281 Measuring immune checkpoint inhibitor efficacy using primary patient-derived 3D spheroids

Background

Cancerous cells can utilize immune checkpoints to escape T-cell-mediated cytotoxicity. Agents that target PD-1, PD-L1 and CTLA4 are collectively deemed immune checkpoint inhibitors (ICIs), and many have been approved for treatment of non-small cell lung cancer (NSCLC) and melanoma. Unfortunately, many patients do not respond to these therapies and often experience disease progression. Immunohistochemistry assays to predict response to ICIs have been inconsistent in their readouts and often patients with low expression levels respond to ICIs. Understanding the determinants of ICI response in individual patients is critical for improving the clinical success of this drug class. Using patient-derived spheroids from NSCLC and melanoma primary tissue, we developed a multi-plexed assay for detecting ICI efficacy.

Methods

Nine NSCLC and 11 melanoma primary tumor samples were dissociated to single cells, classified for immune checkpoint expression and cell content by flow cytometry, and seeded for spheroid formation. Spheroids were treated with pembrolizumab, nivolumab, atezolizumab, ipilimumab or durvalumab across a range of concentrations and monitored for cytotoxicity at 24-hours and viability at 72-hours by multiplexing CellTox™ Green Cytotoxicity Assay and CellTiter-Glo® 3D Cell Viability Assay. IFNγ and granzyme B secretion was assessed using Luminex technology. ICI response was evaluated by determining the concentration-response relationship for all three read-outs.

Results

Increased IFNγ and granzyme B were detected for every ICI in one or more patient samples. ICI-induced IFNγ secretion inversely correlated with PD-1+ immune cells. Durvalumab was significantly more cytotoxic for both NSCLC and melanoma spheroids compared to the other ICIs and significantly reduced spheroid viability with mean spheroid survival decreasing to 19.5% for NSCLC and 58.2% for melanoma. We evaluated if there was an association between durvalumab response and cell composition and found that percent spheroid survival significantly correlated with CD8+ T-cells for both NSCLC (r=-0.7920, p=0.0191) and melanoma (r=-0.6918, p=0.0390). Furthermore, CD8+ T-cells correlated with durvalumab-induced granzyme B secretion for NSCLC (r=-0.7645, p=0.0271) and melanoma (r=-0.7419, p=0.0221).

Conclusions

In this study we show ICI-specific increases in immune-related analytes in a concentration-dependent manner for NSCLC and melanoma patient-derived spheroids. We detected spheroid cytotoxicity following short term ICI treatment which closely mirrored decreased spheroid viability at a later timepoint. Finally, we can decipher response mechanisms as exemplified by durvalumab-induced granzyme B secretion correlating with the presence of CD8+ T-cells which results in reduced spheroid viability for both tested cancer indications.

Single-cell dissection of cellular components and interactions shaping the tumor immune phenotypes in ovarian cancer

Distinct T cell infiltration patterns, i.e., immune infiltrated, excluded, and desert, result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these tumor immune phenotypes remain elusive. Here, we provide a high-resolution dissection of the entire tumor ecosystem through single-cell RNA-sequencing analysis of 15 ovarian tumors. Immune-desert tumors are characterized by unique tumor cell-intrinsic features, including metabolic pathways and low antigen presentation, and an enrichment of monocytes and immature macrophages. Immune-infiltrated and -excluded tumors differ markedly in their T cell composition and fibroblast subsets. Furthermore, our study reveals chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumor cell-T cell cross talk via CXCL16-CXCR6 and stromal-immune cell cross talk via CXCL12/14-CXCR4. Our data highlight potential molecular mechanisms that shape the tumor immune phenotypes and may inform therapeutic strategies to improve clinical benefit from cancer immunotherapies.

