Treatment Of High-grade Serous Ovarian Cancer Research Articles

Beacon: A phase II study of bevacizumab, atezolizumab, and cobimetinib in patients with recurrent, platinum resistant, high grade serous ovarian cancer.

5565 Background: Platinum resistant high grade serous ovarian cancer (HGSC) is associated with a poor prognosis and limited treatment options. Immune checkpoint inhibitors have failed to show significant impact in treatment of HGSC to date. Bevacizumab (anti-VEGF) and atezolizumab (anti-PDL1) have shown synergy in multiple cancer types. Cobimetinib (MEK inhibitor) may also potentiate immune responses, particularly by altering the tumour microenvironment. We sought to evaluate the efficacy of cobimetinib, bevacizumab and atezolizumab in women with platinum resistant HGSC. Methods: BEACON is a Phase II single arm study of cobimetinib (60mg oral D1-21 q 28-days), bevacizumab (5mg/kg IV q2w) and atezolizumab (840mg IV q2w from Cycle 2) in patients with platinum-resistant recurrent HGSC. Patients continued therapy until progression or unacceptable toxicity. The primary endpoint was overall response rate (ORR) according to RECIST 1.1 at 24 weeks. Secondary endpoints included best overall response (BOR), safety, progression free survival, and response duration. Correlative studies on paired tumor biopsy and blood samples will explore molecular characteristics/subtypes and potential biomarkers of response as exploratory objectives. This study has now completed accrual and we present the 24-week response data, with a data cut off 21st December 2023. Results: Twenty-nine patients were enrolled between September 2018 and June 2023. Median age was 62 years (range 37 - 79) and 97% had received ≥ 2 prior lines of chemotherapy. The median number of cycles received was 3 cycles of atezolizumab and cobimetinib, and 4 cycles of bevacizumab. The ORR at 24 weeks was 21% [95% CI: 8-40], and a further 28% had stable disease as assessed per RECIST. Five patients (17%) have remained on study treatment for ≥ 52 weeks to date, suggesting that in some patients there was durable disease control. In terms of safety, 22 patients (76%) required a dose reduction in cobimetinib, mainly due to gastrointestinal and skin toxicity. Seventeen patients (59%) experienced a ≥Grade 3 treatment related adverse event, most commonly hypertension (6 patients, 21%). Two patients (7%) discontinued all study treatments due to toxicity. Conclusions: Preliminary results from this study show promising efficacy with the combination of atezolizumab, bevacizumab and cobimetinib in platinum resistant HGSC. Duration of response, progression free survival data and translational data exploring molecular characteristics will be presented as data matures. Clinical trial information: NCT03363867 . [Table: see text]

Abstract 231: Live cell painting of drug responses in high grade serous cancer organoids

Abstract While most patients with high grade serous ovarian cancer (HGSC) respond to platinum-based chemotherapy, the response is rarely durable and recurrence almost inevitable. A characteristic of HGSC is defective DNA repair. A class of drugs called PARP inhibitors (PARPi) exploit this vulnerability and have proven useful in delaying recurrence. However, resistance is inevitable. In models of HGSC a protein that frequently confers resistance is called Bcl-xL, a member of the Bcl-2 family of proteins that prevent apoptosis. If treating the patients with a PARPi makes cancer cells dependent on Bcl-xL then adding an inhibitor of Bcl-xL to their treatment would be sufficient to cause the cancer cells to die. To test this, we have initiated companion studies for a clinical trial in which patients that have had a recurrence after receiving platinum-based therapy will first be treated with the PARPi Olaparib and then, an inhibitor of Bcl-xL, Navitoclax, will be added to their course of treatment. The idea is that for some women this will provide the one-two-punch needed to eliminate the cancer or at least dramatically prolong response. However, Bcl-xL is only one of the five known inhibitors of apoptosis. To identify which women will benefit most from adding Navitoclax to their treatment we need a biomarker(s). An ideal biomarker would also let us determine for other women which inhibitor of Bcl-2 proteins would be best combined with a PARPi. Our hypothesis is that patient derived organoids can be used as a pragmatic way to identify for individual patients which Bcl-2 protein inhibitor will synergize with a PARPi to optimize treatment. We are using organoids to develop biomarkers for High Grade Serous Cancer (HGSC) treatment response. Organoids generated from biopsy samples acquired prior to treatment for HGSC promise to be efficient and reliable experimental models that recapitulate in vitro patient tumors faithfully enough to facilitate translation to therapeutic decisions for patients. By adapting the relatively new technique of conditional reprogramming and combining it with novel methods for cell aggregation and hydrogel based synthetic ECM supports we can reproducibly generate HGSC patient-specific tumor organoids models in weeks with greater than 90% success. Organoids grown 384 well format are stained with novel non-toxic dyes enabling live cell painting of chemoresponses to drugs alone and in combination with drugs targeting anti-apoptotic proteins. Our data suggest that this approach captures the inherent heterogeneity of the disease, albeit local to the sampled site. We are now employing deep learning AI algorithms to enable automated analyses of 3D confocal image stacks of organoids to infer drug responses that will be compared to patient responses in ongoing clinical trials. Citation Format: David W. Andrews, Betty Li, Wiebke Schormann, Alla Buzina, Lilian Gien, Helen MacKay. Live cell painting of drug responses in high grade serous cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 231.

