bims-ovdlit 2024-10-27 papers

Nat Commun. 2024 Oct 21. 15(1): 8801

Cancer treatment monitoring using cell-free DNA fragmentomes.

Circulating cell-free DNA (cfDNA) assays for monitoring individuals with cancer typically rely on prior identification of tumor-specific mutations. Here, we develop a tumor-independent and mutation-independent approach (DELFI-tumor fraction, DELFI-TF) using low-coverage whole genome sequencing to determine the cfDNA tumor fraction and validate the method in two independent cohorts of patients with colorectal or lung cancer. DELFI-TF scores strongly correlate with circulating tumor DNA levels (ctDNA) (r = 0.90, p < 0.0001, Pearson correlation) even in cases where mutations are undetectable. DELFI-TF scores prior to therapy initiation are associated with clinical response and are independent predictors of overall survival (HR = 9.84, 95% CI = 1.72-56.10, p < 0.0001). Patients with lower DELFI-TF scores during treatment have longer overall survival (62.8 vs 29.1 months, HR = 3.12, 95% CI 1.62-6.00, p < 0.001) and the approach predicts clinical outcomes more accurately than imaging. These results demonstrate the potential of using cfDNA fragmentomes to estimate tumor burden in cfDNA for treatment response monitoring and clinical outcome prediction.

DOI: https://doi.org/10.1038/s41467-024-53017-7

J Pathol Clin Res. 2024 Nov;10(6): e70006

Assessing the impact of deep-learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes.

AI‐STIC Study Group

In recent years, it has become clear that artificial intelligence (AI) models can achieve high accuracy in specific pathology-related tasks. An example is our deep-learning model, designed to automatically detect serous tubal intraepithelial carcinoma (STIC), the precursor lesion to high-grade serous ovarian carcinoma, found in the fallopian tube. However, the standalone performance of a model is insufficient to determine its value in the diagnostic setting. To evaluate the impact of the use of this model on pathologists' performance, we set up a fully crossed multireader, multicase study, in which 26 participants, from 11 countries, reviewed 100 digitalized H&E-stained slides of fallopian tubes (30 cases/70 controls) with and without AI assistance, with a washout period between the sessions. We evaluated the effect of the deep-learning model on accuracy, slide review time and (subjectively perceived) diagnostic certainty, using mixed-models analysis. With AI assistance, we found a significant increase in accuracy (p < 0.01) whereby the average sensitivity increased from 82% to 93%. Further, there was a significant 44 s (32%) reduction in slide review time (p < 0.01). The level of certainty that the participants felt versus their own assessment also significantly increased, by 0.24 on a 10-point scale (p < 0.01). In conclusion, we found that, in a diverse group of pathologists and pathology residents, AI support resulted in a significant improvement in the accuracy of STIC diagnosis and was coupled with a substantial reduction in slide review time. This model has the potential to provide meaningful support to pathologists in the diagnosis of STIC, ultimately streamlining and optimizing the overall diagnostic process.

Keywords: STIC; artificial intelligence; computational pathology; deep learning; high‐grade serous carcinoma; histopathology; serous tubal intraepithelial carcinoma

DOI: https://doi.org/10.1002/2056-4538.70006

J Gynecol Oncol. 2024 Oct 21.

Gut microbiome associated with PARP inhibitor efficacy in patients with ovarian cancer.

OBJECTIVE: To investigate an association between the gut microbiome and efficacy of poly(ADP-ribose) polymerase inhibitors (PARPi) in ovarian cancer.
METHODS: This study conducted fecal microbiome analysis (16S rRNA gene sequencing) and circulating tumor DNA (ctDNA) profiling for ovarian cancer patients who underwent PARPi maintenance therapy. Fecal and blood samples were collected at the baseline and the progressive disease (PD) or last follow-up. The relative abundance of gut microbes and progression-free survival (PFS) were analyzed using linear discriminant analysis of effect size and the Cox proportional hazard model according to BRCA1/2 mutation (BRCA1/2mut) status detected by ctDNA sequencing.
RESULTS: Baseline samples were available from 23 BRCA1/2mut-positive patients and 33 BRCA1/2mut-negative patients. The microbes enriched in the baseline samples with long PFS were Bifidobacterium, Roseburia, Dialister, Butyricicoccus, and Bilophila for BRCA1/2mut-positive patients and Phascolarctobacterium for BRCA1/2mut-negative patients. In multivariate analyses dividing patients by the median values of relative abundances, no bacteria were associated with PFS in BRCA1/2mut-positive patients, whereas high Phascolarctobacterium abundances (≥1.11%) was significantly associated with longer PFS in BRCA1/2mut-negative patients (median 14.0 vs. 5.9 months, hazard ratio=0.28; 95% confidence interval=0.11-0.69; p=0.014). In the last samples, the relative abundances of Phascolarctobacterium were significantly higher in patients without PD (n=5) than those with PD (n=15) (median 1.25% vs. 0.06%; p=0.016).
CONCLUSION: High fecal composition of Phascolarctobacterium was associated with prolonged PFS in patients with BRCA1/2mut-negative ovarian cancer receiving PARPi therapy. Our results would provide new insights for future research.