Abstract 315: Multifaceted functional assessment of checkpoint inhibitor efficacy using 3D tumor spheroids

Three-dimensional (3D) culture of immortalized cell lines and patient-derived primary cells has been shown to be a more representative in vitro model of tumor biology compared to standard 2D techniques. For immune-oncology, animal models continue to lack the ability to fully recapitulate the human immune system. The use of 3D models to study immunotherapies provides the opportunity to mimic the complex interactions between immune cells and the tumor microenvironment in a fully human system. However, standard well-based assays that measure cell viability prevent the obtainment of useful knowledge on tumor-immune cell interactions and immunotherapy effect on immune cell numbers and viability. To address these limitations, we have developed an in vitro based assay for the visualization and quantitation of T-cell-mediated cell death using fluorescently labeled live tumor cells in a 3D spheroid platform. Enhanced T-cell mediated tumor cell killing using immune checkpoint inhibitors can be detected allowing for real-time evaluation of tumor-specific apoptosis in the presence of cytotoxic T-cells. Moreover, the cytotoxic effects can be inhibited by co-treatment with a blocking anti-CD8 antibody, demonstrating a specific requirement for CD8+ T-cells. In order to detect changes to tumor biology induced by T-cells as well as immune-oncology drug treatments, we monitored dynamic fluctuation of PD-L1 and MHC-I expression using immunofluorescence in the spheroids. Finally, we detected changes in T-cell populations, such as T-cell activation, and changes in CD8+:Treg ratios, induced by tumor spheroids with or without drug treatment using flow cytometry. In summary, we can observe T-cell mediated tumor cell killing and relate drug efficacy back to identified changes in tumor cell and T-cell phenotypes. This multifaceted approach is ideal for the functional evaluation of preclinical I/O agents and for identifying drug combinations as it represents a holistic perspective of drug response.

Citation Format: Katy A. Lassahn, Kathryn M. Appleton, Ashley Elrod, Aaron L. Carlson, Teresa M. DesRochers. Multifaceted functional assessment of checkpoint inhibitor efficacy using 3D tumor spheroids [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 315.

Abstract 6018: The perfused 3DKUBE™ rare tumor assay models in vivo drug response

Models that accurately reflect patient drug response are essential for the clinical design of personalized treatment plans and necessary for preclinical drug development. The advancement of predictive models for rare tumor types is impeded in part, by the relative scarcity of fresh tumor tissue available for study. To address the problem of tissue availability we have developed a label-free, combined functional and chemical selection method for the isolation of rare tumor cancer stem cells (CSC) and circulating tumor cells (CTC) from primary patient tissue and blood. Enriched cells were expanded as 3D microtumors under optimized conditions, validated as CSC through in vivo tumorigenesis studies, and characterized by correlative genomic, proteomic/phosphoproteomic, and phenomic analysis. We found isolation and expansion by this method yielded a source of primary cells suitable for live, cell-based predictive drug screening in multiple rare tumor derived models of neuroendocrine and mesenchymal origin, including locally or regionally advanced and metastatic SCLC, recurrent Merkel Cell Carcinoma, recurrent osteosarcoma and dermatofibrosarcoma protuberans. The 3DKUBE™ rare tumor assay was performed using validated CSCs cultured as perfused 3D microtumors (pMTs). Drug studies using the perfused, 3DKUBE™ rare tumor assay modeled individual patient response better than CSC-based or 3D static microtumor-based drug screens and thus demonstrate the effectiveness of this platform for predictive modeling of individual patient drug response. Taken together, this system provides a means of performing ex vivo drug response experiments on very small tissue samples, including core biopsies, with relevant results for patients.

Citation Format: Melissa Millard, Kathryn M. Appleton, Ashley Elrod, Nicholas W. Bateman, Tamara Abulez, Kelly Conrads, Brian Hood, Thomas P. Conrads, Lillia M. Holmes, Teresa M. DesRochers. The perfused 3DKUBE™ rare tumor assay models in vivo drug response [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6018.