Abstract B027: Screening of drug candidates to repurpose for high-grade serous ovarian cancer treatment

Abstract B027: Screening of drug candidates to repurpose for high-grade serous ovarian cancer treatment

Abstract B019: Investigating Cannabis sativa bioactive compounds as an anti-cancer treatment in high-grade serous ovarian cancer

Abstract B019: Investigating <i>Cannabis sativa</i> bioactive compounds as an anti-cancer treatment in high-grade serous ovarian cancer

Biology-driven therapy advances in high-grade serous ovarian cancer.

Following a period of slow progress, the completion of genome sequencing and the paradigm shift relative to the cell of origin for high grade serous ovarian cancer (HGSOC) led to a new perspective on the biology and therapeutic solutions for this deadly cancer. Experimental models were revisited to address old questions, and improved tools were generated. Additional pathways emerging as drivers of ovarian tumorigenesis and key dependencies for therapeutic targeting, in particular, VEGF-driven angiogenesis and homologous recombination deficiency, were discovered. Molecular profiling of histological subtypes of ovarian cancer defined distinct genetic events for each entity, enabling the first attempts toward personalized treatment. Armed with this knowledge, HGSOC treatment was revised to include new agents. Among them, PARP inhibitors (PARPis) were shown to induce unprecedented improvement in clinical benefit for selected subsets of patients. Research on mechanisms of resistance to PARPis is beginning to discover vulnerabilities and point to new treatment possibilities. This Review highlights these advances, the remaining challenges, and unsolved problems in the field.

Construction of monocyte-related prognosis model based on comprehensive analysis of bulk RNA-seq and single-cell RNA-seq in high-grade serous ovarian cancer.

High-grade serous ovarian cancer (HGSOC) is a common subtype of ovarian cancer with high mortality. Finding a new biomarker is useful for the diagnosis and treatment of HGSOC. The scRNA and bulk RNA data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The monocyte-related clusters were identified and annotated by Seruat and SingleR package. The Kaplan-Meier and receiver operating characteristic curve was used to determine the prognosis. The differentially expressed genes were determined by limma. The single sample Gene Set Enrichment Analysis, Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes were used for the enrichment function. The correlation between drug activity and gene expression was assessed by rcellminer and rcellminer Data package. We identified 9 cell types and obtained 37 differentially expressed marker genes of monocyte. A2M, CD163, and FPR1 were screened out as hub genes and used to construct risk model in HGSOC through univariate and multivariate cox analysis. Single sample Gene Set Enrichment Analysis showed risk score was related to B cell and T cell signal pathways, and further analysis showed most immune checkpoint genes expressions were upregulated in high-risk score group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis exhibited that hub gene related genes were involved in signal receptor binding and cytokine-cytokine interaction. Low A2M expression and high expression of CD163 and FPR1 were associated with poor prognosis. Gene Set Enrichment Analysis revealed that A2M promoted tumor development through enhancing immune cell related signal pathways, while CD163 and FPR1 inhibited tumor development through activated carcinogenic signal pathways. Drug sensitivity analysis revealed that these hub genes could be potential therapeutic targets for the treatment of HGSOC. We constructed a risk model for the overall survival and explored the potential mechanism of monocyte in HGSOC.

Interactions of Histone Deacetylase 6 with DNA Damage Repair Factors Strengthen its Utility as a Combination Drug Target in High-Grade Serous Ovarian Cancer.

