Genome-wide quantification of copy-number aberration impact on gene expression in ovarian high-grade serous carcinoma.

Copy-number alterations (CNAs) are a hallmark of cancer and can regulate cancer cell states via altered gene expression values. Herein, we have developed a copy-number impact (CNI) analysis method that quantifies the degree to which a gene expression value is impacted by CNAs and leveraged this analysis at the pathway level. Our results show that a high CNA is not necessarily reflected at the gene expression level, and our method is capable of detecting genes and pathways whose activity is strongly influenced by CNAs. Furthermore, the CNI analysis enables unbiased categorization of CNA categories, such as deletions and amplifications. We identified six CNI-driven pathways associated with poor treatment response in ovarian high-grade serous carcinoma (HGSC), which we found to be the most CNA-driven cancer across 14 cancer types. The key driver in most of these pathways was amplified wild-type KRAS, which we validated functionally using CRISPR modulation. Our results suggest that wild-type KRAS amplification is a driver of chemotherapy resistance in HGSC and may serve as a potential treatment target.

HRD related signature 3 predicts clinical outcome in advanced tubo-ovarian high-grade serous carcinoma.

OBJECTIVES: We evaluated usability of single base substitution signature 3 (Sig3) as a biomarker for homologous recombination deficiency (HRD) in tubo-ovarian high-grade serous carcinoma (HGSC). MATERIALS AND METHODS: This prospective observational trial includes 165 patients with advanced HGSC. Fresh tissue samples (n = 456) from multiple intra-abdominal areas at diagnosis and after neoadjuvant chemotherapy (NACT) were collected for whole-genome sequencing. Sig3 was assessed by fitting samples independently with COSMIC v3.2 reference signatures. An HR scar assay was applied for comparison. Progression-free survival (PFS) and overall survival (OS) were studied using Kaplan-Meier and Cox regression analysis. RESULTS: Sig3 has a bimodal distribution, eliminating the need for an arbitrary cutoff typical in HR scar tests. Sig3 could be assessed from samples with low (10%) cancer cell proportion and was consistent between multiple samples and stable during NACT. At diagnosis, 74 (45%) patients were HRD (Sig3+), while 91 (55%) were HR proficient (HRP, Sig3-). Sig3+ patients had longer PFS and OS than Sig3- patients (22 vs. 13 months and 51 vs. 34 months respectively, both p < 0.001). Sig3 successfully distinguished the poor prognostic HRP group among BRCAwt patients (PFS 19 months for Sig3+ and 13 months for Sig3- patients, p < 0.001). However, Sig3 at diagnosis did not predict chemoresponse anymore in the first relapse. The patient-level concordance between Sig3 and HR scar assay was 87%, and patients with HRD according to both tests had the longest median PFS. CONCLUSIONS: Sig3 is a prognostic marker in advanced HGSC and useful tool in patient stratification for HRD.

Efficacy and safety of niraparib in patients aged 65 years and older with advanced ovarian cancer: Results from the PRIMA/ENGOT-OV26/GOG-3012 trial.

