Background Epithelial ovarian cancer (EOC) has a high case-fatality rate, largely due to diagnosis at advanced stages and lack of effective screening tools. Conventional screening tools, like CA125 and ultrasound, have limited sensitivity and specificity. Advances in deep learning (DL) applied to medical imaging such as CT scans offer a promising avenue for improving early EOC detection. Objective To build, develop, and validate prediction models of EOC using deep machine learning (DL) to process and analyze abdominal-pelvic CT scans. Methods We performed a pilot case-control study to predict EOC using artificial intelligence (AI) methodology and abdominal-pelvic CT scans comparing EOC patients (cases, N = 355) to patients with histology-proven benign adnexal masses (controls, N = 213). CT images were converted to 3D NIFTI format and segmented using the ovseg pipeline. Multiple DL architectures were evaluated, including convolutional neural networks (CNNs) and vision transformers (ViTs). Model performance was assessed using area under the operating characteristic curve (AUC), accuracy, and precision. Model interpretability was evaluated using Gradient-weighted Class Activation Mapping (Grad-CAM). Radiomics-based models were constructed using PyRadiomics features and compared with DL models. Results Most of women had and advanced FIGO stage, 88%, and high grade histology, 92%. Exploratory analysis of different methods without segmentation (or masking) resulted in poor performances, with AUCs between 0.39 and 0.83. The best performing models were those trained with CNN architecture with masked images, with AUC of 0.92. Validation and testing performances for EOC prediction with PyRadiomics had AUCs of 0.74 and 0.66 respectively. Conclusions DL using segmented abdominal-pelvic CT scans, particularly CNN-based architecture, demonstrate strong potential for distinguishing EOC from benign pelvic masses. Further studies are needed to create accurate DL models for early EOC detection.

The majority of patients with epithelial ovarian cancer (EOC) continue to be diagnosed at an advanced stage despite great advances in this disease treatment. To impact overall survival, we need better methods of EOC early diagnosis. We performed a case control study to predict high-grade serous cancer (HGSC) using artificial intelligence methodology and methylated DNA from surgical specimens. Initial prediction models with MethylNet were accurate but complex (AUC = 100%). We optimized these models by selecting the most informative probes with univariate ANOVA analyses first, and then multivariate lasso regression modelling. This step-wise approach resulted in 9 methylated probes predicting HGSC with an AUC of 100%. These models were validated with different analytics and with an independent DNA-methylation experiment with excellent performances.

Bacterial communities within the female upper genital tract may influence the risk of ovarian cancer. In this retrospective cohort pilot study, we aim to detect different communities of bacteria between ovarian cancer and normal controls using topic modeling, a natural language processing tool. RNA was extracted and analyzed using the VITCOMIC2 pipeline. Topic modeling assessed differences in bacterial communities. Idatuning identified an optimal latent topic number and Latent Dirichlet Allocation (LDA) assessed topic differences between high-grade serous ovarian cancer (HGSOC) and controls. Results were validated using The Cancer Genome Atlas (TCGA) HGSOC dataset. A total of 801 unique taxa were identified, with 13 bacteria significantly differing between HGSOC and normal controls. LDA modeling revealed a latent topic associated with HGSOC samples, containing bacteria Escherichia/Shigella and Corynebacterineae. Pathway analysis using KEGG databases suggest differences in several biologic pathways including oocyte meiosis, aldosterone-regulated sodium reabsorption, gastric acid secretion, and long-term potentiation. These findings support the hypothesis that bacterial communities in the upper female genital tract may influence the development of HGSOC by altering the local environment, with potential functional implications between HGSOC and normal controls. However, further validation is required to confirms these associations and determine mechanistic relevance.

