Kiyatec (United States)

Abstract Unlike cell lines, organoids maintain most of the biological properties of the parental tissue from which the starting cells were isolated including the histology and gene expression. When organoids include clinical annotation, they become a useful, renewable tool for clinical correlation studies, but to be truly predictive the drug profiling assays utilized to screen organoid response must have measurable correlation with patient response. 3D Predict™ is a highly accurate assay that is 89% and 85% predictive of response in first-line ovarian cancer and high-grade gliomas (HGG) respectively. We have developed a panel of organoids that are clinically annotated, include correlative primary tissue 3D Predict™ drug response data, and have been assessed for the recapitulation of primary tissue histology and genomics. Additionally, our organoid models incorporate matched immune cells, a key component of the tumor microenvironment, making them an ideal model for immune-oncology studies. Here we present data on 15 available organoid models across HGG, breast, colorectal and bladder cancer. We have applied these models to drug response studies, including checkpoint inhibitors and shown correlation to primary patient response. The assurance of predictive capacity is unique to KIYATEC’s organoids and is significant because it avoids the pitfalls of comparing drug responses across non-concordant assay platforms while providing assurance that the models are reflective of individual patient response and outcomes. Citation Format: Melissa Millard, Natalie A. Williams, Ashley K. Elrod, Teresa M. DesRochers. Organoids standardized to a clinically validated drug response assay for truly predictive in vitro drug response profiling [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 3086.

Abstract Glioblastoma is an aggressive tumor that is clinically and pathologically heterogeneous, and as such, remains challenging to treat. Response to initial standard treatment is widely variable and patient specific. We describe a cohort of 11 newly diagnosed patients enrolled in the 3D-PREDICT study at a single institution who underwent maximal safe surgical resection with tumor tissue collected prospectively for ex vivo cell culture assays against a panel of commonly used agents, including temozolomide. Nine of eleven patients received concurrent radiation + temozolomide followed by adjuvant temozolomide as per current standard of care. Two patients progressed immediately following concurrent chemoradiation; pseudoprogression was ruled out with short interval repeat imaging and clinical deterioration with pathology confirming recurrent tumor on re-resection in one patient. Median follow-up was 10 months (range 2-18). Outcomes were assessed retrospectively using Kaplan-Meier time-to-event curves, separating into two groups the temozolomide responders (n=4) and temozolomide nonresponders (n=7), as defined by the previously validated assay. The event was reached when radiographic tumor recurrence/progression occurred. Due to limited sample size, statistical significance was not reached, but a trend toward longer time to recurrence was noted among the temozolomide responder group. Continued experience with this tool may help clinicians predict which patients with newly diagnosed glioblastoma will respond well to initial treatment with temozolomide and those that may be more appropriate for clinical trial enrollment, independent of MGMT promoter methylation status. Longer term studies with a larger number of patients will help to determine the true significance of this drug response prediction assay.

Standard first-line treatment of newly diagnosed Glioblastoma (GBM) is primarily radiotherapy and Temozolomide (TMZ) with a strong NCCN recommendation of enrollment in clinical trials. The only biomarker that can currently provide a stratification of strong and poor responders to standard of care is methylation of MGMT which indicates a median PFS of 10.3 months for methylated patients and 5.3 months for unmethylated patients. Development of patient-specific in vitro models of GBM for rapid testing of therapeutic options may yield more efficacious therapies and faster, more accurate assignation of therapies to each patient. To that end, we have developed a multi-faceted, patient-based 3D GBM model with modularity that facilitates increasing levels of model complexity such as the inclusion of immune cell components. Stable populations of glioma stem cells (GSC) from 24 of 41 patient samples have been successfully established, verified for stemness through limited dilution in in vitro and in vivo studies, and cultured long-term with minimal molecular changes, as determined from genetic analyses including RT-PCR arrays and MGMT methylation status, flow cytometry, and IHC. These cell populations have been used to establish and validate our 3D model system as well as generate comparable patient-derived xenografts (PDX). KIYATEC’s 3D microtumor in our 3DKUBE™ perfusion system provides a moderate throughput, dynamic system that is easily controlled to establish complex microtumors. GSC cell populations were cultured in monoculture only, co-cultured with human brain endothelial cells (HBEC), and tri-cultured with HBEC and CD14+ peripheral blood mononuclear cells (PBMC). Three microtumors were characterized by drug response to TMZ and axitinib, IHC, and molecular profiling including RNA expression and MGMT methylation status. Interestingly, increasing the complexity of the microtumor was capable of reestablishing the primary tumor MGMT methylation status if it were lost during culturing. We also generated PDX models from the same 3 patient tumor tissues as the above 3D models. PDX are a low throughput, time consuming, and expensive model that are still utilized for many systemic drug response studies and therefore a good comparator to the 3D tissue models we established. In vitro drug response in the 3D tissue models has been compared to both the matched PDX in vivo drug response and the patient’s clinical response to TMZ and MGMT methylation. Our data supports that KIYATEC’s complex patient-derived GBM model can be successfully used to identify, screen, and characterize novel treatments of GBM.Citation Format: Ashley M. Smith, Lillia Holmes, Lacey E. Dobrolecki, Charles Kanos, Stephen Gardner, Philip Hodge, Michael Lynn, Jeff Edenfield, Michael T. Lewis, Howland E. Crosswell, Teresa M. DesRochers. Ex vivo models of glioblastoma: a comparison of 3D tissues and patient-derived xenografts to clinical response [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 53.

