No abstract

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.

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

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.