High-grade serous ovarian cancer (HGSOC) is the deadliest gynecologic malignancy in women. The low survival rate is largely due to drug resistance. Approximately 80% of patients who initially respond to treatment relapse and become drug-resistant. The lack of effective second-line therapeutics remains a substantial challenge for BRCA-1/2 wild-type HGSOC patients. Histone Deacetylases (HDACs) are promising targets in HGSOC treatment; however, the mechanism and efficacy of HDAC inhibitors are understudied in HGSOC. In order to consider HDACs as a treatment target, an improved understanding of their function within HGSOC is required. This includes elucidating HDAC6-specific protein-protein interactions. In this study, we carried out substrate trapping followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) to elucidate HDAC6 catalytic domain (CD)-specific interactors in the context of BRCA-1/2 wild-type HGSOC. Overall, this study identified new HDAC6 substrates that may be unique to HGSOC. The HDAC6-CD1 mutant condition contained the largest number of significant proteins compared to the CD2 mutant and the CD1/2 mutant conditions, suggesting the HDAC6-CD1 domain has catalytic activity that is independent of CD2. Among the identified substrates were proteins involved in DNA damage repair including PARP proteins. These findings further justify the use of HDAC inhibitors as a combination treatment with platinum chemotherapy agents and PARP inhibitors in HGSOC.

Abstract 4956: Discovering novel targetable pathways by combining functional and multi-omic data from primary ovarian cancer samples

Abstract Background: There is a critical necessity to reveal novel and tractable targets for anti-cancer treatments in indications with high unmet medical need, such as high grade serous ovarian cancer (HGSOC). However, standard process for target discovery using models such as outgrown cell lines and well-averaged readouts has yielded a less than 5% approval rate for drugs entering trials (Thomas et al. 2016 Bio.org). Here, we describe patient-centric target discovery through the use of disease relevant primary OC samples and single cell functional characterization using a platform with proven hemonc translatability (Kornauth et al. 2021, Snijder et al. 2017). We integrate data from our functional drug testing platform under multiple drug perturbations with matching genomic and transcriptomic data to reveal associations with novel downstream regulators of sensitivity. Methods: Sensitivity of the cancer cell compartment in primary malignant ascites samples (n = 20; 75% HGSOC) to 85 small molecule drugs, was evaluated using a proprietary and translatable deep learning-driven single cell imaging platform (Vladimer et al. 2017). Cancer cell sensitivity from the drugs was combined with WES, bulk-RNAseq and drug induced changes in phosphoproteome, and single cell RNAseq transcriptome to identify perturbed targets and pathways. Results: Here we describe a family of TKIs including ALKi that induce cytotoxicity of cancer cells in primary samples, not previously captured in publicly available cell line drug sensitivity screening data (Iorio et al. 2016). We report novel sensitivity of OC driven by non-canonical targets of ceritinib such as FAK1 or IGF1R, mediated by the downstream signaling hub YBX1 (Kuenzi et al. 2017), involved in NFB pathway regulation (Motolani et al. 2021). Indeed, transcriptomic scRNA analysis upon ceritinib treatment of primary OC cells revealed rapid perturbation of numerous NFB pathway members, alongside YBX1 inactivation. Conclusions: Combining functional endpoints and single cell-based differential expression analysis of primary OC samples, we have identified the NFB pathway and the regulator YBX1 as a promising novel sensitivity for HGSOC treatment development. These and several other important targetable nodes identified, sit outside the recently suggested JAK/STAT pathway (Izar et al. 2020), thereby demonstrating a pipeline towards novel drug target and pathway discovery driven by patient-centric, disease relevant models of high-need indications. Citation Format: Irene Gutierrez-Perez, Bekir Ergüner, Pisanu Buphamalai, Joost Van Ham, Paul Heinz, Valentin Aranha, Rin Okumura, Elisabeth Waltenberger, Isabella Alt, Claudia Baumgaertler, Maja Stulic, Edgar Petru, Christoph Minichsdorfer, Judith Lafleur, Lukas Hefler, Laudia Hadjari, Lucia Dzurillova, Jozef Sufliarsky, Nikolaus Krall, Thorsten Füreder, Gregory Ian Vladimer, Bojan Vilagos, Robert Sehlke. Discovering novel targetable pathways by combining functional and multi-omic data from primary ovarian cancer samples. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4956.

Evaluation of mitochondrial biogenesis and ROS generation in high-grade serous ovarian cancer.