OBJECTIVE: To evaluate the impact of age on the efficacy and safety of niraparib first-line maintenance therapy in patients with newly diagnosed advanced ovarian cancer with a complete/partial response to first-line platinum-based chemotherapy. METHODS: Post hoc analysis of the phase 3 PRIMA/ENGOT-OV26/GOG-3012 study (NCT02655016). Patients in the intent-to-treat population were categorized according to age at baseline (<65 years vs ≥65 years), and progression-free survival (PFS), safety, and health-related quality of life (HRQOL) were evaluated for each age subgroup (clinical cutoff date, May 17, 2019). Safety findings were also evaluated according to a fixed starting dose (FSD) or an individualized starting dose (ISD). RESULTS: Of 733 randomized patients, 289 (39.4%) were ≥65 years (190 niraparib, 99 placebo) at baseline. Median PFS (niraparib vs placebo) and hazard ratios (95% CI) were similar in patients aged <65 years (13.9 vs 8.2 months; HR, 0.61 [0.47-0.81]) and ≥65 years (13.7 vs 8.1 months; HR, 0.53 [0.39-0.74]). The incidences of any-grade and grade ≥3 treatment-emergent adverse events (TEAEs) were similar across age subgroups; in the niraparib arm, TEAEs leading to dose discontinuation occurred in 7.8% of patients <65 years and 18.4% of patients ≥65 years. ISD use lowered the incidence of grade ≥3 thrombocytopenia events in niraparib-treated patients compared with the FSD (<65 years: 42.8% vs 18.0%; ≥65 years 57.0% vs 26.1%). HRQOL was comparable across age subgroups. CONCLUSION: Niraparib efficacy, safety, and HRQOL were generally comparable across age subgroups, although patients ≥65 years had a higher rate of discontinuations due to TEAEs. ISD use reduced grade ≥3 thrombocytopenia events regardless of age.

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer.

Each patient's cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.

Overall survival and patient-reported outcome results from the placebo-controlled randomized phase III IMagyn050/GOG 3015/ENGOT-OV39 trial of atezolizumab for newly diagnosed stage III/IV ovarian cancer.

OBJECTIVE: To determine the impact on overall survival (OS) and patient-reported outcomes (PROs) of combining atezolizumab with standard therapy for newly diagnosed stage III/IV ovarian cancer. METHODS: The placebo-controlled double-blind randomized phase III IMagyn050/GOG 3015/ENGOT-OV39 trial (NCT03038100) assigned eligible patients to 3-weekly atezolizumab 1200 mg or placebo for 22 cycles with platinum-based chemotherapy and bevacizumab. Coprimary endpoints were progression-free survival (already reported) and OS in the PD-L1-positive and intent-to-treat (ITT) populations, tested hierarchically. Prespecified PRO analyses focused on disease-related abdominal pain and bloating symptoms (European Organisation for Research and Treatment of Cancer QLQ-OV28), functioning, and health-related quality of life (HRQoL) (QLQ-C30). RESULTS: After 38 months' median follow-up, the OS hazard ratio in the PD-L1-positive population was 0.83 (95% CI, 0.66-1.06; p = 0.13); median OS was not estimable with atezolizumab versus 49.2 months with placebo. The hazard ratio for OS in the ITT population was 0.92 (95% CI, 0.78-1.09; median 50.5 versus 46.6 months, respectively). At week 9, similar proportions of patients in both arms of the neoadjuvant cohort showed ≥10-point improvement from baseline in abdominal pain and bloating, functioning, and HRQoL. In the primary surgery cohort, similar proportions of patients in each arm had improved, stable, or worsened physical and role function and HRQoL from baseline over time. Neither cohort showed differences between arms in treatment-related symptoms or overall side-effect bother. CONCLUSIONS: Incorporation of atezolizumab into standard therapy for newly diagnosed ovarian cancer does not significantly improve efficacy or impose additional treatment burden for patients. CLINICALTRIALS: gov registration: NCT03038100.

Comorbidity of Urogynecological and Gastrointestinal Disorders in Female Patients With Lichen Sclerosus.