Women diagnosed with advanced-stage ovarian cancer have a much worse survival rate than women diagnosed with early-stage ovarian cancer, but the early detection of this disease remains a clinical challenge. Some recent reports indicate that genetic variations could be useful for the early detection of several malignancies. In this pilot observational retrospective study, we aimed to assess whether mitochondrial DNA (mtDNA) variations could discriminate the most frequent type of ovarian cancer, high-grade serous carcinoma (HGSC), from normal tissue. We identified mtDNA variations from 20 whole-exome sequenced (WES) HGSC samples and 14 controls (normal tubes) using the best practices of genome sequencing. We built prediction models of cancer with these variants, with good performance measured by the area under the curve (AUC) of 0.88 (CI: 0.74–1.00). The variants included in the best model were correlated with gene expression to assess the potentially affected processes. These analyses were validated with the Cancer Genome Atlas (TCGA) dataset, (including over 420 samples), with a fair performance in AUC terms (0.63–0.71). In summary, we identified a set of mtDNA variations that can discriminate HGSC with good performance. Specifically, variations in the MT-CYB gene increased the risk for HGSC by over 30%, and MT-CYB expression was significantly decreased in HGSC patients. Robust models of ovarian cancer detection with mtDNA variations could be applied to liquid biopsy technology, like those which have been applied to other cancers, with a special focus on the early detection of this lethal disease.

High-grade serous ovarian cancer (HGSC) is a heterogeneous disease. RNA sequencing (RNAseq) of bulk solid tissue is of limited use in these populations due to heterogeneity. Single-cell RNA-seq (scRNA-seq) allows for the identification of diverse genetic compositions of heterogeneous cell populations. New computational methodologies are now available that use scRNAseq results to estimate cell type proportions in bulk RNAseq data. We performed bulk RNA-seq gene expression analysis on 112 HGSC specimens and 12 benign fallopian tube (FT) controls. We identified several publicly available scRNAseq datasets for use as annotation and reference datasets. Deconvolution was performed with MUlti-Subject SIngle Cell Deconvolution (MuSiC) to estimate cell type proportions in the bulk RNA-seq data. Datasets from the Cancer Genome Atlas (TCGA). HGSC repositories were also evaluated. Clinical variables and percentages of cell types were compared for differences in clinical outcomes and treatment results. Pathway enrichment analysis was also performed. Different annotations for referenced scRNA-seq datasets used for deconvolution of bulk RNA-seq data revealed different cellular proportions that were significantly associated with clinical outcomes; for example, higher proportions of macrophages were associated with a better response to primary chemotherapy. Our deconvolution study of bulk RNAseq HGSC samples identified cell populations within the tumor that may be associated with some of the observed clinical outcomes.

PURPOSE Pelvic recurrence is a frequent pattern of relapse for women with endometrial cancer. A randomized trial compared progression-free survival (PFS) after treatment with radiation therapy alone as compared with concurrent chemotherapy. MATERIALS AND METHODS Between February 2008 and August 2020, 165 patients were randomly assigned 1:1 to receive either radiation treatment alone or a combination of chemotherapy and radiation treatment. The primary objective of this study was to determine whether chemoradiation therapy was more effective than radiation therapy alone at improving PFS. RESULTS The majority of patients had low-grade (1 or 2) endometrioid histology (82%) and recurrences confined to the vagina (86%). External beam with either the three-dimensional or intensity modulated radiation treatment technique was followed by a boost delivered with brachytherapy or external beam. Patients randomly assigned to receive chemotherapy were treated with once weekly cisplatin (40 mg/m2). Rates of acute toxicity were higher in patients treated with chemoradiation as compared with radiation treatment alone. Median PFS was longer for patients treated with radiation therapy alone as compared with chemotherapy and radiation (median PFS was not reached for RT v 73 months for chemoradiation, hazard ratio of 1.25 (95% CI, 0.75 to 2.07). At 3 years, 73% of patients treated definitively with radiation and 62% of patients treated with chemoradiation were alive and free of disease progression. CONCLUSION Excellent outcomes can be achieved for women with localized recurrences of endometrial cancer when treated with radiation therapy. The addition of chemotherapy does not improve PFS for patients treated with definitive radiation therapy for recurrent endometrial cancer and increases acute toxicity. Patients with low-grade and vaginal recurrences who constituted the majority of those enrolled are best treated with radiation therapy alone.