Ovarian cancer is one of the leading causes of death for women with cancer worldwide. Energy requirements for tumor growth in epithelial high-grade serous ovarian cancer (HGSOC) are fulfilled by a combination of aerobic glycolysis and oxidative phosphorylation (OXPHOS). Although reduced OXPHOS activity has emerged as one of the significant contributors to tumor aggressiveness and chemoresistance, up-regulation of mitochondrial antioxidant capacity is required for matrix detachment and colonization into the peritoneal cavity to form malignant ascites in HGSOC patients. However, limited information is available about the mitochondrial biogenesis regulating OXPHOS capacity and generation of mitochondrial reactive oxygen species (mtROS) in HGSOC. To evaluate the modulation of OXPHOS in HGSOC tumor samples and ovarian cancer cell lines, we performed proteomic analyses of proteins involved in mitochondrial energy metabolism and biogenesis and formation of mtROS by immunoblotting and flow cytometry, respectively. We determined that the increased steady-state expression levels of mitochondrial- and nuclear-encoded OXPHOS subunits were associated with increased mitochondrial biogenesis in HGSOC tumors and ovarian cancer cell lines. The more prominent increase in MT-COII expression was in agreement with significant increase in mitochondrial translation factors, TUFM and DARS2. On the other hand, the ovarian cancer cell lines with reduced OXPHOS subunit expression and mitochondrial translation generated the highest levels of mtROS and significantly reduced SOD2 expression. Evaluation of mitochondrial biogenesis suggested that therapies directed against mitochondrial targets, such as those involved in transcription and translation machineries, should be considered in addition to the conventional chemotherapies in HGSOC treatment.

Identification of Tumor Antigens and Immune Subtypes of High-grade Serous Ovarian Cancer for mRNA Vaccine Development.

High-grade serous ovarian cancer (HGSC) is the most common pathology of ovarian cancer and has aggressive characteristics and poor prognosis. mRNA vaccines are a novel tool for cancer immune treatment and may play an important role in HGSC therapy. Our study aimed to explore tumour antigens for vaccine development and identify potential populations amenable to vaccine treatment. Based on transcription data from The Cancer Genome Atlas (TCGA), we identified four tumour-specific antigens for vaccine production: ARPC1B, ELF3, VSTM2L, and IL27RA. In addition to being associated with HGSC patient prognosis, the expression of these antigens was positively correlated with the abundances of antigen-presenting cells (APCs). Furthermore, we stratified HGSC samples into three immune subtypes (IS1-IS3) with different immune characteristics. A corhort from ICGC (International Cancer Genome Consortium) was used to validate. Patients of IS3 had the best prognosis, while patients of IS1 were most likely to benefit from vaccination. There was substantial heterogeneity in immune signatures and immune-associated molecule expression in HGSC. Finally, weighted gene coexpression network analysis (WGCNA) was employed to cluster immune-related genes and explore potential biomarkers related to vaccination. In conclusion, we identified four potential tumour antigens for mRNA vaccine production for HGSC treatment, and the immune subtype could be an important indicator to select suitable HGSC patients to receive vaccination.

Differential histone deacetylase inhibitor-induced perturbations of the global proteome landscape in the setting of high-grade serous ovarian cancer.

High-grade serous ovarian cancer (HGSOC) is the most lethal gynecologic malignancy in women. Its low survival rate is attributed to late detection, relapse, and drug resistance. The lack of effective second-line therapeutics remains a significant challenge. There is an opportunity to incorporate the use of histone deacetylase inhibitors (HDACi) into HGSOC treatment. However, the mechanism and efficacy of HDACi in the context of BRCA-1/2 mutation status is understudied. Therefore, we set out to elucidate how HDACi perturb the proteomic landscape within HGSOC cells. In this work, we used TMT labeling followed by data-dependent acquisition LC-MS/MS to quantitatively determine differences in the global proteomic landscape across HDACi-treated CAOV3, OVCAR3, and COV318 (BRCA-1/2 wildtype) HGSOC cells. We identified significant differences in the HDACi-induced perturbations of global protein regulation across CAOV3, OVCAR3, and COV318 cells. The HDACi Vorinostat and Romidepsin were identified as being the least and most effective in inhibiting HDAC activity across the three cell lines, respectively. Our results provide a justification for the further investigation of the functional mechanisms associated with the differential efficacy of FDA-approved HDACi within the context of HGSOC. This will enhance the efficacy of targeted HGSOC therapeutic treatment modalities that include HDACi.