OBJECTIVE: Lichen sclerosus (LS) is a chronic inflammatory disease with a significant impact on quality of life. The aim of this cross-sectional case-control study was to characterize concomitant urogynecological and gastrointestinal disorders in female patients with LS. METHODS: A medical records search between 2004 and 2012 yielded 455 women and girls (mean age 64 years) with LS. The study cohort was compared with a 10-fold age- and sex-matched control cohort. Gynecological cancers and their precursors; gynecological, urinary, and gastrointestinal disorders; and pain syndromes were evaluated. RESULTS: The well-known association between LS and increased risk of vulvar cancer and its precursors was also found in our study (relative risk [RR] = 100.0; p < .001 and high-grade squamous intraepithelial lesions RR = 110.0; p < .001, respectively), but we also found an increased risk for cervical cancer (RR = 6.0; p = .005) and endometrial cancer (RR = 2.9; p < .001). Gynecological pain syndromes such as dyspareunia (RR = 20.0; p < .001) and interstitial cystitis (RR = 5.0; p < .001) and urinary incontinence (RR = 4.8; p < .001) were also increased. Among gastrointestinal disorders, we found increased risk for celiac disease (RR = 6.8; p < .001), diverticular intestine diseases (RR = 1.9; p < .001), functional intestinal disorders (RR = 2.3; p = .003), and anal and rectal fissures (RR = 2.4; p = .046). CONCLUSIONS: We found that female patients with LS have an increased risk for gynecological cancers as well as for several urogynecological and gastrointestinal disorders. Increased awareness is required to identify and treat these concomitant disorders.

QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability.

RNA in situ hybridization (RNA-ISH) is a powerful spatial transcriptomics technology to characterize target RNA abundance and localization in individual cells. This allows analysis of tumor heterogeneity and expression localization, which are not readily obtainable through transcriptomic data analysis. RNA-ISH experiments produce large amounts of data and there is a need for automated analysis methods. Here we present QuantISH, a comprehensive open-source RNA-ISH image analysis pipeline that quantifies marker expressions in individual carcinoma, immune, and stromal cells on chromogenic or fluorescent in situ hybridization images. QuantISH is designed to be modular and can be adapted to various image and sample types and staining protocols. We show that in chromogenic RNA in situ hybridization images of high-grade serous carcinoma (HGSC) QuantISH cancer cell classification has high precision, and signal expression quantification is in line with visual assessment. We further demonstrate the power of QuantISH by showing that CCNE1 average expression and DDIT3 expression variability, as captured by the variability factor developed herein, act as candidate biomarkers in HGSC. Altogether, our results demonstrate that QuantISH can quantify RNA expression levels and their variability in carcinoma cells, and thus paves the way to utilize RNA-ISH technology.

FUNGI: FUsioN Gene Integration toolset.

MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. RESULTS: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance. AVAILABILITYAND IMPLEMENTATION: FUNGI and its documentation are available at https://bitbucket.org/alejandra_cervera/fungi as standalone or from Anduril at https://www.anduril.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples.

MOTIVATION: A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample composition changes systematically due to chemotherapy and between the anatomical sites, preventing direct comparison of treatment-naive and treated samples. RESULTS: To overcome this, we developed PRISM, a latent statistical framework to simultaneously extract the sample composition and cell-type-specific whole-transcriptome profiles adapted to each individual sample. Our results indicate that the PRISM-derived composition-free transcriptomic profiles and signatures derived from them predict the patient response better than the composite raw bulk data. We validated our findings in independent ovarian cancer and melanoma cohorts, and verified that PRISM accurately estimates the composition and cell-type-specific expression through whole-genome sequencing and RNA in situ hybridization experiments. AVAILABILITYAND IMPLEMENTATION: https://bitbucket.org/anthakki/prism. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Agile workflow for interactive analysis of mass cytometry data.

MOTIVATION: Single-cell proteomics technologies, such as mass cytometry, have enabled characterization of cell-to-cell variation and cell populations at a single-cell resolution. These large amounts of data, require dedicated, interactive tools for translating the data into knowledge. RESULTS: We present a comprehensive, interactive method called Cyto to streamline analysis of large-scale cytometry data. Cyto is a workflow-based open-source solution that automates the use of state-of-the-art single-cell analysis methods with interactive visualization. We show the utility of Cyto by applying it to mass cytometry data from peripheral blood and high-grade serous ovarian cancer (HGSOC) samples. Our results show that Cyto is able to reliably capture the immune cell sub-populations from peripheral blood and cellular compositions of unique immune- and cancer cell subpopulations in HGSOC tumor and ascites samples. AVAILABILITYAND IMPLEMENTATION: The method is available as a Docker container at https://hub.docker.com/r/anduril/cyto and the user guide and source code are available at https://bitbucket.org/anduril-dev/cyto. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Efficacy of niraparib by time of surgery and postoperative residual disease status: A post hoc analysis of patients in the PRIMA/ENGOT-OV26/GOG-3012 study.

