bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2024‒02‒18
nine papers selected by
Lara Paracchini, Humanitas Research

  1. Med J Aust. 2024 Feb 14.
      Ovarian cancer remains the most lethal gynaecological malignancy with 314 000 cases and 207 000 deaths annually worldwide. Ovarian cancer cases and deaths are predicted to increase in Australia by 42% and 55% respectively by 2040. Earlier detection and significant downstaging of ovarian cancer have been demonstrated with multimodal screening in the largest randomised controlled trial of ovarian cancer screening in women at average population risk. However, none of the randomised trials have demonstrated a mortality benefit. Therefore, ovarian cancer screening is not currently recommended in women at average population risk. More frequent surveillance for ovarian cancer every three to four months in women at high risk has shown good performance characteristics and significant downstaging, but there is no available information on a survival benefit. Population testing offers an emerging novel strategy to identify women at high risk who can benefit from ovarian cancer prevention. Novel multicancer early detection biomarker, longitudinal multiple marker strategies, and new biomarkers are being investigated and evaluated for ovarian cancer screening. Risk-reducing salpingo-oophorectomy (RRSO) decreases ovarian cancer incidence and mortality and is recommended for women at over a 4-5% lifetime risk of ovarian cancer. Pre-menopausal women without contraindications to hormone replacement therapy (HRT) undergoing RRSO should be offered HRT until 51 years of age to minimise the detrimental consequences of premature menopause. Currently risk-reducing early salpingectomy and delayed oophorectomy (RRESDO) should only be offered to women at increased risk of ovarian cancer within the context of a research trial. Pre-menopausal early salpingectomy is associated with fewer menopausal symptoms and better sexual function than bilateral salpingo-oophorectomy. A Sectioning and Extensively Examining the Fimbria (SEE-FIM) protocol should be used for histopathological assessment in women at high risk of ovarian cancer who are undergoing surgical prevention. Opportunistic salpingectomy may be offered at routine gynaecological surgery to all women who have completed their family. Long term prospective opportunistic salpingectomy studies are needed to determine the effect size of ovarian cancer risk reduction and the impact on menopause.
    Keywords:  Mass screening; Ovarian neoplasms; Preventive medicine
  2. Gynecol Oncol Rep. 2024 Feb;51 101330
      Given the tubal origin of high-grade serous ovarian cancer (HGSC), we sought to investigate intrauterine lavage (IUL) as a novel method of biomarker detection. IUL and serum samples were collected from patients with HGSC or benign pathology. Although CA-125 and HE4 concentrations were significantly higher in IUL samples compared to serum, they were similar between IUL samples from patients with HGSC vs benign conditions. In contrast, CA-125 and HE4 serum concentrations differed between HGSC and benign pathology (P =.002 for both). IUL and tumor samples from patients with HGSC were subjected to targeted panel sequencing and droplet digital PCR (ddPCR). Tumor mutations were found in 75 % of matched IUL samples. Serum CA-125 and HE4 biomarker levels allowed for better differentiation of HGSC and benign pathology compared to IUL samples. We believe using IUL for early detection of HGSC requires optimization, and current strategies should focus on prevention until early detection strategies improve.
    Keywords:  Early detection; Intrauterine lavage; Ovarian cancer
  3. bioRxiv. 2024 Jan 29. pii: 2024.01.26.577350. [Epub ahead of print]
      Despite ovarian cancer being the deadliest gynecological malignancy, there has been little change to therapeutic options and mortality rates over the last three decades. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes but are limited by a lack of spatial understanding. We performed multiplexed ion beam imaging (MIBI) on 83 human high-grade serous carcinoma tumors - one of the largest protein-based, spatially-intact, single-cell resolution tumor datasets assembled - and used statistical and machine learning approaches to connect features of the TIME spatial organization to patient outcomes. Along with traditional clinical/immunohistochemical attributes and indicators of TIME composition, we found that several features of TIME spatial organization had significant univariate correlations and/or high relative importance in high-dimensional predictive models. The top performing predictive model for patient progression-free survival (PFS) used a combination of TIME composition and spatial features. Results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.