CCNE1 is a potential target of Metformin for tumor suppression of ovarian high-grade serous carcinoma

ABSTRACT High-grade serous ovarian cancer (HGSOC) is the most common and malignant type of ovarian cancer, accounting for 70%–80% of mortality. However, the treatment of HGSOC has improved little in the past few decades. Metformin is the first-line medication for the treatment of type 2 diabetes and has now gained more attention in cancer treatment. In this study, we sought to identify potential hub genes that metformin could target in the treatment of HGSOC. We downloaded GSE69428 and GSE69429 in the Gene Expression Omnibus database and performed the bioinformatics analysis. Subsequently, we analyzed the effect of Metformin in HGSOC through biological experiments. Molecular simulation docking was used to predict the interaction of Metformin and CCNE1. We chose CCNE1 for the study based on bioinformatics analysis, literature studies, and preliminary data. We evaluated that CCNE1 is overexpressed in HGSOC tissues and found that HGSOC cells with high CCNE1 expression increase sensitivity to Metformin treatment in the analysis of cell proliferation and anchorage-independent growth. Metformin could inhibit the expression of CCNE1, which is associated with the anti-proliferative effect of tumor cells. Moreover, Metformin could ameliorate the tumor growth in syngeneic orthotopic transplantation mouse models and xenograft tumorigenesis models. Furthermore, molecular simulation docking showed that Metformin may bind to CCNE1 protein, suggesting that CCNE1 could be a potential target for Metformin. Our data revealed that Metformin has antitumor effects on ovarian cancer and CCNE1 could be a potential target for Metformin.

Linoleic Acid-Glucosamine Hybrid for Endogenous Iron-Activated Ferroptosis Therapy in High-Grade Serous Ovarian Cancer.

As the most common subtype in ovarian malignancies, high-grade serous ovarian cancer (HGSOC) made less therapeutic progress in past decades due to the lack of effective drug-able targets. Herein, an effective linoleic acid (LA) and glucosamine (GlcN) hybrid (LA-GlcN) was synthesized for the treatment of HGSOC. The GlcN was introduced to recognize the glucose transporter 1 (GLUT 1) overexpressed in tumor cells to enhance the uptake of LA-GlcN, and the unsaturated LA was employed to trigger ferroptosis by iron-dependent lipid peroxidation. Since the iron content of HGSOC was ∼5 and 2 times, respectively, higher than that of the normal ovarian cells and low-grade serous ovarian cancer cells, these excess irons make them a good target to enhance the ferroptosis of LA-GlcN. The in vitro study demonstrated that LA-GlcN could selectively kill HGSOC cells without affecting normal cells; the in vivo study revealed that LA-GlcN at the dose of 50 mg kg-1 achieved a comparable tumor inhibition as doxorubicin hydrochloride (4 mg kg-1) while the overall survival of mice was extended largely due to the low toxicity, and when the dose was increased to 100 mg kg-1, the therapeutic outcomes could be improved further. This dietary hybrid which targets the excess endogenous iron to activate ferroptosis represents a promising drug for HGSOC treatment.

Serum LAG-3 is associated with improved patient prognosis in high grade serous ovarian cancer (203)

<b>Objectives:</b> With a five-year survival rate of only 39%, high-grade serous ovarian cancer (HGSOC) is the deadliest gynecologic cancer and a fifth leading cause of cancer-related deaths in women. Prior research has demonstrated a poor response to PD-1 based immunotherapy, despite the fact that ovarian tumors are considered immunogenic, highlighting a need to identify novel prognostic and therapeutic immunologic factors. Our prior data demonstrated intratumoral levels of immune co-inhibitory receptor LAG-3 as a marker of improved survival in HGSOC patients. In this study, we sought to evaluate the prognostic utility of serum-based LAG-3 and determine the variation in circulating LAG-3 levels in response to standard chemotherapy. <b>Methods:</b> Serum samples from patients with HGSOC were obtained from the Department of Special Testing and the Program in Women's Oncology Gynecologic Tissue Bank at Women and Infants Hospital. A total of 43 HGSOC treatment naïve serum samples were tested for serum LAG-3 and PD-1. In 20 of these patients, samples during and post- frontline platinum-based chemotherapy were analyzed. A commercially available ELISA kit was employed to detect serum LAG-3 and PD-1. This study was approved by the Women and Infants Institutional Review Board. <b>Results:</b> Pre-, on- and post-serum LAG-3 levels following frontline chemotherapy were not significantly changed. The median levels of LAG-3 decreased with the initiation of therapy, which persisted post-treatment. Kaplan-Meier curves analysis demonstrated longer progression-free survival (PFS) in patients with higher pre-treatment LAG-3 concentrations stratified by both median (HR: 0.4916, logrank p=0.022) and quartile (HR: 0.2679, log-rank p=0.0031) (Figure 1). In comparison, higher pre-treatment serum PD-1 levels were only found to be statistically significantly associated with an improved PFS when stratified by quartile (HR: 0.3894, log-rank p=0.0299) (Figure 1). Finally, upon stratification of patients by chemoresistant versus chemosensitive disease, it was revealed that patients with a PFS of six months or less had a significantly (p=0.0031) lower mean rank of pre-treatment serum LAG-3 when compared to patients with a PFS of 18 months or greater. <b>Conclusions:</b> These findings demonstrate that circulating immune checkpoint receptors have prognostic capabilities in HGSOC. Furthermore, our data suggest that circulating LAG-3 is an improved marker of prognosis compared to PD-1. Future directions include expanding upon our initial cohort size to validate these results.