OBJECTIVE: To evaluate the association between surgical timing and postoperative residual disease status on the efficacy of niraparib first-line maintenance therapy in patients with newly diagnosed advanced ovarian cancer at high risk of recurrence. METHODS: Post hoc analysis of the phase 3 PRIMA/ENGOT-OV26/GOG-3012 (NCT02655016) study of niraparib in patients with newly diagnosed primary advanced ovarian, primary peritoneal, or fallopian tube cancer with a complete/partial response to first-line platinum-based chemotherapy. Progression-free survival (PFS) was assessed by surgical status (primary debulking surgery [PDS] vs neoadjuvant chemotherapy/interval debulking surgery [NACT/IDS]) and postoperative residual disease status (no visible residual disease [NVRD] vs visible residual disease [VRD]) in the intent-to-treat population. RESULTS: In PRIMA (N = 733), 236 (32.2%) patients underwent PDS, and 481 (65.6%) received NACT/IDS before enrollment. Median PFS (niraparib vs placebo) and hazard ratios (95% CI) for progression were similar in PDS (13.7 vs 8.2 months; HR, 0.67 [0.47-0.96]) and NACT/IDS (14.2 vs 8.2 months; HR, 0.57 [0.44-0.73]) subgroups. In patients who received NACT/IDS and had NVRD (n = 304), the hazard ratio (95% CI) for progression was 0.65 (0.46-0.91). In patients with VRD following PDS (n = 183) or NACT/IDS (n = 149), the hazard ratios (95% CI) for progression were 0.58 (0.39-0.86) and 0.41 (0.27-0.62), respectively. PFS was not evaluable for patients with PDS and NVRD because of sample size (n = 37). CONCLUSIONS: In this post hoc analysis, niraparib efficacy was similar across PDS and NACT/IDS subgroups. Patients who had NACT/IDS and VRD had the highest reduction in the risk of progression with niraparib maintenance.

qSNE: quadratic rate t-SNE optimizer with automatic parameter tuning for large datasets.

MOTIVATION: Non-parametric dimensionality reduction techniques, such as t-distributed stochastic neighbor embedding (t-SNE), are the most frequently used methods in the exploratory analysis of single-cell datasets. Current implementations scale poorly to massive datasets and often require downsampling or interpolative approximations, which can leave less-frequent populations undiscovered and much information unexploited. RESULTS: We implemented a fast t-SNE package, qSNE, which uses a quasi-Newton optimizer, allowing quadratic convergence rate and automatic perplexity (level of detail) optimizer. Our results show that these improvements make qSNE significantly faster than regular t-SNE packages and enables full analysis of large datasets, such as mass cytometry data, without downsampling. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are openly available at https://bitbucket.org/anthakki/qsne/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A longitudinal analysis of CA125 glycoforms in the monitoring and follow up of high grade serous ovarian cancer.