Keywords: Circulating Tumor DNA; Gut Microbiome; Maintenance; Ovarian Cancer; PARP Inhibitor; Progression-Free Survival

DOI: https://doi.org/10.3802/jgo.2025.36.e38

Int J Gynecol Cancer. 2024 Oct 23. pii: ijgc-2024-005497. [Epub ahead of print]

Consensus on drivers of maintenance treatment choice and patterns of care in advanced ovarian cancer.

OBJECTIVES: Maintenance therapies, including poly (ADP-ribose) polymerase (PARP) inhibitors and/or bevacizumab, have substantially improved the prognosis of patients with advanced ovarian cancer. Owing to the variability in treatment strategies across Europe, a Delphi study was conducted among European experts to understand the heterogeneity of clinical practice and identify key factors driving maintenance treatment decisions for advanced ovarian cancer.
METHODS: A pragmatic literature review was conducted to identify key questions regarding maintenance treatment strategies in patients with advanced ovarian cancer. Utilizing a Delphi methodology, consensus was assessed among a panel of 16 experts using a questionnaire based on results of the pragmatic literature review.
RESULTS: Panelists agreed that BRCA mutation and homologous recombination status should be assessed in parallel at diagnosis, and that first-line platinum chemotherapy may be initiated concurrently. There was a consensus that alternative homologous recombination deficiency tests are acceptable provided they are clinically validated. Panelists agreed that Response Evaluation Criteria in Solid Tumors (RECIST) and CA-125 elimination rate constant K (KELIM) scores can help assess tumor chemosensitivity and guide treatment-related decisions. Panelists defined high-risk disease as International Federation of Gynecology and Obstetrics (FIGO) stage IV disease or stage III with residual disease after initial/interval cytoreduction. Risk of disease progression was a key determinant of choice between PARP inhibitor, bevacizumab, or both in combination, as maintenance therapy in advanced ovarian cancer.
CONCLUSIONS: Key drivers for selecting advanced ovarian cancer maintenance treatments include tumor mutational status as a key biomarker and clinician perception of the risk for early disease progression.

Keywords: Ovarian Cancer

DOI: https://doi.org/10.1136/ijgc-2024-005497

Clin Obstet Gynecol. 2024 Dec 01. 67(4): 702-710

Uptake of Cascade Genetic Testing for Hereditary Breast and Ovarian Cancer: A Systematic Review and Meta-Analysis.

Muhammad Danyal Ahsan, Isabelle R Chandler, Samantha Min, Benjamin Grant, Michelle Primiano, Jamieson Greenwald, Tamar N Soussana, Becky Baltich Nelson, Charlene Thomas, Eloise Chapman-Davis, Ravi N Sharaf, Melissa K Frey.

This is a systematic review and meta-analysis evaluating the uptake of cascade genetic testing for hereditary breast and ovarian cancer syndrome. Among 30 studies included for meta-analysis, the uptake of cascade genetic testing was 33% (95% CI 25%-42%), with higher uptake rates among females compared with male relatives, and among first-degree compared with second-degree relatives. These findings indicate suboptimal uptake of cascade genetic testing among people at risk for hereditary breast and ovarian cancer syndrome, representing a missed opportunity for cancer prevention and early detection. There is a need for interventions to improve uptake rates.

DOI: https://doi.org/10.1097/GRF.0000000000000895

Clin Obstet Gynecol. 2024 Dec 01. 67(4): 687-695

The Current State-or Lack Thereof-of Screening and Prevention for Gynecologic Malignancies for Patients With Lynch Syndrome.

Sharonne Holtzman, Madison Cox, Stephanie V Blank.

Lynch syndrome (LS) is an autosomal dominant genetic disorder that results in an increased risk of ovarian and endometrial cancers. The aim of this paper was to explore the management of this risk through screening and prevention. Published materials and evidence were explored and summarized. This paper demonstrated that while there has been increased awareness and advances in the identification and diagnosis of patients with LS, recommendations for screening and prevention remain less evidence-based. In decisions of management of patients with LS, a shared decision-making model should be used considering individual patient goals.

DOI: https://doi.org/10.1097/GRF.0000000000000892