Maurizio D’Incalci

Immune evasion mechanisms in early-stage I high-grade serous ovarian carcinoma: insights into regulatory T cell dynamics

Abstract The mechanisms driving immune evasion in early-stage I high-grade serous ovarian carcinoma (HGSOC) remain poorly understood. To investigate this, we performed single-cell RNA-sequencing analysis. Our findings revealed a highly immunosuppressive HGSOC microenvironment, characterized by abundant infiltration of regulatory T cells (Tregs). Trajectory analysis uncovered differentiation pathways of naïve Tregs, which underwent either activation and proliferation or transcriptional instability. The predicted Treg-cell interaction network, including crosstalk within tumor cells, facilitates Treg mobility and maturation while reinforcing their immunosuppressive function and persistence in the tumor. Moreover, their interactions with immune cells likely inhibit CD8 T cells and antigen-presenting cells, supporting tumor immune escape. Additionally, more immunogenic tumor conditions, marked by IFNγ production, may contribute to Treg destabilization. Our findings underscore the pivotal role of Tregs in early immune evasion of HGSOC and provide insights into potential therapeutic strategies targeting their activity and differentiation fate.

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.

TP53 mutations and survival in ovarian carcinoma patients receiving first‐line chemotherapy plus bevacizumab: Results of the MITO16A/MaNGO OV‐2 study

AbstractTo date, there are no biomarkers that define a patient subpopulation responsive to bevacizumab (BEV), an effective treatment option for advanced ovarian carcinoma (OC). In the context of the MITO16A/MaNGO OV‐2 trial, a Phase IV study of chemotherapy combined with BEV in first‐line treatment of advanced OC, we evaluated TP53 mutations by next‐generation sequencing and p53 expression by immunohistochemistry (IHC) on 202 and 311 cases, respectively. We further correlated TP53 mutations in terms of type, function, and site, and IHC data with patients' clinicopathological characteristics and survival. TP53 missense mutations of unknown function (named unclassified) represented the majority of variants in our population (44.4%) and were associated with a significantly improved overall survival (OS) both in univariable (hazard ratio [HR] = 0.43, 95% confidence interval [CI] = 0.20–0.92, p = .03) and multivariable analysis (HR = 0.39, 95% CI = 0.18–0.86, p = .02). Concordance between TP53 mutational analysis and IHC was 91%. We observed an HR of 0.70 for OS in patients with p53 IHC overexpression compared to p53 wild‐type, which however did not reach statistical significance (p = .31, 95% CI = 0.36–1.38). Our results indicate that the presence of unclassified TP53 mutations has favorable prognostic significance in patients with OC receiving upfront BEV plus chemotherapy. In particular, unclassified missense TP53 mutations characterize a subpopulation of patients with a significant survival advantage, independently of clinicopathological characteristics. Our findings warrant future investigations to confirm the prognostic impact of TP53 mutations in BEV‐treated OC patients and deserve to be assessed for their potential predictive role in future randomized clinical studies.

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.