Abstract 3790: A study of evolutionary dynamics induced by carboplatin, olaparib and paclitaxel in high-grade serous ovarian cancer cell line models

Abstract Background High-grade serous ovarian cancer (HGSOC) is characterized by extensive intratumoral heterogeneity, which is associated with drug resistance. Our aim was to study the effects of drugs used in the treatment of HGSOC - carboplatin (C), paclitaxel (P) and olaparib (O) - on clonal dynamics in experimental models. Methods We tracked clonal evolution in PEO1, a BRCA2-mutant HGSOC cell line model, by transfecting an initial population of 1.714x106 cells with a barcode (BC) library (CloneTrackerXP). Barcoded populations of cells (18.73x106 cells/flask) were grown in HYPERflasks till confluence, and then replicates were exposed to C (3163 nM) for 5 weeks, P (6.32 nM) for 4 weeks, and O (28467 nM) for 5 weeks (as single agents), reducing the cell population to &amp;lt; 10% (controls kept till cell confluence in the absence of drugs). After that, drug pressure was removed, allowing cells to regrow fully. NGS was used to quantify BCs in the final cell populations and, to get information on the temporal dynamics, also in dead floating cells collected from the weekly culture media change. Heterogeneity of the cell populations was estimated using the Shannon diversity index (SDI). Results The SDI in the controls was 6.306 (95% Bootstrap CI 6.304-6.310) for C and 6.192 (95% Bootstrap CI 6.190-6.197) for P and O. After exposure to C, P and O, the SDI was reduced to 3.208, 2.520 and 4.753 (95% Bootstrap CI 3.209-3.211, 2.517-2.523, 4.750-4.759) respectively, using aggregated replicates (pairwise 2-sided Hutcheson t-test: p &amp;lt; 2.2e-16 pre-drug exposure vs C, P and O). The number of unique BCs in controls vs C, P and O were 1799 vs 545, 1463 vs 288 and 1463 vs 1270, respectively, demonstrating reduction of heterogeneity and change in frequency of clones following drug selection pressure. Cell populations exposed to C and O share some similar clone selection (approximately 60%). This is important as, although the degree of heterogeneity caused by individual drugs are different (C and P lead to less heterogeneous populations than O), there is some concordance between the remaining clones determined by DNA damaging/DNA damage response inhibitors compared to clone selection following exposure to antimicrotubule agents. The selection pattern of BCs among replicates of the different drugs was similar with conservation of BCs with the highest fitness, demonstrating that the initial conditions are determinants of selection under drug exposure. Conclusion Our work, for the first time, quantifies and shows that heterogeneity followed by O therapy is greater than by C and P. Furthermore, the emergent population of cells post-selection pressure was more similar in the C and O groups when compared to P-exposed cells, suggesting correlation in the mechanism of action of drugs and drug resistance/tolerance. Our results also indicate that evolutionary dynamics are largely deterministic and, therefore, can be predictable. Citation Format: Alvaro H. Ingles Russo Garces, Salvatore Milite, Javier Fernandez-Mateos, Bingjie Chen, Lisa Pickard, Adam Stewart, Sara Diaz Sanchez, Rachel Lau, Erica Oliveira, Susana Banerjee, Andrea Sottoriva, Udai Banerji. A study of evolutionary dynamics induced by carboplatin, olaparib and paclitaxel in high-grade serous ovarian cancer cell line models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3790.