OBJECTIVE: Cancer antigen 125 (CA125) is generally considered the gold standard of biomarkers in the diagnosis and monitoring of high grade serous ovarian carcinoma (HGSC). We recently reported, that two CA125 glycoforms (CA125-STn and CA125-MGL) have a high specificity to HGSC and further hypothesized, that these cancer specific glycoforms are feasible candidates as biomarkers in HGSC treatment and follow up. METHODS: Our cohort consisted of 122 patients diagnosed with HGSC. Serum samples were collected longitudinally at the time of diagnosis, during treatment and follow up. Serum levels of CA125, CA125-STn and CA125-MGL were determined and compared or correlated with different end points (tumor load assessed intraoperatively, residual disease, treatment response, progression free survival). RESULTS: Serum CA125-STn levels at diagnosis differentiated patients with low tumor load and high tumor load (p = 0,030), indicating a favorable detection of tumor volume. Similarly, the CA125-STn levels at diagnosis were significantly lower in patients with subsequent complete cytoreduction than in patients with suboptimal cytoreduction (p = 0,025). Conventional CA125 did not differentiate these patients (p = 0,363 and p = 0,154). The CA125-STn nadir value predicted the progression free survival of patients. The detection of disease relapse was improved with CA125-STn, which presented higher fold increase in 80,0% of patients and earlier increase in 37,0% of patients. CONCLUSIONS: CA125-STn showed promise as a useful biomarker in the monitoring and follow up of patients with HGSC utilizing a robust and affordable technique. Our findings are topical as a suitable indicator of tumor load facilitates patient selection in an era of new targeted therapies.

HE4 in the evaluation of tumor load and prognostic stratification of high grade serous ovarian carcinoma.

OBJECTIVE: Human epididymis protein 4 (HE4) is a validated, complementary biomarker to cancer antigen 125 (CA125) for high grade serous ovarian carcinoma (HGSC). Currently, there are insufficient data on the utility of longitudinal HE4 measurement during HGSC treatment and follow up. We set to provide a comprehensive analysis on the kinetics and prognostic performance of HE4 with serial measurements during HGSC treatment and follow up. METHODS: This prospective study included 143 patients with advanced HGSC (ClinicalTrials.gov identifier: NCT01276574). Serum CA125 and HE4 were measured at baseline, before each cycle of chemotherapy and during follow up until first progression. Baseline biomarker values were compared to the tumor load assessed during surgery and to residual disease. Biomarker nadir values and concentrations at progression were correlated to survival. RESULTS: The baseline HE4 concentration distinguished patients with a high tumor load from patients with a low tumor load assessed during surgery (p<.0001). The baseline CA125 level was not associated with tumor load to a similar extent (p=.067). At progression, the HE4 level was an independent predictor of worse survival in the multivariate analysis (p=.002). All patients that were alive 3 years post-progression had a serum HE4 concentration below 199.20 pmol/l at the 1st recurrence. CONCLUSION: HE4 is a feasible biomarker in the treatment monitoring and prognostic stratification of patients with HGSC. Specifically, the serum level of HE4 at first relapse was associated with the survival of patients and it may be a useful complementary tool in the selection of second line treatments. This is to the best of our knowledge the first time this finding has been reported.

Niraparib plus bevacizumab versus niraparib alone for platinum-sensitive recurrent ovarian cancer (NSGO-AVANOVA2/ENGOT-ov24): a randomised, phase 2, superiority trial.