Abstract 2244: PARP inhibition in combination with pembrolizumab enhances cytotoxicity in ovarian cancer patient-derived 3D spheroids

Poly(ADP-ribose) polymerase (PARP) inhibitors have shown impressive clinical activities for ovarian cancer patients with BRCA mutations and have altered the paradigm for ovarian cancer treatment. Despite the utility that PARP inhibitors provide, intrinsic and acquired resistance often limit their effectiveness as a monotherapy, and therefore combination treatment is an attractive alternative for more durable responses. Checkpoint inhibitors have shown impressive efficacy in numerous solid tumor types, but have failed to show meaningful response in ovarian cancer. The role PARP inhibitors play as immune modulators to enhance checkpoint blockade efficacy has just recently emerged indicating that their combination with checkpoint inhibitors may be beneficial over either single agent. A recent phase I/II clinical trial by researchers at the Dana-Farber Cancer Institute demonstrated niraparib in combination with pembrolizumab produced complete or partial responses in 18% of patients with recurrent platinum-resistant ovarian cancer compared to less than a 5% response rate with PARP inhibitors alone (JAMA Oncol. 2019;5(8):1141-1149). Further understanding of the immune modulatory capacity of PARP inhibitors alone and in combination with checkpoint blockade will aid in the prediction of patient response or resistance to therapy. To address this lack in knowledge, we evaluated therapeutic responses to PARP inhibitors, checkpoint inhibitors, and combinations using ovarian cancer patient-derived 3D tumor spheroids. Primary tumor samples were evaluated for PD-L1 and EpCAM expression, and tumor infiltrating lymphocyte (TILs) populations were assessed for T-cell activation and CD8+:Treg ratios. Immune-mediated antitumor activity was investigated by monitoring changes in PD-L1 and MHC class-I expression in the tumor cell populations following PARP inhibition, pembrolizumab treatment, and in combination. The effects of pembrolizumab alone and in combination for enhanced T-cell mediated tumor cell killing were also tested. PD-L1 expression was associated with response to pembrolizumab, and pembrolizumab induced tumor cell killing was T-cell dependent. Despite detection of cytotoxic activity by olaparib and pembrolizumab as single agents, increased tumor cell killing was detected when olaparib and pembrolizumab were used in combination. In summary, we detected therapy related modulation of tumor cells as well as the immune composition which results in decreased tumor spheroid viability in the presence of PARP inhibition in combination with checkpoint blockade. These results highlight the potential benefit of PARP/checkpoint inhibitor combination therapy and of patient-derived 3D spheroids as a platform to help identify subsets of cancer patients who would likely respond to immunotherapies as single agents or in combination with other approved agents.

Citation Format: Kathryn M. Appleton, Ashley Elrod, Stephen Shuford, Teresa M. DesRochers. PARP inhibition in combination with pembrolizumab enhances cytotoxicity in ovarian cancer patient-derived 3D spheroids [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2244.

Prospective Validation of an Ex Vivo, Patient-Derived 3D Spheroid Model for Response Predictions in Newly Diagnosed Ovarian Cancer

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.

Abstract 500: Predicting patient response to immuno-oncology agents in vitro using 3D cultures

Immuno-oncology (I/O) based therapeutics, including cellular therapies and checkpoint inhibitors have surged in the last 2 years, but the technology to accurately test them in a pre-clinical setting is significantly lacking. While animal models have tried to provide accurate testing platforms, the ultimate goal of a matched patient tumor and immune system is not achievable in mice. To overcome this issue, we have developed two 3D tissue systems for in vitro testing that combine a patient’s tumor cells and autologous immune cells for accurate testing and prediction. We hypothesize that our 3D cell culture systems can recapitulate the patient’s tumor microenvironment to detect I/O response. Our spheroid-based system allows us to monitor how primary T-cells are affected by paired tumor cells and/or the PD-1 inhibitor pembrolizumab using flow cytometry. We have successfully detected pembrolizumab binding to T-cells in a dose dependent manner, clonal expansion of lymphocyte populations, as well as increased expression of activation markers on CD3+ cells following combination with tumor cells and exposure to pembrolizumab. This model also accurately detects CD3+CD8+ T-cell mediated tumor cell death and can be used to track changes in secreted cytokines and chemokines such as Granzyme B and IFN gamma. Our second model, a 3D microtumor platform, allows us to detect immune cell migration and infiltration and therapy related cell death. Our results show pembrolizumab can increase lymphocyte infiltration while simultaneously decreasing microtumor growth in matched patient samples whose tumor cells express PD-L1 and whose lymphocytes are CD8+. Cytokine secretion detected by multiplex technology from our microtumor model supports our observed enhanced T-cell activation in the presence of pembrolizumab. The data generated from our two complex 3D in vitro models can recapitulate in vivo biology in order to derive correlations to I/O drug response. These models can be utilized for preclinical testing of new I/O agents as well as for patient response predictions to I/O therapies.

