Microphysiological platform for analyzing multiple myeloma's tumor microenvironment, enabling immunotherapy assessment and drug screening. - ABSTRACT The tumor microenvironment (TME) plays a critical role in hematologic malignancies, especially in multiple myeloma (MM). Each cellular and non-cellular component of the TME exerts a different effect on MM cell survival, proliferation, immune evasion, and resistance to treatment. Several studies have shown that CAR- T therapy produces an overall response rate of 78% in the relapsed/refractory MM setting; however, many patients still relapse, and the median time to disease progression is about 1 year. Therefore, there is an urgent need to define mechanisms of disease progression and resistance to CAR-T and bispecific antibodies using an in vitro cell culture system that mimics the complex TME. Continuous progress in tissue engineering, including the development of various 3D scaffolds and microfluidic systems, has improved the diversity, fidelity, and capacity of culture models that can be used in cancer and other disease research. Most 3D in vitro culture systems lack the integral TME and dynamic perfusion and/or influence immune-tumor crosstalk or/and prolonged culture capabilities. In addition, most models cannot mimic the hypoxic gradients observed in tumors, which dramatically reduces the efficacy of molecular and cellular therapeutics. The hypoxic TME likely protects tumors against immunotherapies by altering cellular metabolism and inducing immune suppression. Therefore, an ideal experimental in vitro cell culture system should mimic the heterogeneous nature of the hypoxic TME to allow a more complete understanding of cancer cell and immune cell biology, immunotherapy validation, and development of efficacious treatment strategies for clinical application. To address the aforementioned limitations, in this proposal, we will focus on developing a novel microfluidic droplet-based platform (MDP) technology to generate and analyze a 3D biomimetic multicellular immunogenic tumor model and test its capabilities to (1) establish multiple levels of hypoxia within the same tumor-chip for parallel processing; (2) investigate spatiotemporal interaction between TME cancer- immune cells during therapy; (3) quantify the impact of state-of-the-art targeted immunotherapy efficacy and define multiparametric (dynamic, secretomic, and transcriptomic) responses for a comprehensive analysis of cell fate. We will incorporate patient tumor cells and their microenvironment in MDP to predict the status of the patient as a potential responder or non-responder. Potential responders to immunologic therapy such as CAR-T will benefit from not having to wait for several months in clinic to determine whether the therapy has achieved response or not, while potential non-responders will be spared the side-effects of non-effective treatment and help clinicians choose other forms of therapy. Our approach will therefore result in the development of a versatile and multifunctional system that can serve as a new and innovative technology for deep analysis of cell-cell interactions and predicting the optimal therapy for individual patients and significantly advance the goal of personalized medicine.
