High-grade Serous Ovarian Cancer Research Articles

High prevalence of FAP+ cancer-associated fibroblasts predicts poor outcome in patients with high-grade serous ovarian cancer with high CD8 T-cell density.

Studies have implied that fibroblasts may act as regulators of immune cells in the tumor microenvironment (TME). We investigated the clinical relevance of fibroblast activation protein (FAP) positive stroma in high-grade serous ovarian cancer (HGSC) in relation to CD8+ lymphocyte's infiltration. In a discovery cohort (N=113) of HGSC, expression of FAP and CD8 in the TME was analyzed with immunohistochemistry. Results were correlated with overall survival (OS) and progression-free survival (PFS). The findings were validated in an independent cohort of HGSC (N=121) and in public available datasets. High infiltration of CD8+ cells in the TME of HGSC was found to be associated with longer OS, as previously known. Increased expression of FAP was associated with shorter median PFS (11.4 vs. 18.6months) in tumors with high density of CD8+ cells (HR 4.03, CI 95% 1.38-11.72, p=0.01). Similarly, in the validation cohort, high intensity of FAP in cases with high density of CD8+ cells was associated with shorter OS, 31.5 vs 76.9months (HR 2.83; 95% CI 1.17-6.86, p=0.02). The results were consistent in multivariable analyses. The association between high FAP expression and poor outcome in high density CD8 HGSC was also confirmed in publicly available datasets. The TME infiltration of FAP-positive fibroblasts is associated with poor prognosis in HGSC with high CD8+ cells density. Targeting the FAP+ subset of fibroblasts may unlock the local immune-activation in the TME thus enhance the positive prognostic effect of T-cells in ovarian cancer.

Molecular characterization of ovarian mesonephric-like adenocarcinoma: Insights from single-cell RNA sequencing and mitochondrial metabolism.

Ovarian mesonephric-like adenocarcinoma (MLA) is a rare malignancy with limited understanding of its molecular features and therapeutic vulnerabilities. Although similar to uterine MLA, its unique characteristics remain undefined. This study aimed to characterize ovarian MLA using single-cell RNA sequencing (scRNA-seq) and compare it with high-grade serous ovarian cancer (HGSOC). We analyzed the cellular and molecular heterogeneity of an ovarian MLA sample using scRNA-seq. Differential gene expression and pathway analyses were performed to identify unique molecular signatures and therapeutic targets. HGSOC scRNA-seq datasets were used for comparative analysis. Ovarian MLA demonstrated reduced heterogeneity, with a predominance of epithelial cells compared to HGSOC. Transcriptomic profiling revealed an upregulation of mitochondrial metabolism and lipid biosynthesis genes, indicating a metabolic shift toward oxidative phosphorylation. Gene enrichment and protein-protein interaction analyses identified distinct pathways, including mitochondrial biogenesis and dynamics, suggesting mitochondrial reprogramming. This study provides the first scRNA-seq-based molecular characterization of ovarian MLA, differentiating it from HGSOC. Findings suggest potential therapeutic avenues, with a proposed combination therapy targeting MAP kinase and PI3K/AKT/mTOR pathways. Validation in larger cohorts is necessary for clinical application.

Association between plasma perfluoroalkyl substances and high-grade serous ovarian cancer overall survival: A nested case-control study.