Abstract 4071: Utilizing colforsin as a novel therapeutic for high grade serous ovarian cancer treatment

Abstract Epithelial ovarian cancer (EOC) is currently the deadliest gynecological cancer with approximately 20,000 new cases and 15,000 deaths per year in the United States. Ovarian cancer can be stratified into distinct subtypes of which high-grade serous ovarian cancer (HGSOC) comprises 90% of all cases. The majority of HGSOC patients are diagnosed with late-stage disease and have a poor prognosis with a 5-year survival rate of less than 30%. Thus, there is a critical need to develop novel therapeutic strategies to improve patient treatment and survival outcomes. Our lab has recently discovered that the small molecule colforsin has potent anti-cancer properties when used to treat HGSOC in vitro and in vivo. Colforsin is a water-soluble derivative of forskolin, and acts as an activator of cAMP signaling via direct binding and activation of adenylyl cyclase. It is currently in clinical use for treatment of conditions such as glaucoma, diabetes, and liver fibrosis. This makes colforsin a prime candidate for drug repurposing to treat ovarian cancer. Our data show that colforsin can induce cell cycle arrest and cell death in established HGSOC cell line models in vitro. We have also found that colforsin can inhibit tumor growth and tumor burden in an intraperitoneal model of HGSOC using HEYA8 cells. In addition, we have also found that colforsin acts synergistically with cisplatin to cause HGSOC cell death. Taken together, our data show that colforsin has potential as a new therapeutic tool to aid in HGSOC treatment in combination with existing therapies. Citation Format: Matthew Knarr, Hunter Reavis, Marilyn Mitchell, Ronny Drapkin. Utilizing colforsin as a novel therapeutic for high grade serous ovarian cancer treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4071.

Abstract 3930: AI-driven discovery and profiling of GTAEXS-617, a selective and highly potent inhibitor of CDK7

Abstract Background: Uncontrolled cancer cell growth results from genetic lesions that disrupt mechanisms regulating cell cycle progression. Furthermore, these alterations invariably lead to dysregulated transcriptional programs that promote tumourigenesis and tumour growth. Cyclin-dependent kinase (CDK) 7 is an attractive therapeutic target in that it plays a dual role in regulating cell cycle progression and transcription. Knock-down studies and pharmacological inhibition of CDK7 have been shown to severely limit the proliferative capacity of cancer cells in vitro and in vivo. Methods: To overcome challenges associated with therapeutic inhibition of CDK7, we leveraged artificial intelligence-driven drug discovery to generate an orally bioavailable, highly potent and selective small-molecule antagonist of CDK7: GTAEXS-617 (‘617). Results: Using Exscientia’s AI drug discovery platform, we identified ‘617 through synthesis and testing of only 136 compounds. ‘617 demonstrates potent anti-proliferative activity with an average IC50 of 6.6 nM in in vitro models of high-grade serous ovarian cancer (HGSOC) and triple negative breast cancer (TNBC). Associated with its anti-proliferative activity, we demonstrate that ‘617 induces cell cycle arrest, apoptosis, and inhibits several key growth-promoting transcriptional programs. In vivo, treatment of HGSOC and TNBC xenograft tumour-bearing mice with ‘617 results in complete tumour regression, with no impact on body weight. Next, we examined the impact of ‘617 on the viability of tumour and non-transformed immune cells in primary patient ovarian cancer samples using high-content microscopy and single cell phenotypic screening. ‘617 reduced the viability of primary human tumour cells with less cytotoxicity of the immune cell compartment compared to two CDK4/6 inhibitors and another CDK7 inhibitor. Further, two response groups of patient samples began to form, indicating that further investigation may be required into target cell sensitivity that may affect clinical responses. Conclusions: In summary, Excientia’s AI platform enabled rapid and highly efficient discovery of ‘617, an orally bioavailable CDK7 inhibitor, demonstrating potent anti-tumour activity in vivo and preferential activity against primary human tumour cells vs non-transformed immune cells. These data support the advancement of ‘617 towards clinical development. Citation Format: Jérémy Besnard, James Joseph, Haiyun Bai, Ross A. Paveley, Tao Wang, Olivier R. Barbeau, Xiao-Hui Gu, Andrew S. Bell, Mate Somlyay, Christina Taubert, Christophe Boudesco, Gregory Vladimer, Fred Aswad. AI-driven discovery and profiling of GTAEXS-617, a selective and highly potent inhibitor of CDK7 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3930.

Single-Cell RNA Sequencing Reveals the Tissue Architecture in Human High-Grade Serous Ovarian Cancer.

