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 <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

Introduction: Significant resources have been dedicated to the development of patient derived tumor models for precision medicine initiatives, including the NCI's Patient-Derived Models Repository. The majority of efforts are geared towards use of these patient derived in vitro models (3D cultures, organoids) in the pre-clinical drug discovery and development setting or use of patient-derived xenograft models in the co-clinical trial or clinical setting for determining patient-specific therapies. Our company is focused on developing patient-derived models for ex vivo 3D drug response profiling (EV3D) for real time clinical decision making. In this report, we highlight the development, drug testing and early validation efforts of clinically relevant 3D culture platforms amenable to multiple different types of solid tumors and classes of therapies for the purpose of predicting patient response. Methods: With a goal of developing EV3D drug response profiling (DRP) tests to be used by treating physicians for predicting patient response, we focus our report on the intended late validation steps and regulatory considerations necessary for utilizing patient-derived in vitro models for precision medicine initiatives. Lead clinical programs include ovarian, breast, glioblastoma and lung cancer, with NCI-awarded contracts to support the development of more complex ex vivo models to be used for mimicking the tumor microenvironment's role in tumor heterogeneity, therapeutic resistance, and immune-protection. With a clinically impactful and regulated assay in mind, major considerations to be addressed include standardization of cell sources, 3D scaffolds and matrices, drugs and therapeutic application (including timing and combinations) and analytical assays. Methods of correlation of ex vivo drug response with molecular subtype, in vivo response and clinical response (biomarkers and outcomes) are addressed. Finally, considering that no functionally predictive in vitro cancer response assay has yet be fully validated to date, we describe future clinical trial plans aimed at validating our EV3D DRP platforms. Conclusions: Patient-derived ex vivo 3D culture models have great promise for precision medicine initiatives, and our efforts highlight the benefits and barriers involved in developing and validating predictive in vitro 3D assays to be used in the clinic. Ultimately, multisite clinical trials will need to be performed to fully determine the clinical utility of patient-derived 3D models, and the regulatory and logistical aspects of this process must be considered early in the development phase of patient-derived tumor models for truly precision medicine applications. Citation Format: Tessa M. DesRochers, Lillia Holmes, Matt Gevaert, Hal E. Crosswell. Ex vivo 3D functional drug response profiling using patient-derived cancer models: Clinical and regulatory considerations. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr A17.

Surgical resection is rarely an option for small cell lung cancer (SCLC) patients as the majority present with extensive disease at diagnosis. This scarcity of patient samples suitable for research presents a significant road block for the development of SCLC targeted-therapeutics. To address the problem of tissue scarcity, we have developed a method for the isolation and expansion of cancer stem cells (CSC) and circulating tumor cells (CTC) from primary tissues and blood of SCLC patients using the 3DKUBE™ perfusion microbioreactor. We have established a label-free, combined chemical and functional selection method for the isolation of CSCs from SCLC samples, solid tumor as well as blood, that does not rely upon the bias imposed by marker-based selection. Cells enriched in this manner were further purified and expanded under optimized conditions (growth factors, ECM, scaffolding and oxygen tension) within the 3DKUBE™ perfusion microbioreactor. These isolated and expanded CSCs have maintained resistance to cisplatin and etoposide, stabilized the expression of traditional CSC markers, and been validated in vitro through serial spheroid formation assays. These CSCs are currently being characterized and compared to parental tissue through correlative genomic and phenomic analysis and validated through in vivo tumorigenesis models. These cells will be utilized to generate 3D microtumors to accurately predict SCLC drug response in vitro, a determination that is not accurately performed in conventional 2D cell culture and is inhibited by both cost and time in patient-derived xenografts (PDX) Citation Format: Melissa Millard, Alina Lotstein, Lillia Holmes, David Schammel, Ki Chung, Jeff Edenfield, Hal E. Crosswell, Tessa DesRochers. Paired isolation and expansion of CSC and CTC from primary small cell lung cancer patient tissue and blood using the 3DKUBE bioreactor platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1923. doi:10.1158/1538-7445.AM2017-1923

BackgroundImmune checkpoint inhibitors (ICIs) have shifted the cancer treatment paradigm. Cancers such as melanoma and non-small cell lung cancer (NSCLC) demonstrate high tumor mutational burden and tumor neoantigen expression which renders them more responsive to checkpoint inhibitor blockade compared to other malignancies. Yet, 40–65% of metastatic melanoma patients do not have an initial response to ICI therapy1 and in NSCLC, PD-L1 expression, often a prerequisite for ICI treatment, does not definitively associate with ICI clinical response2. Mechanisms of resistance often result from aberrant interactions between tumor and immune cells. Development of pre-clinical models that mimic the complex interplay between cells within the tumor microenvironment in a patient-specific manner are critical for accurate ex vivo profiling of ICIs. To improve immunotherapy predictive testing, we present a 3D spheroid culture system for testing personalized ICI efficacy.MethodsCell lines co-cultured with T-cells from healthy donor peripheral blood mononuclear cells were used to optimize assay conditions and confirm ICI binding to target proteins. For ex vivo testing, primary melanoma or NSCLC tumor tissue from treatment naïve patients was dissociated and cultured as 3D spheroids using autologous immune cells to profile ICI target expression and sensitivity to treatment. ICI enhanced T-cell killing of tumor cells was quantified via lactate dehydrogenase release. Changes in IFNγ were used as a metric for ICI induced immune cell activation. Ratios and activation status of T-cell subsets was determined using flow cytometry. Fluorescent imaging was used to confirm the mechanism of tumor cell killing.ResultsICI binding to target proteins was measured across six ICIs, and no significant differences in concentration-dependent site occupancy within drug target classes was observed. However, differences in drug induced cytotoxicity across different tumor samples was detected even within the same drug target class. The immune composition of tumor samples that responded to ICIs displayed increased T-cell activation and increased IFNγ production. Furthermore, changes in PD-L1 and MHC-class I expression were detected which reflected ICI response. Finally, T-cell-dependent induction of tumor cell apoptosis was confirmed to be the observed mechanism of cytotoxicity within the 3D spheroid system.ConclusionsThis work demonstrates that differences in ICI induced cytotoxicity can accurately be detected using our ex vivo 3D spheroid platform. The differences in therapy sensitivity can be related back to cell composition and function to potentially predict patient-specific drug response. Future correlation to patient clinical outcomes will be necessary for true clinical applications.AcknowledgementsN/ATrial RegistrationN/AEthics ApprovalTissue for this study was procured from commercial vendors who maintain strict ethical compliance, including fully de-identified materials and stringent IRB and Ethics Committee compliance.ConsentN/AReferencesFenton SE, Sosman JA, Chandra S. Resistance mechanisms in melanoma to immuneoncologic therapy with checkpoint inhibitors. Cancer Drug Resistance. 2019;2(3):744–61.Chiang AC, Herbst RS. Frontline immunotherapy for NSCLC - the tale of the tail. Nat Rev Clin Oncol 2020;17(2):73–4.