bims-ovdlit 2026-05-03 papers

Issue of 2026–05–03
seven papers selected by
Lara Paracchini, Humanitas Research

Int J Gynecol Cancer. 2026 Apr 03. pii: S1048-891X(26)00207-0. [Epub ahead of print]36(6): 104676

Contemporary risk assessment and risk-reducing strategies for tubo-ovarian cancer in women with BRCA pathogenic variants.

David Viveros-Carreño, Isabel Beshar, Nuria Agustí, Ananya Murthy, Nathalia Mora-Soto, Maria D Iniesta, Karla Barajas, Alexander Melamed, J Alejandro Rauh-Hain, Roni Nitecki Wilke.

Tubo-ovarian cancer represents the most lethal gynecologic malignancy, and its burden is compounded by the absence of effective screening and the substantial lifetime risk carried by women with germline BRCA1 or BRCA2 pathogenic variants. While risk-reducing salpingo-oophorectomy remains the standard for prevention, conferring reduction in tubo-ovarian cancer risk and improved overall survival, it also induces premature menopause with significant effects on quality of life and bone, cardiovascular, and sexual health. These consequences have driven the exploration of alternative preventive strategies, and a paradigm shift toward individualized risk assessment. Emerging data highlight that tubo-ovarian cancer risk among BRCA pathogenic variant carriers is not uniform but influenced by gene type, variant position, family history, and modifiable factors such as parity, breastfeeding, and oral contraceptive use. Modern risk models integrate genetic, familial, and lifestyle data to refine personalized estimates and guide the timing of intervention. Concurrently, the understanding that many high-grade serous carcinomas originate in the fallopian tube has prompted evaluation of risk-reducing salpingectomy with delayed oophorectomy as a staged surgical strategy that may balance oncologic safety with preservation of hormonal function. Ultimately, management of BRCA pathogenic variant carriers must combine genomic precision, reproductive planning, and patient-centered counseling to align cancer prevention with quality of life, supporting truly individualized care in hereditary tubo-ovarian cancer risk reduction. Despite several reviews on hereditary tubo-ovarian cancer prevention, a clinically relevant gap remains in translating contemporary evidence into a practical counseling framework for women with BRCA1/2 pathogenic variants. This narrative review aims to synthesize current evidence on tubo-ovarian cancer risk assessment and risk-reducing strategies in this population, with a focus on individualized counseling and shared decision-making.

Keywords: BRCA1 Protein/Genetics; BRCA2 Protein/Genetics; Ovarian Neoplasms; Risk Assessment; Salpingo-Oophorectomy

DOI: https://doi.org/10.1016/j.ijgc.2026.104676

Int J Gynecol Cancer. 2026 Apr 03. pii: S1048-891X(26)00210-0. [Epub ahead of print]36(6): 104679

Decoding BRCA1 and BRCA2 Mutations in High-Grade Serous Ovarian Cancer: Impact of Location and Type of Mutation on Prognosis and PARP Inhibitor Treatment.

Marina Momi, Elisa Salviato, Antonella Ravaggi, Cinzia Mazza, Germana Tognon, Cosetta Bergamaschi, Laura Zanotti, Elisa Gozzini, Valentina Zizioli, Franco Odicino, Eliana Bignotti.