Abstract While immuno-oncology based therapies are rapidly becoming the treatment of choice for many tumor types, the assay systems to accurately test them in preclinical development are lacking. This is primarily due to the complexity and function of the immune system and its interaction with tumors in terms of cell types, cellular recruitment and organization, and microenvironment. The ultimate in vitro systems would 1. Combine patient specific tumor cells with autologous immune cells to counteract cytotoxicity due to interactions between allogeneic lymphocytes and tumor cells, 2. Be designed to force recruitment of lymphocytes and macrophages by the tumor cells and their microenvironment, 3. Promote macrophage polarization and lymphocyte activation that recapitulates the patient's tumor by recapitulating the microenvironment, and 4. Result in tumor cell death that correlates to clinical response, biomarker expression (PD-1, PD-L1, CTLA-4, etc.), and therapy mechanism of action. To develop these systems, we have focused our work on numerous areas with 2 presented here, 1. Checkpoint inhibitors, pembrolizumab and Ipilimumab, in solid tumors such as ovarian cancer and melanoma, and 2. Lymphocyte and Macrophage migration, activation, and polarization in breast cancer. For checkpoint inhibitor studies, we have screened primary ovarian cancer tissues, melanoma, and matching lymphocytes for the expression of PD-1, PD-L1, and CTLA-4 by histology and flow cytometry. Both negative and positive tissues have then been utilized in 3D tissue models to examine the effects of drug upon the tumor cells and the other cell types within the model. We have seen correlation between Pembrolizumab binding to lymphocytes and PD-1 expression and shown further correlation to the expression of PD-L1 on the matching tumor cells and drug efficacy. In breast cancer we have used our complex, multi-cell type models to examine macrophage and lymphocyte migration and recruitment into the tumor. We have also examined the polarization of macrophages in these systems and their impact upon tumor cell viability with the tumor cells promoting M2 macrophage polarization and the M2 macrophages promoting tumor cell viability compared to M1 macrophages. Secreted cytokines as measured by multiplex technology have also supported an immune protective environment with M2 macrophages as seen by changes in IFNγ, IL-10, and TNFα compared to the presence of M1 macrophages. Our data to date reveals that these complex 3D in vitro models have the ability to recapitulate in vivo biology and biomarkers correlated drug response. These models can be used to both predict individual patient response to immune-oncology agents and test new agents for efficacy in a preclinical setting. Citation Format: Kathryn M. Appleton, Alina Lotstein, Qi Guo, Ashley Elrod, Larry Puls, Jeffrey Elder, Lillia Holmes, Howland E. Crosswell, Teresa M. DesRochers. 3D tissue models to predict patient-specific response to immuno-oncology based therapies [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 1154.

Abstract The immune system plays an active role in both the prevention and the promotion of cancer dependent upon its interaction with the tumor cells. The roles of both macrophages and T-cells in cancer progression have been heavily studied over the past few years. Macrophages have been found to be either tumor promoting or tumor preventing depending upon their differentiation status and the tumor microenvironment while the homing and cell destroying capabilities of T-cells have been manipulated to effect better, more specific tumor cell cytotoxicity through the development of therapies such as chimeric antigen receptor T-cells (CAR-T cells). Unfortunately the majority of research in the area of immune-oncology has relied upon either 2D cell culture or animal models. While a large amount of information has been learned from these models, it has been well established that 2D cell culture does not mimic in vivo biology and the immune system of mouse models differs from that of humans in numerous ways including T-cell subsets, cytokine receptors, and costimulatory molecule expression. To overcome these limitations, we have developed a number of 3D in vitro tissue models including multi-cell type models of glioblastoma (GBM), breast, and ovarian cancer. Our GBM model combines tumor cells, endothelial cells, and macrophages; the ovarian cancer model includes patient-derived tumor cells and macrophages; our breast cancer model incorporates 5 cell types including tumor cells, fibroblasts, adipocytes, endothelial cells, and macrophages. We have also begun preliminary work to incorporate patient-specific T-cells into these models. Preliminary work in GBM and breast has utilized a combination of cell lines and primary cells while ovarian modeling has relied solely upon primary patient cells from either solid tumors or ascitic fluid. These models have been characterized for tumor cell viability, biomarker expression, and drug response. We have noted changes in both tumor cell viability and biomarker expression dependent upon macrophage differentiation and have also observed the reciprocal effect of tumor cells upon the macrophages. Additionally, employing multiphoton microscopy we have identified the incorporation of macrophages into the 3D microtumors. Utilizing primary patient tumor cells and immune components, we can test these models for patient-specific responses to not only traditional chemotherapeutics, but also immunotherapies such as CAR-Ts and antibody drug conjugates. Citation Format: Tessa M. DesRochers, Lillia Holmes, Qi Guo, Lauren O’Donnell, Stephen Shuford, Larry Puls, Jeff Elder, Jeff Edenfield, Hal E. Crosswell. Complex, 3D tissues for modeling the immune response in cancer and predicting the activity of immunotherapies. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5119.

