IRCCS Humanitas Research Hospital & Humanitas University
Published March 9, 2026 | Version v1
Dataset Open

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

Authors/Creators

  • 1. ROR icon Humanitas University
  • 2. ROR icon IRCCS Humanitas Research Hospital
  • 3. ROR icon University of Padua
  • 4. ROR icon University of Campania "Luigi Vanvitelli"
  • 5. Humanitas San Pio X
  • 6. ROR icon Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale"
  • 7. ROR icon European Institute of Oncology
  • 8. ROR icon University of Milano-Bicocca
  • 9. ROR icon Agostino Gemelli University Polyclinic
  • 10. ROR icon Istituto Oncologico Veneto
  • 11. Università degli Studi della Campania Luigi Vanvitelli
  • 12. ROR icon Mario Negri Institute for Pharmacological Research

Description

 This record contains raw data related to article “Multimodal tumor-agnostic ctDNA analysis for minimal residual disease detection and risk stratification in ovarian cancer: results from the MITO16a/MaNGO-OV2 trial"

Abstract

Background: 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 genomewide fragmentomic profiles (PF)―could refine early risk stratification after cytoreductive surgery and enable longitudinal monitoring during therapy.
Materials and methods: 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), postchemotherapyp (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.
Results: 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.
Conclusions: 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.

Files

Paracchini et al 2026 ESMO Open_reference_datasets.pdf

Files (280.8 kB)

Additional details

Related works

Is supplemented by
Publication: 10.1016/j.esmoop.2026.106087 (DOI)
Publication: 41747586 (PMID)