Although evidence suggests that perfluoroalkyl and polyfluoroalkyl substances (PFASs) are positively correlated to several disease risks, no studies have proven if plasma PFASs are related to ovarian cancer survival. To explore the association between plasma PFASs and high-grade serous ovarian cancer (HGSOC) overall survival (OS) in the population who did not smoke. We conducted a nested case-control study within the Ovarian Cancer Follow-Up Study, matching 159 dead patients and 159 survival ones based on body mass index, sample date, and age at diagnosis. Nine plasma PFASs were extracted by solid phase extraction and measured using a liquid chromatography system coupled with tandem mass spectrometry. Baseline plasma concentrations of perfluorinated carboxylic acids (PFCAs) [perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluoroheptanoic acid (PFHpA)] and perfluorinated sulfonic acids (PFSAs) [perfluorooctane sulfonic acid (PFOS) and perfluorohexane sulfonic acid (PFHxS)] were calculated. Odds ratios (ORs) and corresponding 95 % confidence intervals (CIs) were calculated via conditional logistic regression models. To elucidate the combined effects, Bayesian kernel machine (BKMR), and regression quantile g-computation (QGC) models were utilized. In full-adjusted model, significant differences were observed between HGSOC survival and perfluorobutane sulfonic acid, PFHpA, PFHxS, PFOS, PFCA, and PFSA. ORs and 95 %CIs were 2.74 (1.41-5.31), 1.97 (1.03-3.76), 2.13 (1.15-3.95), 2.28 (1.16-4.47), 3.74 (1.78-7.85), and 2.56 (1.31-5.01), respectively for the highest tertile compared with the lowest tertile. The QGC and BKMR models indicated that elevated concentrations of PFAS mixtures were associated with poor OS in HGSOC. Both individual and mixed plasma PFASs may relate to poor OS of HGSOC. Further research is necessary to establish causality, and it is recommended to reinforce environmental risk mitigation strategies to minimize PFAS exposure.

MYC and HSF1 Cooperate to Drive Sensitivity to Polo-like Kinase 1 Inhibitor Volasertib in High-grade Serous Ovarian Cancer.

We show that HSF1 and MYC genes are co-amplified in more than 30% of HGSOC and demonstrate that HSF1 and MYC functionally cooperate to drive the growth of HGSOC cells. This work provides the foundation for HSF1 and MYC co-amplification as a biomarker for treatment efficacy of the polo-like kinase 1 inhibitor volasertib in HGSOC.

OTUD4-mediated inhibition of YAP1 signaling pathway in ovarian cancer: Implications for macrophage polarization and recruitment.

Ovarian cancer is a malignancy gynecologic oncology with high incidence and high mortality rate. M2-like tumor-associated macrophages promote cancer cell migration and metastasis. Ovarian tumor family deubiquitinase 4 (OTUD4) belongs to deubiquitinating enzyme family. The roles of OTUD4 in tumor microenvironments in ovarian cancer remains unknow. In this work, OTUD4 was overexpressed or knocked down in high-grade serous ovarian cancer cells OVCAR8 and CAOV3. Ovarian cells were co-cultured with THP-1 macrophages to simulate the tumor microenvironment. We found that OTUD4-expressed ovarian cells inhibited macrophage chemotaxis and M2 polarization. Besides, in ovarian tumor-bearing mouse model, OTUD4 suppressed tumor metastasis and remodeling tumor-associated macrophages phenotype (pro-tumor M2 to anti-tumor M1). In mechanism, OTUD4 protein bound to YAP1 protein, and downregulation of OTUD4 enhanced K63 ubiquitination and nuclear translocation of YAP1, thus increasing CCL2 transcription and subsequent macrophage recruitment. OTUD4 might inhibit CCL2 expression to regulate tumor-associated macrophages in ovarian tumor microenvironment. Those findings present a potential therapeutic strategy for ovarian cancer.

High-grade serous ovarian cancer—bridging the gap between epidemiology and prevention with biology

High-grade serous ovarian cancer—bridging the gap between epidemiology and prevention with biology

Identification of TTLL8, POTEE, and PKMYT1 as immunogenic cancer-associated antigens and potential immunotherapy targets in ovarian cancer