Background: In Part 1 of the phase III RUBY trial (NCT03981796) in patients with primary advanced or recurrent endometrial cancer (EC), dostarlimab plus carboplatin–paclitaxel (CP) significantly improved progression-free survival and overall survival compared with CP alone. Limited safety data have been reported for the combination of immunotherapies plus chemotherapy in this setting. Objectives: The objective of this analysis was to identify the occurrence of treatment-related adverse events (TRAEs) and immune-related adverse events (irAEs) and to describe irAE management in Part 1 of the RUBY trial. Design: RUBY is a phase III, randomized, double-blind, multicenter study of dostarlimab plus CP compared with CP alone in patients with primary advanced or recurrent EC. Methods: Patients were randomized 1:1 to dostarlimab 500 mg, or placebo, plus CP every 3 weeks for 6 cycles, followed by dostarlimab 1000 mg, or placebo, every 6 weeks for up to 3 years. Adverse events (AEs) were assessed according to Common Terminology Criteria for Adverse Events, version 4.03. Results: The safety population included 487 patients who received ⩾1 dose of treatment (241 dostarlimab plus CP; 246 placebo plus CP). Treatment-emergent AEs were experienced by 100% of patients in both arms. TRAEs occurred in 97.9% of the dostarlimab arm and 98.8% of the placebo arm. The most common TRAEs occurred at similar rates between arms and were mostly low grade. IrAEs occurred in 58.5% of patients in the dostarlimab arm and 37.0% of patients in the placebo arm. Dostarlimab- or placebo-related irAEs were reported in 40.7% of patients in the dostarlimab arm and 16.3% of the placebo arm. Conclusion: The safety profile of dostarlimab plus CP was generally consistent with that of the individual components. Dostarlimab plus CP has a favorable benefit–risk profile and is a new standard of care for patients with primary advanced or recurrent EC. Trial registration: NCT03981796.

OBJECTIVES:To assess the efficacy and toxicity of paclitaxel and carboplatin (PC) compared to bleomycin, etoposide, and cisplatin (BEP) for treatment of newly diagnosed Stage IIA-IV or recurrent chemotherapy-naive ovarian sex cord-stromal tumors (SCST). METHODS:This phase II noninferiority trial randomly assigned patients to receive PC (6 cycles P 175 mg/m2 and C AUC = 6 IV every 3 weeks), or BEP (4 cycles B 20 units/m2 IV push day 1, E 75 mg/m2 IV days 1-5, and cisplatin 20 mg/m2 IV days 1-5 every 3 weeks). The primary endpoint was progression- free survival (PFS). This trial is registered with ClinicalTrials.gov, NCT01042522. RESULTS:At the interim analysis, 63 patients (31 PC and 32 B.P. had accrued between Feb 8, 2010 and Apr 30, 2020. Median age was 48 years. 87% had granulosa cell tumors. 37% had measurable disease. The DSMB closed accrual early for futility of PC arm. The futility analysis was supported by an estimated HR = 1.11 [95% CI: 0.57 to 2.13] which exceeded the pre-determined threshold for non-inferiority (1.10). Median PFS was 27.7 months [11.2 to 41.0] for PC and 19.7 months for BEP [95% CI: 10.4-52.7]. PC patients had fewer grade 3 or higher adverse events (PC 77% vs BEP 90%). CONCLUSIONS:The study met its pre-specified criterion for stopping early for futility and so failed to demonstrate non-inferiority of PC versus BEP in ovarian SCSTs, in a non-inferiority test with a hazard ratio margin of 1.1. Both PC and BEP may be considered in patients with advanced/recurrent SCST.

