Although 70–80% of newly diagnosed ovarian cancer patients respond to first-line therapy, almost all relapse and five-year survival remains below 50%. One strategy to increase five-year survival is prolonging time to relapse by improving first-line therapy response. However, no biomarker today can accurately predict individual response to therapy. In this study, we present analytical and prospective clinical validation of a new test that utilizes primary patient tissue in 3D cell culture to make patient-specific response predictions prior to initiation of treatment in the clinic. Test results were generated within seven days of tissue receipt from newly diagnosed ovarian cancer patients obtained at standard surgical debulking or laparoscopic biopsy. Patients were followed for clinical response to chemotherapy. In a study population of 44, the 32 test-predicted Responders had a clinical response rate of 100% across both adjuvant and neoadjuvant treated populations with an overall prediction accuracy of 89% (39 of 44, p < 0.0001). The test also functioned as a prognostic readout with test-predicted Responders having a significantly increased progression-free survival compared to test-predicted Non-Responders, p = 0.01. This correlative accuracy establishes the test’s potential to benefit ovarian cancer patients through accurate prediction of patient-specific response before treatment.

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Background: Epithelial ovarian cancer (EOC) affects nearly 22,000 women annually and is the leading cause of death from gynecologic cancer in the United States. Five year cure rates are &lt;40% and approximately 14,000 will die each year. Large-scale efforts are currently underway to use molecular profiling via next generation sequencing (NGS) technology to guide treatment in cancer patients with poor prognosis, but limited application of NGS in ovarian cancer has been reported. In this report, our previously described Ex Vivo 3D Drug Response Profiling was used to identify response differences between newly diagnosed and relapsed ovarian cancer patients and correlated with NGS of primary tissue. Materials & Methods: Processing of Ovarian Cancers: Under informed consent, ovarian cancer samples were obtained and processed using standard mincing & digestion. 3D spheroids were developed and 3D perfused Ovarian Microtumors were cultured using the 3DKUBE™. Ex Vivo Testing & Analysis: Cultured cells were exposed to clinically relevant concentrations of cytotoxic or targeted agents. Relative IC50s and total percent inhibition were used for ranking compounds. Isolated DNA was sequenced in a CLIA laboratory using a 37-gene NGS panel (GeneTrails®) on the Ion Torrent PGM. Results: Tissues from both newly diagnosed, treatment naive subjects and relapsed subjects were obtained and processed after IRB-approved tissue consent was provided. Spheroid formation was uniform across all malignant tumor types. There was a statistical difference for 3D spheroids treated with Carboplatin formed from either naïve or relapse tissue. The relapse samples had a significantly higher median IC50 than did the naïve samples (70.8 vs. 17.4). This significant difference was not apparent in matched 2D treatment groups. Gemcitabine response varied across tissue type, but did not correlate with traditional biomarkers (i.e. hENT mRNA expression). NGS testing turn-around time was a median of 9 days (range 7-14). Ovarian 3D microtumors were successfully perfuse and tested with targeted agents guided by NGS results, as evidence by a tumor with a mutation of EGFR (p.P265T, clinical significance unknown) with both erlotinib and afatanib demonstrating activity (3.3uM and 0.7uM, respectively). Conclusions: EV3D DRP successfully differentiates carboplatin response and 3D perfusion of microtumors permits ex vivo culture of primary ovarian samples for genotypic-phenotypic response determination. Clinical response data and clinical correlation is ongoing. EV3D DRP permits phenotypic drug response correlation with molecular profiling in real time and may be a clinically relevant functional assay for driver mutation identification and maximal patient response to targeted agent(s). Citation Format: Tessa Desrochers, Stephen Shuford, Christina Mattingly, Lillia Holmes, Matt Gevaert, Jeff Elder, David Orr, Christopher Corless, Larry Puls, Hal E. Crosswell. Ex vivo 3d drug response profiling of primary human ovarian cancer differentiates treatment-naive and relapsed patients and molecular subtypes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-282. doi:10.1158/1538-7445.AM2015-LB-282