ABSTRACT Most high-grade serous ovarian cancers (OC) do not respond to current immunotherapies. To identify potential new actionable tumor antigens in OC, we performed immunopeptidomics on a human OC cell line expressing the HLA-A02:01 haplotype, which is commonly expressed across many racial and ethnic groups. From this dataset, we identified TTLL8, POTEE, and PKMYT1 peptides as candidate tumor antigens with low expression in normal tissues and upregulated expression in OC. Using tissue microarrays, we assessed the protein expression of TTLL8 and POTEE and their association with patient outcomes in a large cohort of OC patients. TTLL8 was found to be expressed in 56.7% of OC and was associated with a worse overall prognosis. POTEE was expressed in 97.2% of OC patients and had no significant association with survival. In patient TILs, increases in cytokine production and tetramer-positive populations identified antigen-specific CD8 T cell responses, which were dependent on antigen presentation by HLA class I. Antigen-specific T cells triggered cancer cell killing of antigen-pulsed OC cells. These findings suggest that TTLL8, POTEE, and PKMYT1 are potential targets for the development of antigen-targeted immunotherapy in OC.

Utilizing explainable machine learning for progression-free survival prediction in high-grade serous ovarian cancer: insights from a prospective cohort study.

High-grade serous ovarian cancer (HGSOC) remains one of the most challenging gynecological malignancies, with over 70% of ovarian cancer patients ultimately experiencing disease progression. The current prognostic tools for progression-free survival (PFS) in HGSOC patients have limitations. This study aims to develop an explainable machine learning (ML) model for predicting PFS in HGSOC patients. Nine ML algorithms for PFS prediction were developed using a prospective cohort of 310 HGSOC patients consecutively enrolled from a large Chinese tertiary hospital between January 2017 and December 2020. The optimal model was internally validated using the 1000 bootstrap method. The SHapley Additive exPlanations (SHAP) method was employed to interpret the model in terms of feature importance and feature effects. The final model, constructed with the optimal feature subset, was deployed as an interactive web-based Shiny app. The random survival forest (RSF) model demonstrated superior predictive performance compared to other ML models, the RFS model constructed with an optimal feature subset in the optimal imputed dataset achieved a superior 1000 bootstrap C-index of 0.755 (95% CI: 0.750-0.780) and a Brier score of 0.183 (95% CI: 0.175-0.190). SHAP analysis identified tumor residual, HE4, FIGO stage, T stage, CA125, age, ascites volume, platelet counts, and BMI as the top nine contributing factors. It also revealed potential nonlinear relationships and important thresholds between HE4, CA125, age, ascites volume, platelet counts, the body mass index, and PFS risk. Additionally, interaction effects were found between tumor residual and age, HE4, and CA125. Finally, an interactive web-based Shiny app for the model was developed and accessible at https://rsfmodels.shinyapps.io/ocRSF/. An explainable ML model for PFS prediction in HGSOC patients was developed with superior results. The publicly accessible web tool based on the optimized model facilitates its utility in clinical settings, potentially improving individualized patient management and treatment decision-making in HGSOC.

UBE2J1 is identified as a novel plasma cell-related gene involved in the prognosis of high-grade serous ovarian cancer

BackgroundImmune cells within tumor tissues play important roles in remodeling the tumor microenvironment, thus affecting tumor progression and the therapeutic response. The current study was designed to identify key markers of plasma cells and explore their role in high-grade serous ovarian cancer (HGSOC).MethodsWe utilized single-cell sequencing data from the Gene Expression Omnibus (GEO) database to identify key immune cell types within HGSOC tissues and to extract related markers via the Seurat package. The effects of immune cell markers on prognosis were analyzed via univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and gene set variation analysis (GSVA) of bulk sequencing data from The Cancer Genome Atlas (TCGA)-HGSOC cohort. Finally, the effects of key markers on HGSOC cells were evaluated via Cell Counting Kit-8 (CCK-8), Transwell, colony formation, wound healing, immunofluorescence and in vivo tumor growth assays.ResultsAt the single-cell level, we detected a significant increase in the proportion of plasma cells in HGSOC samples compared to that in normal ovarian samples. Within HGSOC tissues, these plasma cells were found to interact with CD8 + T cells, fibroblasts and endothelial cells. In addition, patients in the high-plasma cell-related score group had better survival rates and higher epithelial‒mesenchymal transition (EMT), apoptosis and immune scores. Moreover, univariate Cox and LASSO regression analyses revealed that ubiquitin-conjugating enzyme E2 J1 (UBE2J1) is a prognostic marker in HGSOC. Further functional studies revealed that overexpression of UBE2J1 promoted cell proliferation, invasion, migration and colony formation, whereas UBE2J1 knockdown attenuated the abovementioned cellular behaviors. Additionally, UBE2J1 overexpression promoted EMT, as evidenced by alterations in the protein expression levels of N-cadherin, snail family transcriptional repressor 2 (Slug), Twist family BHLH transcription factor 1 (Twist 1) and E-cadherin. Moreover, we found that UBE2J1 silencing was able to inhibit the tumor growth in vivo.ConclusionsOverall, this study elucidated the role of plasma cells and revealed UBE2J1 as a novel oncogene in HGSOC, uncovering new mechanisms related to HGSOC tumorigenesis and promising therapeutic targets for HGSOC patients.