Objective. To assess patient -reported health -related quality of life (HRQoL) in patients with ovarian cancer (OC) who received niraparib as first -line maintenance therapy. Methods. PRIMA/ENGOT-OV26/GOG-3012 (NCT02655016) enrolled patients with newly diagnosed advanced OC who responded to first -line platinum -based chemotherapy. Patients were randomized (2:1) to niraparib or placebo once daily in 28 -day cycles until disease progression, intolerable toxicity, or death. HRQoL was assessed as a prespecified secondary end point using patient -reported responses to the European Organisation for Research and Treatment of Cancer QOL Questionnaire (EORTC QLQ-C30), the EORTC QLQ Ovarian Cancer Module (EORTC QLQ-OV28), the Functional Assessment of Cancer Therapy-Ovarian Symptom Index (FOSI), and EQ-5D-5L questionnaires. Assessments were collected at baseline and every 8 weeks (+/- 7 days) for 56 weeks, beginning on cycle 1/day 1, then every 12 weeks (+/- 7 days) thereafter while the patient received study treatment. Results. Among trial participants (niraparib, n = 487; placebo, n = 246), PRO adherence exceeded 80% for all instruments across all cycles. Patients reported no decline over time in HRQoL measured via EORTC QLQ-C30 Global Health Status/QoL and FOSI overall scores. Scores for abdominal/gastrointestinal symptoms (EORTC QLQ-OV28) and nausea and vomiting, appetite loss, and constipation (EORTC QLQ-C30) were higher (worse symptoms) in niraparib-treated patients than placebo -treated patients; except for constipation, these differences resolved over time. Patients did not self -report any worsening from baseline of fatigue, headache, insomnia, or abdominal pain on questionnaires. Conclusions. Despite some early, largely transient increases in gastrointestinal symptoms, patients with OC treated with niraparib first -line maintenance therapy reported no worsening in overall HRQoL. (c) 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

5525 Background: NRG GY012 is a randomized, 3-arm phase II study, comparing olaparib (O) and the combination of cediranib and olaparib (CO) to the reference arm cediranib (C) for metastatic pre-treated, endometrial cancer (EC). The trial found a trend towards benefit for CO and no benefit for O compared to C. Archival tumor and prospective blood samples were collected for biomarker analysis. Methods: Targeted next-generation sequencing (BROCA-GO) was used to detect pathogenic variants (PV) and loss of heterozygosity (LOH) in DNA from paired blood and archival cancers. The LOH cut-off was identified at 11% for HRD based on testing ovarian cancers with known HRD. Plasma samples collected at baseline, cycle 2 day 1, and end-of-treatment were analyzed via multiplex ELISA for 25 angiogenic and inflammatory circulating protein biomarkers (Angiome); IL6 was of specific interest. Prognostic associations with PFS and OS were analyzed using proportional hazards models (PhM) stratified by histology and adjusted for treatment assignment. Predictive associations (PFS and OS) were analyzed using PhM stratified by histology and including main effects for both treatment assignment and biomarker group plus an interaction term. Results: In 97 patients (pts) with evaluable tumor, BROCA-GO identified 370 somatic PV; TP53 (61%) was the most commonly mutated gene. PV in homologous recombination repair (HRR) genes were identified in 5 cases (5%). Somatic PVs were identified in BRCA2, RAD51B and PALB2. 1 pt had a germline BRCA1 PV. 2 cases had somatic PV that might restore HRR: 1 case with a somatic BRCA2 PV had somatic PVs in CHD4 and TP53BP1; the TP53BP1 frameshift PV was present only in the recurrent and not primary cancer. LOH was available for 45 cases. LOH high occurred in 16 (35.6%) cases and was exclusive to EC with TP53 mutations (p=0.0003). LOH was not associated with outcome in any of the arms. For the circulating biomarker analysis (N=96), median IL-6 was 4pg/ml. IL-6 levels >4pg/ml were associated with increased risk of progression (HR: 1.59; 95% CI: (1.04-2.42); p-value=0.032). In predictive analyses, pts with IL-6 > 4 pg/ml receiving C or C+O had increased PFS (3.8 mo vs 1.9 mo) and OS (11.9 mo vs 5.7 mo) compared to pts receiving O, the interaction p value did not reach statistical significance. Conclusions: LOH high status was not associated with outcome to O. There were too few cases with HRR PVs to determine their relationship to PARPi response. The restriction of LOH high to cancers with TP53 mutation may suggest that genomic LOH in ECs correlates better with aneuploidy than with HRR function indicating that at least some biomarkers of PARPi response vary between tumor types. IL-6 levels were prognostic of PFS but were not predictive of either OS or PFS for pts receiving C compared to pts receiving O in this small study. Further analysis of the complete Angiome and integration with the BROCA-GO dataset are ongoing. Clinical trial information: NCT03660826 .