OBJECTIVE: Pathogenic mutations in BRCA1/2 are associated with improved survival in high-grade serous ovarian carcinoma, but the prognostic impact of specific mutations remains unclear. The primary aim of this study was to evaluate the role of different locations, types, and functions of BRCA1/2 mutations on survival in patients with high-grade serous ovarian carcinoma.
METHODS: This study included a total of 174 patients with advanced-stage high-grade serous ovarian cancer, 74 women with BRCA1/2 mutations, and 100 wild-type controls. Mutations were categorized based on gene (BRCA1 vs BRCA2), location (inside exon 11 vs outside; functional domains), type (frameshift, nonsense, missense), and function (truncated protein vs amino acid change). Poly (adenosine diphosphate-ribose) polymerase inhibitor exposure was defined as receipt of maintenance therapy in first or subsequent lines. Survival outcomes were analyzed using univariate and multi-variate models.
RESULTS: In multi-variate analysis, adjusted for residual tumor and International Federation of Gynecology and Obstetrics stage, mutations in BRCA2 RAD51-BD (hazard ratio 0.03, P=.001) and in BRCA1 DNA-binding domain (hazard ratio 0.23, p =.008) were associated with the most favorable prognosis compared to wild type. In contrast, BRCA1 BRCT or RING domain mutations showed survival outcomes similar to wild type. Frameshift (hazard ratio 0.17, p <.001) and nonsense mutations (hazard ratio 0.4, p =.016) were associated with improved survival compared to wild type, whereas missense variants were not. In patients not receiving poly (adenosine diphosphate-ribose) polymerase inhibitors, the presence of a BRCA2 or BRCA1 mutation was an independent marker of improved overall survival (hazard ratio 0.09, p <.001 and hazard ratio 0.37, p =.006, respectively), while the presence of residual tumor (>0) and International Federation of Gynecology and Obstetrics stage IV were associated with worse prognosis (hazard ratio 3.07, p =.001; hazard ratio 1.93, p =.031, respectively). In the poly (adenosine diphosphate-ribose) polymerase inhibitor-treated group, only BRCA2 mutations remained significantly associated with improved overall survival (hazard ratio 0.12, p =.043).
CONCLUSIONS: The prognostic value of BRCA1/2 mutations in high-grade serous ovarian carcinoma may depend on their specific location and type. If validated in larger cohorts, our findings could influence patient stratification and should be considered in future clinical trial design.

Keywords: BRCA1/2 Mutations; Ovarian Carcinoma; Precision Medicine; Prognostic Biomarker

DOI: https://doi.org/10.1016/j.ijgc.2026.104679

Cell Commun Signal. 2026 May 01.

A machine learning framework combining cfDNA fragmentomics and serum biomarkers for early ovarian cancer detection.

Wanying Weng, Qunxian Rao, Song Wang, Ruilin Lei, Ruixin Li, Lin Lin, Yunyun Liu, Dongqin Zhu, Hua Bao, Weijian Zhang, Jihong Wei, Xingrong Qing, Xiaohong Ruan, Guocai Xu, Bingzhong Zhang.

BACKGROUND: Ovarian cancer (OC) is a leading cause of cancer-related mortality in women, largely due to the lack of effective strategies for early detection. Here, we aimed to develop a liquid biopsy assay integrating cell-free DNA (cfDNA) fragmentomic features with serum biomarkers for sensitive OC detection.
METHODS: Plasma cfDNA from training (n = 91) and independent validation (n = 46) cohorts comprising patients with OC, benign ovarian diseases, and healthy controls, underwent low-coverage whole-genome sequencing to extract copy number variation, fragment size distribution, and Neomer features. Fragmentomic features were first integrated using a stacked machine-learning model and subsequently combined with serum biomarkers CA125 and HE4 to construct the final diagnostic model. Model performance was evaluated in the overall cohort and stratified by disease stage, histological subtype, and tumor grade. An external validation cohort (n = 58) was further used to assess model generalizability.
RESULTS: The combined model integrating cfDNA fragmentomic features and serum biomarkers demonstrated superior diagnostic accuracy compared with all alternative approaches. In the independent validation cohort, the model achieved an AUC of 0.968 (95% CI: 0.896-0.996), with 85.7% sensitivity and 96.0% specificity. For early-stage OC (FIGO stage I and II), the model yielded an AUC of 0.938 (95% CI: 0.864-0.988), achieving 72.2% sensitivity at a specificity of 96%. Robust performance was observed across histological subtypes (AUC: 0.925-0.991) and tumor grades (AUC: 0.976-0.977). Stratified analyses further confirmed strong discrimination between OC and healthy controls (AUC: 0.995, 95% CI: 0.980-1.000) as well as benign ovarian diseases (AUC: 0.963, 95% CI: 0.921-0.993). In the external validation cohort, the combined model maintained robust diagnostic performance, achieving an AUC of 0.962 (95% CI: 0.898-0.991), with 86.2% sensitivity at 96% specificity.
CONCLUSIONS: Integrating cfDNA fragmentomics with CA125 and HE4 via machine learning demonstrates strong potential for ovarian cancer detection and clinicopathological subtyping, supporting future evaluation for clinical translation in population screening and preoperative risk assessment.