Identification of a TNIK-CDK9 axis as a targetable strategy for platinum-resistant ovarian cancer.

Up to 90% of high-grade serous ovarian cancer (HGSC) patients will develop resistance to platinum-based chemotherapy, posing substantial therapeutic challenges due to a lack of universally druggable targets. Leveraging BenevolentAI's AI-driven approach to target discovery, we screened potential AI-predicted therapeutic targets mapped to unapproved tool compounds in patient-derived 3D models. This identified TNIK, which is modulated by NCB-0846, as a novel target for platinum-resistant HGSC. Targeting by this compound demonstrated efficacy across both in vitro and ex vivo organoid platinum-resistant models. Additionally, NCB-0846 treatment effectively decreased Wnt activity, a known driver of platinum resistance; however, we found that these effects were not solely mediated by TNIK inhibition. Comprehensive AI, in silico, and in vitro analyses revealed CDK9 as another key target driving NCB-0846's efficacy. Interestingly, TNIK and CDK9 co-expression positively correlated, and chromosomal gains in both served as prognostic markers for poor patient outcomes. Combined knockdown of TNIK and CDK9 markedly diminished downstream Wnt targets and reduced chemotherapy-resistant cell viability. Furthermore, we identified CDK9 as a novel mediator of canonical Wnt activity, providing mechanistic insights into the combinatorial effects of TNIK and CDK9 inhibition and offering a new understanding of NCB-0846 and CDK9 inhibitor function. Our findings identified the TNIK-CDK9 axis as druggable targets mediating platinum resistance and cell viability in HGSC. With AI at the forefront of drug discovery, this work highlights how to ensure that AI findings are biologically relevant by combining compound screens with physiologically relevant models thus supporting the identification and validation of potential drug targets.

COMPARISON OF ULTRASOUND-GUIDED TRUCUT NEEDLE BIOPSY AND LAPAROSCOPY IN THE DIAGNOSIS OF HIGH-GRADE SEROUS OVARIAN CANCER

OBJECTIVE: We aimed to compare tru-cut biopsy with laparoscopy in the diagnosis of high-grade serous ovarian cancer (HGSC) in our clinic. MATERIAL AND METHODS: Our retrospective study included patients who underwent surgery for HGSC between January 2013 and December 2023. Patients with pathologically confirmed (FIGO 2018) stage III or IV HGSC underwent neoadjuvant chemotherapy (NACT) and interval debulking surgery (IDS) were performed. Exclusion criteria were patients with stage I and II ovarian cancer and who did not receive NACT. Additionally, patients with non-high-grade serous ovarian cancer or non-gynecological conditions were excluded. As a result, 60 patients were included in the study. Participants were categorized into two groups, namely, Group 1 (Patients diagnosed with HGSC by tru-cut biopsy before NACT) and Group 2 (Patients diagnosed with HGSC by diagnostic laparoscopy before NACT). Time-to-event analyses were conducted using the Kaplan- Meier method and log-rank test. Statistical significance was defined when p < 0.05. RESULTS: Out of the 60 patients, 32 patients were diagnosed by tru-cut biopsy and 28 patients with laparoscopy. The overall survival (OS) of Group 1 was 53.1%, and for Group 2, it was 71.4% (p = 0.371). The progression-free survival (PFS) rate was 56.3 for Group 1 and 64.3% for Group 2 (p = 0.464). No significant difference was detected in terms of recurrence, OS and PFS. We found a significant difference between Group 1 and Group 2 only in terms of hospitalization time (p < 0.001). CONCLUSIONS: HGSC is a histopathological subgroup of ovarian cancer that is difficult to diagnose and manage. While primary debulking surgery remains in the background, the importance of tru-cut biopsy in terms of short hospital stay should not be forgotten in the diagnostic evaluation of patients.