PURPOSE:This paper reports the efficacy of the poly (ADP-ribose) polymerase inhibitor olaparib alone and in combination with the antiangiogenesis agent cediranib compared with cediranib alone in patients with advanced endometrial cancer. METHODS:This was open-label, randomized, phase 2 trial (NCT03660826). Eligible patients had recurrent endometrial cancer, received at least one (<3) prior lines of chemotherapy, and were Eastern Cooperative Oncology Group performance status 0 to 2. Patients were randomly assigned (1:1:1), stratified by histology (serous vs. other) to receive cediranib alone (reference arm), olaparib, or olaparib and cediranib for 28-day cycles until progression or unacceptable toxicity. The primary end point was progression-free survival in the intention-to-treat population. Homologous repair deficiency was explored using the BROCA-GO sequencing panel. RESULTS:A total of 120 patients were enrolled and all were included in the intention-to-treat analysis. Median age was 66 (range, 41-86) years and 47 (39.2%) had serous histology. Median progression-free survival for cediranib was 3.8 months compared with 2.0 months for olaparib (hazard ratio, 1.45 [95% CI, 0.91-2.3] p = .935) and 5.5 months for olaparib/cediranib (hazard ratio, 0.7 [95% CI, 0.43-1.14] p = .064). Four patients receiving the combination had a durable response lasting more than 20 months. The most common grade 3/4 toxicities were hypertension in the cediranib (36%) and olaparib/cediranib (33%) arms, fatigue (20.5% olaparib/cediranib), and diarrhea (17.9% cediranib). The BROCA-GO panel results were not associated with response. CONCLUSION:The combination of cediranib and olaparib demonstrated modest clinical efficacy; however, the primary end point of the study was not met. The combination was safe without unexpected toxicity.

There are strong correlations between the microbiome and human disease, including cancer. However, very little is known about potential mechanisms associated with malignant transformation in microbiome-associated gynecological cancer, except for HPV-induced cervical cancer. Our hypothesis is that differences in bacterial communities in upper genital tract epithelium may lead to selection of specific genomic variation at the cellular level of these tissues that may predispose to their malignant transformation. We first assessed differences in the taxonomic composition of microbial communities and genomic variation between gynecologic cancers and normal samples. Then, we performed a correlation analysis to assess whether differences in microbial communities selected for specific single nucleotide variation (SNV) between normal and gynecological cancers. We validated these results in independent datasets. This is a retrospective nested case-control study that used clinical and genomic information to perform all analyses. Our present study confirms a changing landscape in microbial communities as we progress into the upper genital tract, with more diversity in lower levels of the tract. Some of the different genomic variations between cancer and controls strongly correlated with the changing microbial communities. Pathway analyses including these correlated genes may help understand the basis for how changing bacterial landscapes may lead to these cancers. However, one of the most important implications of our findings is the possibility of cancer prevention in women at risk by detecting altered bacterial communities in the upper genital tract epithelium.

Results. We included a total of 3686 patients, with 620 patients (16.8%) >= 70 years. OS was 37.2 months in older compared to 45.0 months in younger patients (HR 1.21, 95% CI, 1.09-1.34, p < 0.001). Older patients had an increased risk of cancer-specific-death (HR 1.16, 95% CI, 1.04-1.29) as well as non-cancer related deaths (HR 2.78, 95% CI, 2.00-3.87). Median PFS was 15.1 months in older compared to 16.0 months in younger patients (HR 1.10, 95% CI, 1.00-1.20, p = 0.056). In the carboplatin/paclitaxel arm, older patients were just as likely to complete therapy and more likely to develop grade >= 2 peripheral neuropathy (35.7 vs 19.7%, p < 0.001). Risk of other toxicities remained equal between groups. Conclusions. In women with advanced EOC receiving chemotherapy, age >= 70 was associated with shorter OS and cancer specific survival. Older patients receiving carboplatin and paclitaxel reported higher rates of grade >= 2 neuropathy but were not more likely to suffer from other chemotherapy related toxicities. Clintrials.gov: NCT00011986 (c) 2023 Elsevier Inc. All rights reserved.