Luca Beltrame

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.

Genome-wide Copy-number Alterations in Circulating Tumor DNA as a Novel Biomarker for Patients with High-grade Serous Ovarian Cancer

Abstract Purpose: High-grade serous epithelial ovarian cancer (HGS-EOC) is defined by high levels of somatic copy-number alterations (SCNA) with marked spatial and temporal tumor heterogeneity. Biomarkers serving to monitor drug response and detect disease recurrence are lacking, a fact which reflects an unmet clinical need. Experimental Design: A total of 185 plasma samples and 109 matched tumor biopsies were collected from 46 patients with HGS-EOC, and analyzed by shallow whole-genome sequencing (sWGS). The percentage of tumor fraction (TF) in the plasma was used to study the biological features of the disease at the time of diagnosis (T0) and correlated with patients' survival. Longitudinal analysis of TF was correlated with CA-125 levels and radiological images to monitor disease recurrence. Results: Gain in the clonal regions, 3q26.2 and 8q24.3, was observed in the 87.8% and 78.05% of plasma samples, suggesting that plasma sWGS mirrors solid biopsies. At T0, multivariate analysis revealed that plasma TF levels were an independent prognostic marker of relapse (P < 0.022). After platinum (Pt)-based treatment, circulating tumor DNA (ctDNA) analysis showed a change in the heterogeneous pattern of genomic amplification, including an increased frequency of amplification, compared with before Pt-based treatment in the 19p31.11 and 19q13.42 regions. TF in serially collected ctDNA samples outperformed CA-125 in anticipating clinical and radiological progression by 240 days (range, 37–491). Conclusions: Our results support the notion that sWGS is an inexpensive and useful tool for the genomic analysis of ctDNA in patients with HGS-EOC to monitor disease evolution and to anticipate relapse better than serum CA-125, the routinely used clinical biomarker. See related commentary by Dhani, p. 2372

The miR–181a–SFRP4 Axis Regulates Wnt Activation to Drive Stemness and Platinum Resistance in Ovarian Cancer

Abstract Wnt signaling is a major driver of stemness and chemoresistance in ovarian cancer, yet the genetic drivers that stimulate its expression remain largely unknown. Unlike other cancers, mutations in the Wnt pathway are not reported in high-grade serous ovarian cancer (HGSOC). Hence, a key challenge that must be addressed to develop effective targeted therapies is to identify nonmutational drivers of Wnt activation. Using an miRNA sensor-based approach, we have identified miR-181a as a novel driver of Wnt/β-catenin signaling. miR-181ahigh primary HGSOC cells exhibited increased Wnt/β-catenin signaling, which was associated with increased stem-cell frequency and platinum resistance. Consistent with these findings, inhibition of β-catenin decreased stem-like properties in miR-181ahigh cell populations and downregulated miR-181a. The Wnt inhibitor SFRP4 was identified as a novel target of miR-181a. Overall, our results demonstrate that miR-181a is a nonmutational activator of Wnt signaling that drives stemness and chemoresistance in HGSOC, suggesting that the miR–181a–SFRP4 axis can be evaluated as a novel biomarker for β-catenin–targeted therapy in this disease. Significance: These results demonstrate that miR-181a is an activator of Wnt signaling that drives stemness and chemoresistance in HGSOC and may be targeted therapeutically in recurrent disease.

Copy number alterations in stage I epithelial ovarian cancer highlight three genomic patterns associated with prognosis

Stage I epithelial ovarian cancer (EOC) encompasses five histologically different subtypes of tumors confined to the ovaries with a generally favorable prognosis. Despite the intrinsic heterogeneity, all stage I EOCs are treated with complete resection and adjuvant therapy in most of the cases. Owing to the lack of robust prognostic markers, this often leads to overtreatment. Therefore, a better molecular characterization of stage I EOCs could improve the assessment of the risk of relapse and the refinement of optimal treatment options. 205 stage I EOCs tumor biopsies with a median follow-up of eight years were gathered from two independent Italian tumor tissue collections, and the genome distribution of somatic copy number alterations (SCNAs) was investigated by shallow whole genome sequencing (sWGS) approach. Despite the variability in SCNAs distribution both across and within the histotypes, we were able to define three common genomic instability patterns, namely stable, unstable, and highly unstable. These patterns were based on the percentage of the genome affected by SCNAs and on their length. The genomic instability pattern was strongly predictive of patients' prognosis also with multivariate models including currently used clinico-pathological variables. The results obtained in this study support the idea that novel molecular markers, in this case genomic instability patterns, can anticipate the behavior of stage I EOC regardless of tumor subtype and provide valuable prognostic information. Thus, it might be propitious to extend the study of these genomic instability patterns to improve rational management of this disease.

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.