BACKGROUND: Platinum-based chemotherapy is the foundation of treatment for platinum-sensitive recurrent ovarian cancer, but has substantial toxicity. Bevacizumab and maintenance poly(ADP-ribose) polymerase (PARP) inhibitors both significantly improve efficacy versus standard therapy, primarily in terms of progression-free survival, and offer the potential for chemotherapy-free treatment. AVANOVA2 compared niraparib and bevacizumab versus niraparib alone as definitive treatment for platinum-sensitive recurrent ovarian cancer. METHODS: This open-label, randomised, phase 2, superiority trial in 15 university hospitals in Denmark, Sweden, Finland, Norway, and the USA enrolled women aged 18 years or older with measurable or evaluable high-grade serous or endometrioid platinum-sensitive recurrent ovarian cancer. Patients had to have an Eastern Cooperative Oncology Group performance status of 0-2, and had to have previously received platinum-containing therapy for primary disease but ≤1 prior non-platinum-containing regimen for recurrent disease. Previous treatment with bevacizumab or first-line maintenance PARP inhibitors was permitted. Eligible patients were randomly assigned 1:1 (by random permuted blocks with block sizes of two and four, no masking), stratified by homologous recombination deficiency status and chemotherapy-free interval, to receive once-daily oral niraparib 300 mg alone or with intravenous bevacizumab 15 mg/kg once every 3 weeks until disease progression. The primary endpoint was progression-free survival, assessed by the investigators in the intention-to-treat population after events in at least 62 patients. Safety was analysed in all patients who received at least one dose of study drug. This ongoing trial is registered with ClinicalTrials.gov, number NCT02354131. FINDINGS: Between May 23, 2016, and March 6, 2017, 97 patients were enrolled and randomly assigned: 48 to niraparib plus bevacizumab and 49 to single-agent niraparib. Median follow-up was 16·9 months (IQR 15·4-20·9). Niraparib plus bevacizumab significantly improved progression-free survival compared with niraparib alone (median progression-free survival 11·9 months [95% CI 8·5-16·7] vs 5·5 months [3·8-6·3], respectively; adjusted hazard ratio [HR] 0·35 [95% CI 0·21-0·57], p<0·0001). Grade 3 or worse adverse events occurred in 31 (65%) of 48 patients who received niraparib plus bevacizumab and 22 (45%) of 49 who received single-agent niraparib. The most common grade 3 or worse adverse events in both groups were anaemia (7 [15%] of 48 vs 9 [18%] of 49) and thrombocytopenia (5 [10%] vs 6 [12%]), and hypertension in the combination group (10 [21%] vs 0). Niraparib plus bevacizumab was associated with increased incidences of any-grade proteinuria (10 [21%] of 48 patients vs 0) and hypertension (27 [56%] of 48 vs 11 [22%] of 49) compared with niraparib alone. No treatment-related deaths occurred. INTERPRETATION: The efficacy observed with this chemotherapy-free combination of approved agents in women with platinum-sensitive recurrent ovarian cancer warrants further evaluation. A randomised phase 3 trial investigating niraparib plus bevacizumab versus chemotherapy plus bevacizumab in platinum-sensitive recurrent ovarian cancer is planned. FUNDING: Nordic Society of Gynaecological Oncology and Tesaro.

Identifying differentially methylated sites in samples with varying tumor purity.

Motivation: DNA methylation aberrations are common in many cancer types. A major challenge hindering comparison of patient-derived samples is that they comprise of heterogeneous collection of cancer and microenvironment cells. We present a computational method that allows comparing cancer methylomes in two or more heterogeneous tumor samples featuring differing, unknown fraction of cancer cells. The method is unique in that it allows comparison also in the absence of normal cell control samples and without prior tumor purity estimates, as these are often unavailable or unreliable in clinical samples. Results: We use simulations and next-generation methylome, RNA and whole-genome sequencing data from two cancer types to demonstrate that the method is accurate and outperforms alternatives. The results show that our method adapts well to various cancer types and to a wide range of tumor content, and works robustly without a control or with controls derived from various sources. Availability and implementation: The method is freely available at https://bitbucket.org/anthakki/dmml. Supplementary information: Supplementary data are available at Bioinformatics online.

Is it safe to operate selected low-risk endometrial cancer patients in secondary hospitals?