Abstract 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

Abstract Background: The tumor microenvironment (TME) is a 3D, dynamic interaction between tumor and stromal cells, extracellular matrix, and soluble factors which can promote tumor progression and resistance to therapy. Significant efforts are being made to develop long-term in vitro TME models to study cancer biology, improve drug development, and guide clinical decisions. We have developed a cost-effective micro-bioreactor culture device which enables a wide variety of dynamic cellular and TME interactions that can be monitored with in situ, label free, and non-lytic microscopic analysis. Using the 3DKUBE™, we developed a 3D breast cancer model composed of MCF-7 cells and fibroblasts in segregated co-culture and identified a highly active PI3K inhibitor that had limited activity in 2D monoculture. Based on a more complex morphologic and functional 3D mammary gland model that incorporates multiple human primary cells including epithelial cells (HuMEC), mammary fibroblasts, and adipocytes, our long-term 3D perfused tri-culture breast cancer model is designed to evaluate drug response continuously using non-lytic analysis. We theorize that different breast cancer epithelial cells will be supported in a standard 3D stromal platform which supports mammary gland function. Herein, we describe the 3DKUBE™ modifications and early optimization of a defined stromal TME which supports HuMECs in 3D perfusion. Materials & Methods: Primary human cells were used to optimize seeding conditions for silk fibroin scaffolds containing Matrigel™/collagen hydrogels, including, media composition, cellular ratios, flow rates, and analytical methods for the 3DKUBE™. Destructive analytical methods included morphology (H&E), phenotype (histology), viability & survival (CyQuant, TUNEL, Ki-67), and ER, PR, and casein expression (RT-PCR). Non-lytic assays included metabolism (resazurin reduction), cytotoxicity (LDH release), soluble biomarker expression (xMAP™), and two-photon emission fluorescence via multiphoton microscopy (MPM). Results: The 3DKUBE™ imaging window (1.25 mm thick with a refractive index of 1.590, transmittance (~90%) at wavelengths >290 nm) was replaced with a No. 1.5 glass, high resolution window allowing non-destructive, in situ microscopic imaging. MPM images obtained provided cellular detail (granularity, nuclear-cytoplasmic ratio, size). Optimization of the media conditions and cell numbers revealed that a tri-culture ratio of 1:1:1 was stable in the silk-Matrigel-collagen scaffold during prolonged static and perfusion culture in mixed media. Differentiation of adipocytes had to be performed separately from the tri-culture due to the cytotoxicity of the differentiation media to the epithelial cells. This was achieved via a serial seeding and differentiation method. Our initial drug studies revealed that cytotoxicity could be monitored over the course of a week by multiple methods, including LDH secretion, Presto blue, and CyQuant. Though non-specific drug binding (CPT-11) was seen in the complex 3D matrix, it did not materially impact total drug concentrations. Conclusions: Our current optimization results indicate our ability to grow a bioengineered 3D human breast tri-culture model under perfusion using the 3DKUBE™ while monitoring tissue structure, function, and drug response through both lytic and non-lytic methods. Future Development: The optimized perfused stroma will be used to develop ex vivo breast microtumors of clinically relevant subtypes (ER+, Her+, triple negative) validated against targeted agents. If validated, these 3D microtumors may be applied as predictive phenotypic screens to improve preclinical and clinical breast cancer drug development. Citation Format: Teresa M. DesRochers, Stephen Shuford, Terri F. Bruce, Matthew R. Gevaert, Chaitra Cheluvaraju, Irene Georgakoudi, David L. Kaplan, Davie E. Orr, Howland E. Crosswell. Development of a perfusion-based 3D human tri-culture breast microtumor. [abstract]. In: Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; 2014 Feb 26-Mar 1; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(1 Suppl):Abstract nr A40. doi:10.1158/1538-7445.CHTME14-A40