Citation Format: Kathryn M. Appleton, Qi Guo, Ashley Elrod, Alina Lotstein, Lillia Holmes, Teresa M. DesRochers. Predicting patient response to immuno-oncology agents in vitro using 3D cultures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 500.

Abstract 5673: Complex, patient-derived, multi-cell type, 3D models of breast cancer for personalized prediction of therapeutic response

Breast cancer survival has drastically improved over the past decades; however, drug resistance and subsequent disease progression is responsible for the incurability of advanced disease. While the focus of many drug response studies is the transformed tumor cells, there is increasing evidence suggesting a role for stromal cells in tumorigenesis and drug resistance. Microenvironmental components, including extracellular matrix, fibroblasts, leukocytes, and adipocytes, all contribute to physiological mammary gland biogenesis. Accordingly, these stromal elements contribute to disease progression and resistance. However, many in vitro drug response studies still utilize 2D monolayer cultures with purified breast tumor cells. In vivo studies remain the gold standard for drug development, even though they are performed with immune-compromised mice that may not reflect the physiological tumor microenvironment and have been repeatedly shown to be a poor representation of clinical outcomes. Thus, there is a need for more complex in vitro models to test drug response effectively and accurately. We have previously demonstrated the benefits of using a patient-derived, tri-culture (3x), 3D perfusion microtumor (3DpMT) system. To further replicate the complex tumor microenvironment, we have expanded to a penta-culture (5x) model by incorporating macrophages and lymphocytes alongside the tumor cells, fibroblasts, and adipocytes of the 3x model. We have accrued over 207 primary tumor samples, including both resected tumor and core biopsies, from which we have generated 12 stable PDX models (~50% ER+) and &gt;20 3x, 4x, and 5x 3DpMT with a focus on triple negative (TNBC). The 5x patient-derived 3DpMT tissues represent our most complex breast cancer in vitro model and have been cultured successfully for up to 5 weeks allowing for high-throughput, long term drug response testing with different dosing strategies. They have been characterized by flow cytometry, IHC, RNA expression, NGS, DNA methylation patterns, and cytokine/chemokine secretion. When possible, marker expression has been compared to the primary tumor. Furthermore, the accuracy of our models to replicate clinical tissue is evident in the similar toxicities of chemotherapies observed in clinical use. With these models we can replicate physiological processes including cell migration, polarization of macrophages, activation of lymphocytes, and changes in molecular profiles throughout the duration of our 5x culture assays. Our model has the potential to test a myriad of drugs, from conventional chemotherapies to novel immunotherapies over extended time periods with different dosing strategies in order to provide a more accurate prediction of patient-specific clinical response.

Citation Format: Qi Guo, Melissa Millard, Christine Wilhelm, Ashley Elrod, Nick Erdman, Lacey E. Dobrolecki, Brian McKinley, Mary Rippon, Wendy Cornett, John Rinkliff, Amanda Scopteuolo, Linda Gray, James Epling, Barbara Garner, Jeff Hanna, Eric McGill, C. David Williams, David Schammel, David L. Kaplan, Christopher Corless, Jeff Edenfield, Michael T. Lewis, Howland E. Crosswell, Teresa M. DesRochers. Complex, patient-derived, multi-cell type, 3D models of breast cancer for personalized prediction of therapeutic response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5673.