The heterogeneity of high-grade serous ovarian cancer (HGSOC) is not well studied, which severely hinders clinical treatment of HGSOC. Thus, it is necessary to characterize the heterogeneity of HGSOC within its tumor microenvironment (TME). The tumors of 7 treatment-naïve patients with HGSOC at early or late stages and five age-matched nonmalignant ovarian samples were analyzed by deep single-cell RNA sequencing (scRNA-seq). A total of 59,324 single cells obtained from HGSOC and nonmalignant ovarian tissues were sequenced by scRNA-seq. Among those cells, tumor cells were characterized by a set of epithelial-to-mesenchymal transition (EMT)-associated gene signatures, in which a combination of NOTCH1, SNAI2, TGFBR1, and WNT11 was further selected as a genetic panel to predict the poor outcomes of patients with HGSOC. Matrix cancer-associated fibroblasts (mCAF) expressing α-SMA, vimentin, COL3A, COL10A, and MMP11 were the dominant CAFs in HGSOC tumors and could induce EMT properties of ovarian cancer cells in the coculture system. Specific immune cell subsets such as C7-APOBEC3A M1 macrophages, CD8+ TRM, and TEX cells were preferentially enriched in early-stage tumors. In addition, an immune coinhibitory receptor TIGIT was highly expressed on CD8+ TEX cells and TIGIT blockade could significantly reduce ovarian cancer tumor growth in mouse models. Our transcriptomic results analyzed by scRNA-seq delineate an ecosystemic landscape of HGSOC at early or late stages with a focus on its heterogeneity with TME. The major applications of our findings are a four-EMT gene model for prediction of HGSOC patient outcomes, mCAFs' capability of enhancing ovarian cancer cell invasion and potential therapeutic value of anti-TIGIT treatment.

Targeting DUSP Activity as a Treatment for High-Grade Serous Ovarian Carcinoma.

Identifying novel, durable treatments for high-grade serous ovarian cancer (HGSOC) is paramount to extend both progression-free survival (PFS) and overall survival (OS) in patients afflicted with this disease. Dual-specificity phosphatase 1 (DUSP1) was identified as one of seven genes that may significantly affect prognosis in patients with HGSOC; however, the role of DUSP inhibition (DUSPi) in the treatment of HGSOC remains largely unknown. In this study, we show that DUSP1 is highly expressed in HGSOC and confers worse PFS and OS. Further, we corroborate data that show DUSP1 expression is directly associated with therapy resistance. Using a tissue microarray of 137 different serous ovarian carcinomas, we demonstrate the high expression of DUSP1 in primary and recurrent serous ovarian cancer. In both acquired and de novo therapy HGSOC-resistant models, DUSPi both inhibited cellular proliferation and promoted cell death. RPPA analysis of HGSOC cells revealed DUSPi led to the differential regulation of several pathways, including AMPK and mTORC. Further, in a patient-derived xenograft HGSOC model, DUSPi significantly inhibited tumor progression.

Integrated weighted gene co-expression network analysis reveals biomarkers associated with prognosis of high-grade serous ovarian cancer.

BackgroundOvarian cancer is the gynecologic tumor with the highest fatality rate, and high‐grade serous ovarian cancer (HGSOC) is the most common and malignant type of ovarian cancer. One important reason for the poor prognosis of HGSOC is the lack of effective diagnostic and prognostic biomarkers. New biomarkers are necessary for the improvement of treatment strategies and to ensure appropriate healthcare decisions.MethodsTo construct the co‐expression network of HGSOC samples, we applied weighted gene co‐expression network analysis (WGCNA) to assess the proteomic data obtained from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and module‐trait relationship was then analyzed and plotted in a heatmap to choose key module associated with HGSOC. Subsequently, hub genes with high connectivity in key module were identified by Cytoscape software. Furthermore, the biomarkers were selected through survival analysis, followed by evaluation using the relative operating characteristic (ROC) analysis.ResultsA total of 9 modules were identified by WGCNA, and module‐trait analysis revealed that the brown module was significantly associated with HGSOC (cor = 0.7). Ten hub genes with the highest connectivity were selected by protein‐protein interaction analysis. After survival and ROC analysis, ALB, APOB and SERPINA1 were suggested to be the biomarkers, and their protein levels were positively correlated with HGSOC prognosis.ConclusionWe conducted the first gene co‐expression analysis using proteomic data from HGSOC samples, and found that ALB, APOB and SERPINA1 had prognostic value, which might be applied for the treatment of HGSOC in the future.