Disease-free survival of 15 years after primary surgery in a patient with advanced high-grade serous ovarian cancer: a case report and literature review

BackgroundOvarian cancer, particularly high-grade serous ovarian cancer (HGSOC), is the most lethal gynecological tumor, with most patients experiencing recurrence within 5 years. Long-term survival in HGSOC patients with advanced stages is exceedingly rare.Case summaryWe report a case of advanced HGSOC with exceptional long-term recurrence-free survival following initial treatment. In June 2009, the patient underwent suboptimal cytoreductive surgery for stage IIIC ovarian cancer, including total hysterectomy, bilateral salpingo-oophorectomy, omentectomy, appendectomy, and resection of mesenteric and peritoneal lesions. Postoperatively, residual lesions were observed in the mesenteries and para-aortic lymph nodes. Despite unfavorable prognostic factors (advanced stage, aggressive pathology, and incomplete resection), the patient showed remarkable chemosensitivity, remaining recurrence-free for 15 years.ConclusionThe factors influencing long-term survival in HGSOC patients are not yet fully understood. We present this rare case to contribute data for further studies on long-term survival in advanced HGSOC.

Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction

Patients with High-Grade Serous Ovarian Cancer (HGSOC) exhibit varied responses to treatment, with 20–30% showing de novo resistance to platinum-based chemotherapy. While hematoxylin-eosin (H&E)-stained pathological slides are used for routine diagnosis of cancer type, they may also contain diagnostically useful information about treatment response. Our study demonstrates that combining H&E-stained whole slide images (WSIs) with proteomic signatures using a multimodal deep learning framework significantly improves the prediction of platinum response in both discovery and validation cohorts. This method outperforms the Homologous Recombination Deficiency (HRD) score in predicting platinum response and overall patient survival. Our study suggests that histology and proteomics contain complementary information about biological processes determining response to first line platinum treatment in HGSOC. This integrative approach has the potential to improve personalized treatment and provide insights into the therapeutic vulnerabilities of HGSOC.

Stromal PDGFR-beta expression is a prognostic factor in high-grade serous ovarian cancer patients but is it also predictive for response to antiangiogenic treatment?

ObjectiveIn advanced ovarian cancer, the majority of patients receive anti-angiogenic treatment with bevacizumab. However, its use is often associated with severe side effects, and not all patients benefit from the therapy. Currently, there are no reliable biomarkers to predict response to treatment. Given their role as key regulators of angiogenesis, platelet-derived growth factor receptor-beta (PDGFR-beta) and vascular endothelial growth factor receptor-2 (VEGFR-2) are promising candidates for predictive biomarkers. This study evaluates their potential.MethodsPDGFR-beta and VEGFR-2 expression was evaluated using immunohistochemistry in a tissue microarray assay including 391 ovarian tissue samples. Correlation analyses with clinical and histopathological parameters were performed in a homogeneous cohort of 199 high grade serous ovarian cancer samples (HGSOC).ResultsIn HGSOC, strong stromal PDGFR-beta expression was associated with significantly shorter overall survival compared to weak/moderate expression. The impact of stromal PDGFR-beta expression on patient survival was however not restricted to the subgroup of patients receiving therapy with bevacizumab, and therefore cannot be considered as a predictive factor. For VEGFR-2, no or weak protein expression was found in the majority of the tumor samples. Survival analyses showed a more favorable prognosis with no or weak VEGFR-2 expression.ConclusionsHigh stromal expression levels of PDGFR-beta correlate with shorter overall survival in HGSOC. Thus, stromal PDGFR-beta might serve as a prognostic biomarker. No predictive effect in response to bevacizumab therapy could be attributed.