Background: PDX have become critical elements of preclinical drug development as they better reflect the heterogeneity, molecular and histopathologic signatures of the original tumor than cell lines or genetically engineered mouse models, and their drug response profiles correlate with clinical response. While PDX models have become a powerful tool in drug discovery and development, limitations include low throughput for broad drug screening, lack of dose-response curves, high cost and progressive loss of human-derived stromal elements over serial passages, restricting utility for certain therapeutic classes. A potential mechanism to overcome the low throughput and high cost of PDX models is the incorporation of ex vivo 3D (EV3D) DRP on cells isolated from early passage PDX models. Thus, we correlated DRP results using PDX with genetic mutations and drug response of PDX tested in vivo. Materials & Methods: Cells were isolated from low-passage triple negative breast, invasive bladder, and non-small cell lung PDX tumors propagated in NSG mice and cultured as 3D spheroids. 3D spheroid cultures were exposed to 15 clinically-relevant chemotherapy and targeted agents and assayed for cell viability over a range of concentrations. Non-linear regression curves were generated and relative IC50s estimated. In vivo response with limited numbers of agents at clinically relevant concentrations (3 including controls) was assessed. Results: 3D cultures and testing were successfully established across all PDX and IC50s were successfully generated in 98% of drugs tested. EV3D DRP of PDX tumors differentiated activity of cytotoxic and targeted agents across tumors of similar histologic site of origin. Gemcitabine (IC50 = .007 versus 27 uM) and docetaxel (0.2 versus 40uM) activity was highly correlated with in vivo response in bladder and breast cancers, respectively, whereas cisplatin was equally active across all tumor types (IC50 = 3-8uM). hENT1 mRNA expression was not predictive of gemcitabine activity. EV3D DRP data correlated with PDX and clinical outcome. It identified Erlotinib as being relatively inactive (3 uM) against lung cancer PDX with an EGFR e19del, T790M mutation which correlated with the outcome seen in the PDX mouse and the clinical patient outcome in which the patient became nonresponsive to erlotinib. Trametinib was highly active against lung cancer PDX with a KRAS G12C mutation (IC50 6.7 × 10-6 versus 1.1 × 10-3) and will be used to perform efficacy studies in the KRAS mutant lung PDX model Conclusions: EV3D DRP predicts in vivo response and correlates with pathway activating mutations. EV3D DRP using PDX may represent a novel high throughput and predictive drug response platform that enables compound ranking for preclinical and clinical applications. Citation Format: Tessa M. DesRochers, Christina Mattingly, Stephen Shuford, Matthew Gevaert, David Orr, Carol Bult, Susie Airhart, Mingshan Cheng, Minan Wang, James Keck, Howland Crosswell. Enhancing drug discovery and development throughput without sacrificing predictivity: ex vivo 3D drug response profiling (DRP) using patient-derived xenografts (PDX). [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 318. doi:10.1158/1538-7445.AM2015-318

Background: A goal of personalized medicine is to identify the most active and safest therapy for individual patients. One method for employing personalized medicine for cancer patients is through testing of a patient's cultured tumor tissue against a panel of predetermined drug candidates. To date, there is no standard platform by which an individual patient's tumor can be tested ex vivo in order to reliably predict if a certain drug or therapy is effective. We describe optimized methods of ex vivo 3D (EV3D™) culture and testing of primary human ovarian cancer for personalized medicine. Our hypothesis was that 3D spheroid cultures from primary human tumors would demonstrate unique growth parameters and distinct ex vivo testing responses compared to traditional 2D cultures. Materials & Methods: Optimization experiments: Methods for comparing 2D and 3D drug response, rapid spheroid formation across multiple cell types and scaffold/media conditions in both static and perfusion cultures were optimized using human cancer cell lines and reagents. Processing of Ovarian Cancers: Under informed consent, ovarian cancer samples were obtained and processed using standard mincing & digestion. Spheroids and 2D monolayers were established after viability assessment. Ex Vivo Testing & Analysis: cultured cells in 2D and 3D were exposed to a clinically relevant concentration range of cytotoxic or targeted agents. Multiple analytical techniques were applied including imaging, metabolism and dsDNA quantification; relative and absolute IC50s and total percent inhibition were used for ranking compounds. Results: Median subject age was 63(29-82), majority of which had advanced stage adenocarcinomas. Carboplatin & taxane based combination therapy was used in &gt;90% of patients. Clinical response and outcomes data collection are ongoing (median follow up 8 months). Spheroid formation was uniform across all malignant tumor types, but low grade lesions trended towards smaller, looser aggregates. All drug tested ex vivo samples were exposed to at least one agent that the subject received. Growth and response to positive control varied between 2D and 3D platforms. Doxorubicin and LY294002 showed greatest activity (median IC50 = 1, 0.8 uM, respectively) and cisplatin and topotecan the least (median IC50 16, 22). Median CA-125 fold reduction from baseline was 16 (range, 1.9-143). The subject with the greatest response by CA-125 levels (143 fold decrease) was predicted to respond to carboplatin-paclitaxel therapy in 3D culture but not in 2D (2D v 3D, p&lt;0.01). Conclusions: EV3D allows for rapid and high throughput phenotypic profiling of novel small molecules (i.e. PI3K inhibitors) as well as conventional, FDA approved cytotoxic agents against patient-specific tumor samples in a relevant tumor microenvironment. EV3D cultures have reduced metabolism, decreased short term growth, and different drug-response profiles than 2D. Next generation exome sequencing of 39 drugable targets will allow genotypic-phenotypic correlation. Clinical data collection is ongoing to correlate ex vivo response with clinical outcomes. Current efforts are focused on developing EV3D as a novel small molecule phenotypic screen for clinical trials and as an in vitro chemo-sensitivity assay for personalized medicine. Citation Format: Stephen Shuford, Rebecca Widener, Chaitra Cheluvaraju, Teresa Desrochers, christina mattingly, Larry Puls, matt gevaert, David Orr, Hal E. Crosswell. Chemotherapy testing of primary human ovarian cancers in an ex vivo 3D culture platform: A novel method of phenotypic profiling for clinical trial selection and personalized medicine. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-36. doi:10.1158/1538-7445.AM2014-LB-36