  4. NPJ Precis Oncol. 2024 Feb 14. 8(1): 34
      Reversion mutations that restore wild-type function of the BRCA gene have been described as a key mechanism of resistance to Poly(ADP-ribose) polymerase (PARP) inhibitor therapy in BRCA-associated cancers. Here, we report a case of a patient with metastatic castration-resistant prostate cancer (mCRPC) with a germline BRCA2 mutation who developed acquired resistance to PARP inhibition. Extensive genomic interrogation of cell-free DNA (cfDNA) and tissue at baseline, post-progression, and postmortem revealed ten unique BRCA2 reversion mutations across ten sites. While several of the reversion mutations were private to a specific site, nine out of ten tumors contained at least one mutation, suggesting a powerful clonal selection for reversion mutations in the presence of therapeutic pressure by PARP inhibition. Variable cfDNA shed was seen across tumor sites, emphasizing a potential shortcoming of cfDNA monitoring for PARPi resistance. This report provides a genomic portrait of the temporal and spatial heterogeneity of prostate cancer under the selective pressure of a PARP inhibition and exposes limitations in the current strategies for detection of reversion mutations.
  5. Biomed Eng Online. 2024 Feb 12. 23(1): 18
      BACKGROUND AND AIM: Ovarian cancer (OC) is a prevalent and aggressive malignancy that poses a significant public health challenge. The lack of preventive strategies for OC increases morbidity, mortality, and other negative consequences. Screening OC through risk prediction could be leveraged as a powerful strategy for preventive purposes that have not received much attention. So, this study aimed to leverage machine learning approaches as predictive assistance solutions to screen high-risk groups of OC and achieve practical preventive purposes.MATERIALS AND METHODS: As this study is data-driven and retrospective in nature, we leveraged 1516 suspicious OC women data from one concentrated database belonging to six clinical settings in Sari City from 2015 to 2019. Six machine learning (ML) algorithms, including XG-Boost, Random Forest (RF), J-48, support vector machine (SVM), K-nearest neighbor (KNN), and artificial neural network (ANN) were leveraged to construct prediction models for OC. To choose the best model for predicting OC, we compared various prediction models built using the area under the receiver characteristic operator curve (AU-ROC).
    RESULTS: Current experimental results revealed that the XG-Boost with AU-ROC = 0.93 (0.95 CI = [0.91-0.95]) was recognized as the best-performing model for predicting OC.
    CONCLUSIONS: ML approaches possess significant predictive efficiency and interoperability to achieve powerful preventive strategies leveraging OC screening high-risk groups.
    Keywords:  Machine learning; Ovarian cancer; Predictive efficiency; Preventive strategy; Public health challenge
  6. JAMA Netw Open. 2024 Feb 05. 7(2): e2356078
      Importance: The current method of BRCA testing for breast and ovarian cancer prevention, which is based on family history, often fails to identify many carriers of pathogenic variants. Population-based genetic testing offers a transformative approach in cancer prevention by allowing for proactive identification of any high-risk individuals and enabling early interventions.Objective: To assess the lifetime incremental effectiveness, costs, and cost-effectiveness of population-based multigene testing vs family history-based testing.
    Design, Setting, and Participants: This economic evaluation used a microsimulation model to assess the cost-effectiveness of multigene testing (BRCA1, BRCA2, and PALB2) for all women aged 30 to 35 years compared with the current standard of care that is family history based. Carriers of pathogenic variants were offered interventions, such as magnetic resonance imaging with or without mammography, chemoprevention, or risk-reducing mastectomy and salpingo-oophorectomy, to reduce cancer risk. A total of 2000 simulations were run on 1 000 000 women, using a lifetime time horizon and payer perspective, and costs were adjusted to 2022 US dollars. This study was conducted from September 1, 2020, to December 15, 2023.
    Main Outcomes and Measures: The main outcome measure was the incremental cost-effectiveness ratio (ICER), quantified as cost per quality-adjusted life-year (QALY) gained. Secondary outcomes included incremental cost, additional breast and ovarian cancer cases prevented, and excess deaths due to coronary heart disease (CHD).
    Results: The study assessed 1 000 000 simulated women aged 30 to 35 years in the US. In the base case, population-based multigene testing was more cost-effective compared with family history-based testing, with an ICER of $55 548 per QALY (95% CI, $47 288-$65 850 per QALY). Population-based multigene testing would be able to prevent an additional 1338 cases of breast cancer and 663 cases of ovarian cancer, but it would also result in 69 cases of excess CHD and 10 excess CHD deaths per million women. The probabilistic sensitivity analyses show that the probability that population-based multigene testing is cost-effective was 100%. When the cost of the multigene test exceeded $825, population-based testing was no longer cost-effective (ICER, $100 005 per QALY; 95% CI, $87 601-$11 6323).
    Conclusions and Relevance: In this economic analysis of population-based multigene testing, population-based testing was a more cost-effective strategy for the prevention of breast cancer and ovarian cancer when compared with the current family history-based testing strategy at the $100 000 per QALY willingness-to-pay threshold. These findings support the need for more comprehensive genetic testing strategies to identify pathogenic variant carriers and enable informed decision-making for personalized risk management.