Keywords: Cell-free DNA; Early diagnosis; Fragmentomics; Ovarian cancer; Serum biomarkers

DOI: https://doi.org/10.1186/s12964-026-02908-x

Nat Commun. 2026 Apr 29.

Spatial-aware detection of copy number alterations from spatial transcriptomics using SpaCNA.

Zihui Zhang, Xiaochen Wang, Hong Xuan, Yan Xu, Zijie Jin, Ruibin Xi.

Spatial transcriptomics (ST) profiles genome-wide gene expression while preserving spatial context, yet accurate detection of copy number alterations (CNAs) in tumor ST data remains challenging. Here, we present SpaCNA, a computational framework that integrates multi-modal information of ST for robust CNA detection. SpaCNA aggregates expression from neighboring spots with similar morphological features and leverages a hidden Markov random field model incorporating spatial continuity for reliable CNA detection in ST datasets. Further, SpaCNA can reconstruct 3D CNA profiles with spatial continuity across consecutive slices when applied to 3D ST datasets. Extensive benchmarking on simulated data and real cancer datasets demonstrates SpaCNA's superior accuracy, achieving up to 0.95 F1-score in CNA detection and tumor region identification. In applications to breast cancer and colorectal cancer, SpaCNA reveals tumor boundaries and spatially distinct subclones with context-dependent interactions within the microenvironment. Notably, SpaCNA performs CNA detection in a 3D ST dataset of head and neck squamous cell carcinoma, revealing the tumor evolution trajectory of three subclones in 3D space. By providing accurate CNA inference, SpaCNA facilitates the analysis of intratumoral heterogeneity and spatial cancer biology.

DOI: https://doi.org/10.1038/s41467-026-72284-0

Nature. 2026 Apr 29.

Evolutionary characterization of lung cancer metastasis.

TRACERx Consortium

Limited understanding of the biological processes that govern metastatic dissemination hinders its prevention and treatment1. Here, using 501 longitudinally collected primary and metastatic tumour samples from 24 patients with non-small cell lung cancer (NSCLC) enrolled in the TRACERx lung study and PEACE autopsy programme, we infer tumour evolution from diagnosis to death. With DNA-sequencing data encompassing 70% of the metastases that were radiologically detected before death and paired multi-region sampled primary tumours, we show that the genomes of metastases diverge markedly from those of their ancestral primary tumour, with additional driver alterations and genome doubling events occurring after metastatic dissemination. In 62.5% of patients, multiple primary tumour subclones disseminated, each founding a distinct metastasis. These metastases served as sources of onward spread: more than half of the metastases sampled were seeded by other metastases. The duration that metastases existed in situ influenced their likelihood of seeding further metastases. Most metastatic migrations started and ended in the same anatomical cavity. The few subclones that exited the thorax to seed metastases disseminated widely and were enriched for somatic copy-number alterations, suggesting that chromosomal instability may facilitate extrathoracic spread. This spatial and temporal evolutionary analysis sheds light on the extent of metastatic diversity and seeding in advanced NSCLC-which tends to be underestimated in single metastasis biopsies-and identifies genomic and clinical mediators of metastatic progression.

DOI: https://doi.org/10.1038/s41586-026-10428-4