Spatial transcriptome reveals histology-correlated immune signature learnt by deep learning attention mechanism on H&E-stained images for ovarian cancer prognosis

BackgroundThe ability to predict the prognosis of patients with ovarian cancer can greatly improve disease management. However, the knowledge on the mechanism of the prediction is limited. We sought to deconvolute the attention feature learnt by a deep learning convolutional neural networks trained with whole-slide images (WSIs) of hematoxylin-and-eosin (H&E)–stained tumor samples using spatial transcriptomic data.MethodsIn this study, 773 WSIs of H&E-stained tumor sections from 335 patients with treatment naïve high-grade serous ovarian cancer who were included in The Cancer Genome Atlas (TCGA) Pan-Cancer study were used to train, and validate, and to test a ResNet101 CNN model modified with attention mechanism. WSIs from patients in an independent cohort were used to further evaluate the model.ResultsThe prognostic value of the predicted H&E-based survival scores from the trained model on patient survival was evaluated. The attention signals learnt by the model were then examined their correlation with immune signatures using spatial transcriptome. After validating the model with the testing datasets, pathway enrichment analysis showed that the H&E—based survival score significantly correlated with certain immune signatures and this was validated spatially using spatial transcriptome data generated from ovarian cancer FFPE samples by correlating the selected signature and attention signal.ConclusionsIn conclusion, attention mechanism might be useful to identify regions for their specific immune activities. This could guide future pathological study for the useful immunological features that are important in modulating the prognosis of ovarian cancer patients.

The chemokine CX3CL1 promotes intraperitoneal tumour growth despite enhanced T-cell recruitment in ovarian cancer.

T-cell recruiting chemokines are required for a successful immune intervention in ovarian cancer, and also for the efficacy of modern anticancer agents such as PARP inhibitors. The chemokine CX3CL1 recruits tumour-suppressive T-cells into solid tumours, but also mediates cell-cell adhesions, e.g. of tumour cells, through its membrane-bound form. So far, its role in ovarian cancer has only been rudimentarily addressed. We show that high CX3CL1 expression significantly correlates with worsened survival in human high-grade serous ovarian cancer (n=219). In preclinical ovarian cancer, CX3CL1 plays a dual role, as it enhances the adaptive anti-tumour response, but overall still promotes tumour growth, the latter as a feature of the intraperitoneal environment. Moreover, PARP inhibitors are able to increase CX3CL1 release from human ovarian cancer cells. Collectively, our study shows that CX3CL1 is a driver of intraperitoneal tumour growth in ovarian cancer, a feature that may compromise the anticancer effect of CX3CL1-inducing PARP inhibitors.

Niraparib Maintenance Therapy in Patients with Platinum-Sensitive Recurrent Ovarian Cancer: Real-World Experience at Hospitals in Spain.

