wide fragmentomic profiles (PF)-could refine early risk stratification after cytoreductive surgery and enable longitudinal monitoring during therapy. A total of 393 plasma samples from 173 patients in the phase IV MITO16a/MaNGO-OV2a trial were analyzed by shallow whole-genome sequencing at three time points: post-surgery/pre-chemotherapy (B1), post-chemotherapy (B2), and at the end of maintenance therapy or upon disease progression during maintenance (B3). Associations with progression-free survival (PFS) and overall survival (OS) were assessed using multivariable Cox models adjusted for clinical covariates. TF was detectable in 97% of patients at B1, including those classified as optimally debulked, and outperformed established clinical covariates in predicting survival [PFS: hazard ratio (HR) 1.02, P = 0.008; OS: HR 1.04, P = 0.005]. PF provided independent prognostic values (PFS: HR 1.06, P = 0.010; OS: HR 1.10, P = 0.005), and combined TF/PF modeling identified subgroups with distinct survival trajectories beyond clinical predictors (PFS: HR 1.76, P = 0.015; OS: HR 2.06, P = 0.029). Longitudinal copy number profiling revealed dynamic remodeling under treatment pressure, with recurrent 19q13.42 amplification emerging at B2 and B3. Together, these findings establish multimodal ctDNA profiling as a sensitive, non-invasive strategy for MRD detection and longitudinal surveillance in advanced EOC, refining prognostic assessment beyond clinical and surgical factors while paving the way for precision-guided therapeutic management.