INTRODUCTION: The aim of this study was to assess the accuracy of a preoperative screening algorithm in identifying low-risk endometrial cancer (EC) patients to ensure optimal care. METHODS: A total of 277 patients with primary EC confirmed through biopsy underwent magnetic resonance imaging (MRI). Patients with risk factors for advanced high-risk EC, such as non-endometrioid histology, high-grade differentiation status, deep myometrial invasion, or spread beyond the uterine corpus, were systematically excluded. The remaining preoperatively screened patients with stage IA low-grade endometrioid EC (EEC) (n = 93) underwent surgery in a tertiary hospital. The accuracy of the preoperative diagnosis was evaluated by comparing the findings with the postoperative histopathological results. Disease-free survival (DFS) and overall survival (OS) were analyzed using 8-year follow-up data. RESULTS: Postoperative histopathological analysis revealed that all patients had grade 1-2 EEC localized to the corpus uteri. Only three patients had deep myometrial invasion (stage IB), but they remained disease-free after 6-9 years of follow-up. The median follow-up time for all patients was 8.7 years. The DFS was 7.6 years, and the OS was 8.6 years. Two patients with stage IA grade 1 EEC experienced relapse and, despite treatment, died of EC. No other EC-related deaths occurred. CONCLUSIONS: The screening algorithm accurately identified low-risk EC patients without compromising survival. Therefore, the algorithm appears to be feasible for selecting patients for surgery in secondary hospitals.

Olaparib Addition to Maintenance Bevacizumab Therapy in Ovarian Carcinoma With BRCA-Like Genomic Aberrations.

Importance: Testing for homologous recombination deficiency is required for the optimal treatment of high-grade epithelial ovarian cancer. The search for accurate biomarkers is ongoing. Objective: To investigate whether progression-free survival (PFS) and overall survival (OS) of patients with high-grade epithelial ovarian cancer treated with maintenance olaparib or placebo differed between patients with a tumor BRCA-like genomic profile and patients without a tumor BRCA-like profile. Design, Setting, and Participants: This cohort study was a secondary analysis of the PAOLA-1 randomized clinical trial that compared olaparib plus bevacizumab with placebo plus bevacizumab as maintenance treatment in patients with advanced high-grade ovarian cancer after a good response to first-line platinum with taxane chemotherapy plus bevacizumab, irrespective of germline or tumor BRCA1/2 mutation status. All patients with available tumor DNA were included in the analysis. The current analysis tested for an interaction between BRCA-like status and olaparib treatment on survival outcomes. The original trial was conducted between July 2015 and September 2017; at the time of data extraction for analysis in March 2022, a median follow-up of 54.1 months (IQR, 28.5-62.2 months) and a total follow-up time of 21 711 months was available, with 336 PFS and 245 OS events. Exposures: Tumor homologous recombination deficiency was assessed using the BRCA-like copy number aberration profile classifier. Myriad MyChoice CDx was previously measured. The trial was randomized between the olaparib and bevacizumab and placebo plus bevacizumab groups. Main Outcomes and Measures: This secondary analysis assessed hazard ratios (HRs) of olaparib vs placebo among biomarker strata and tested for interaction between BRCA-like status and olaparib treatment on PFS and OS, using Cox proportional hazards regression. Results: A total of 469 patients (median age, 60 [range 26-80] years) were included in this study. The patient cohort consisted of women with International Federation of Gynaecology and Obstetrics stage III (76%) high-grade serous (95%) ovarian cancer who had no evaluable disease or complete remission at initial or interval debulking surgery (76%). Thirty-one percent of the tumor samples (n = 138) harbored a pathogenic BRCA mutation, and BRCA-like classification was performed for 442 patients. Patients with a BRCA-like tumor had a longer PFS after olaparib treatment than after placebo (36.4 vs 18.6 months; HR, 0.49; 95% CI, 0.37-0.65; P < .001). No association of olaparib with PFS was found in patients with a non-BRCA-like tumor (17.6 vs 16.6 months; HR, 1.02; 95% CI, 0.68-1.51; P = .93). The interaction was significant (P = .004), and HRs and P values (for interaction) were similar in the relevant subgroups, OS, and multivariable analyses. Conclusions and Relevance: In this secondary analysis of the PAOLA-1 randomized clinical trial, patients with a BRCA-like tumor, but not those with a non-BRCA-like tumor, had a significantly longer survival after olaparib plus bevacizumab treatment than placebo plus bevacizumab treatment. Thus, the BRCA1-like classifier could be used as a biomarker for olaparib plus bevacizumab as a maintenance treatment.