The reported benefit of poly (ADP-ribose) polymerase inhibitor (PARPi) maintenance in patients with newly diagnosed and platinum (Pt)-sensitive recurrent ovarian cancer (OC) included in randomized clinical trials needs to be corroborated in a less selected population. The aim is to increase the evidence on niraparib in a real-world setting. This is a retrospective observational study including women with platinum-sensitive relapsed high-grade serous OC who started niraparib maintenance between August 2019 (marketing data, Spain) and May 2022. Patients received ≥ 2 previous lines of therapy with complete or partial response to prior chemotherapy. Patient characteristics, niraparib dose, adequacy of dose individualization, effectiveness (progression-free survival [PFS] and overall survival), safety, and economic savings with an individualized starting dose (ISD) strategy were assessed. The study included 217 patients with a median of 8.9 months of niraparib duration: breast cancer gene (BRCA) wild-type OC, 70%; two prior treatment lines, 49%; Research on Adverse Drug Events and Reports (RADAR) criteria, 82% (receiving mainly 200 mg of niraparib, 79%). Median PFS was 10.8 months (95% confidence interval [CI], 8.4-14.8) without statistically significant differences based on starting dose strategy, contrary to what was observed on the basis of prior lines, response to prior chemotherapy, BRCA mutational status, and International Federation of Gynecology and Obstetrics (FIGO) stage at diagnosis. The last three variables also showed a statistically significant predictive prognostic value for effectiveness. Dose interruptions due to toxicity were required in 7% of patients, and dose adjustments in 56% were mainly due to hematologic toxicities. The actual dose of niraparib reveals economic savings versus the theoretical cost. This large real-world analysis corroborates the tolerability and activity of niraparib maintenance for platinum-sensitive recurrent OC and economic savings.

Benchmarking Spatial Co-Localization Methods for Single-Cell Multiplex Imaging Data with Applications to High-Grade Serous Ovarian and Triple Negative Breast Cancer

Benchmarking Spatial Co-Localization Methods for Single-Cell Multiplex Imaging Data with Applications to High-Grade Serous Ovarian and Triple Negative Breast Cancer

Identification of the novel BRCA1 c.2463_2464delTA mutation in two high grade serous ovarian cancer sisters and potential dosage effects implications: a case report.

Ovarian Cancer is one of the leading causes of cancer death among women worldwide and the therapeutic landscape to treat it is constantly evolving. One of the major points of decision for the treatment choice is the presence of some genomic alterations that could confer sensitivity to the new available therapies including inhibitors of poly (ADP-ribose) polymerase (PARPi) with BRCA1 and 2 genes playing the most important role. We performed the search for any somatic and/or germline alteration in patient's samples by next generation sequencing (NGS). On two patients, our bioinformatic tools allowed us to correctly classify the c.2463_2464delTA BRCA1 new variant. The novel BRCA1 c.2463_2464delTA variant which falls into the DNA Binding Domain (DBD) of the BRCA1 gene can be considered as a variant of clinical significance due to the peculiar family and personal history of patients.

Screening Methods to Discover the FDA-Approved Cancer Drug Encorafenib as Optimally Selective for Metallothionein Gene Loss Ovarian Cancer.

All 11 metallothionein protein-coding genes are located on human chromosome 16q13. It is unique among human genetics to have an entire pathway's genes clustered in a short chromosomal region. Since solid tumors, particularly high-grade serous ovarian cancer (HGSC), exhibit high rates of monoallelic aneuploidy, this region is commonly lost. Studies have not yet been performed to determine what vulnerability may be created in cancer cells with low metallothionein expression. Here, a screen of FDA-approved cancer small molecule drugs for those best targeting low metallothionein ovarian cancer was completed. Screening methods were tested and compared using vehicle-treated negative controls and cadmium chloride, a positive control for cell loss selective for low metallothionein cells. CAOV3 cells, which are unique in their expression of only two metallothionein isoforms, were used, with or without shRNA knockdown of the predominantly expressed MT2A gene. A library of FDA-approved molecules was then screened. The optimal assay utilized Hoechst 33342 nuclear staining and mechanized fluorescent microscope counting of cell content. Encorafenib, an RAF inhibitor, was identified as the most selective for enhanced cytotoxicity in MT2A knockdown cells compared to scrambled controls. The nuclear stain Hoechst 33342, assessed by fluorescence microscopy, provides a low variance, moderate throughput platform for cancer cell loss screens. Low metallothionein ovarian cancer cells exhibit a vulnerability to the RAF inhibitor encorafenib.