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Graduate Category: Health Sciences Degree Level: Doctoral Abstract ID# 1244
Dynamic Profiling of Immuno-­‐Oncological Interac6on for Mul6ple Myeloma at Single Cell Resolu6on Using Droplet Microfluidics Pooja Sabhachandani 1*, Saheli Sarkar 1*, Dina Stroopinksi 2, Kristen Palmer 2, Noa Cohen 1, Jacalyn Rosenbla@ 2, David Avigan2 and Tania Konry1 1 Northeastern University, PharmaceuEcal Science, Boston, MA, 2 Beth Israel Deaconess Medical Centre, Medicine, Boston, MA *Equal ContribuEon ABSTRACT: Immune escape mechanisms are used by tumors to evade immune surveillance, which promotes progression of cancer. Cell-­‐based vaccines are being widely studied as therapeuEc agents to induce clinically meaningful anE-­‐tumor immunity. However, heterogeneity in immune interacEons could compromise the efficacy of these vaccines. Thus, interrogaEon of cell based vaccines at various stages of acEvaEon and effector funcEon at single cell level may be of consequence in assessing the beneficial effects of vaccines in tumor microenvironment. In this study, we describe a droplet microfluidic system for analysis of Immunological synapse (IS) formaEon between dendriEc cells (DCs) and T cells for the laWer's acEvaEon . We co-­‐encapsulated DCs with T cells and observed heterogeneous cell interacEon. Individual non-­‐acEvated DCs interacted transiently with T cells, whereas anEgen-­‐loaded DCs formed both transient and stable contacts, where the duraEon of the contacts varied from cell to cell. AcEvaEon of T cells was indicated by increased intracellular calcium signaling. AddiEonally, we assessed the effecEveness of two different DC vaccines, one acEvated with tumor lysate and the other a hybrid DC-­‐tumor cell fusion. These vaccines were co-­‐encapsulated with T cells and mulEple myeloma (MM) cell line in droplets. Serial interacEon between DCs and T cells and T cells and MM cells resulted in MM cell death. To our knowledge, this is the first report of dynamic analysis of DC vaccines at single cell resoluEon in microfluidic pla[orm. This integrated droplet microarray can potenEally be used to monitor experimental cancer therapeuEcs, funcEonal phenotyping and heterogeneity of cellular response. INTRODUCTION It is postulated that tumor growth and progression is a virtue of opEmal tumor microenvironment. The immune system is said to have a paradoxical role in tumor microenvironment where it can either downregulate tumor growth by destroying cancer cells and inhibiEng their proliferaEon or promote tumor progression by promoEng growth of tumor cells in an immunocompetent host by establishing favorable condiEons within the tumor microenvironment. The combinaEon of these processes is described as cancer immunoediEng (1). DendriEc cells (DCs) are criEcal anEgen presenEng cells (APCs) that present tumor anEgens to tumor-­‐infiltraEng T lymphocytes. However, DC maturaEon and acEvaEon can be suppressed in the tumor microenvironment, prevenEng adequate anEgen presentaEon to T cells. Tumor-­‐specific DCs have been shown to interact with, and acEvate, T cells in vivo and in vitro (2). However, these T cells have no cytolyEc acEon on of tumor cells. This suggests that acEvaEon of adapEve immunity in tumor microenvironment may be heterogeneous or ineffecEve by itself, requiring a co-­‐sEmulatory signal to downregulate tumor growth. The development of DC based cancer vaccines are one of the most potent cancer vaccines in clinical development as they can be loaded ex vivo with tumor anEgens and injected into paEents to generate long-­‐term CD4+ and CD8+ T cell responses that can miEgate cancer. However, dynamic characterizaEon of their responses and interacEons with T cells and tumor cells is important to address prior to clinical applicaEon. We have developed a droplet microfluidics-­‐based pla[orm to chemically isolate individual cells and observe phenotypic changes subsequent to cell-­‐cell interacEon. METHOD Droplet Genera6on, Cell Co-­‐encapsula6on and cell velocity mapping In Microfluidic PlaJorm Fig. 1. Cell co-­‐encapsula6on in droplet microfluidic plaJorm. (A) SchemaEc of integrated three-­‐inlet droplet generaEon and microarray device. (B) GeneraEon of nanoliter droplets. (C) Droplets loaded in microarray for stable docking(D) Morphology of single DC and T cell in droplet. Inset: Magnified image of dendrite extension by DC. (E) Cellular exocytosis observed in droplet. Inset: Magnified image of vesicles secreted by DC at 4hrs. Scale bar: 20µm. (F) RepresentaEve mean velocity of T cells, DC and RPMI-­‐8226 cells in droplet. (G) Decrease in velocity as cells near each other and form conjugate. The onset of contact period is indicated by u. RPMI-­‐8226 cell died at 240min. Scale bar: 20µm. ACKNOWLEDGEMENTS This work was funded by NIH/NCI grant R21 [RM11-­‐014] awarded to T.K. The authors are grateful to Abhinav Gupta, Vinny Motwani, Sneha Verghese and Sai MynampaE at Northeastern University for their assistance in fabricaEon of microfluidic devices and data analysis. REFERENCES: Smyth MJ, Dunn GP, Schreiber RD. Adv Immunol. 2006;90:1-­‐50; 2. Engelhardt JJ, Boldajipour B, et al. Cancer Cell. 2012 ;21(3):402-­‐17. RESULTS Dynamic Profiling Of Dendri6c Cell, T Cell And Mul6ple Myeloma Tumor Cell Intera6ons Fig 2. Dynamic monitoring of interacEon between acEvated DC and T cells in microfluidic droplets. (A) DCs were pulsed with OVA-­‐FITC (100 µg/mL, 16hrs) and CCL21(25ng/mL, 2hrs) and co-­‐encapsulated with untreated T cells in droplets. OVA-­‐FITC expression on DC surface is indicated by arrowheads. T cells are labeled with CMTPX tracker (red), which is transferred to the DCs over Eme. A series of Eme-­‐lapse images of the same droplet is shown over a period of 1hr. Images were obtained every 5min. Scale bar: 20µm. (B) Analysis of the types of interacEon between DC and T cell: no interacEon over a period of 5hrs (-­‐), conEnuous interacEon due to conjugate formaEon disconEnuous interacEon defined by short periods of aWachment and and detachment. DCs were either acEvated by pre-­‐treatment with OVA-­‐FITC and CCL21 (Ag acEvated) or untreated (Non-­‐acEvated). (C) Cells undergoing disconEnuous interacEon were further categorized into transient (≤10 minutes of contact) and stable (≥ 10minutes) interacEon. (D) DistribuEon of contact Emes between DC and T cells (outliers are indicated). The data is represented as mean ± SEM of n=3 independent experiments. P<0.05 is indicated by *. Fig 3. InteracEon between T cells and Tumor cells in droplets. (A) Lysis and death of target cell in contact with T cell. Target cells (green) were labeled with Calcein AM. Scale bar: 50µm. The T cells were not labeled. (B) % of target cell death mediated by T cells (n=3, mean ± SEM). P<0.05 is indicated by *. (C) Comparison of Eme required by PMA/Ionomycin-­‐treated T cells to promote target cell death. A threshold of 200min was set for disEnguishing fast vs. slow kill. (D) Effect of presence/absence of IFN-­‐γ anEbody on rapid target death. Cell numbers (n) used for analysis in this representaEve experiment are indicated. (E) Number of contacts made between acEvated T cell-­‐target cell pairs in a representaEve experiment. N: 104, 98 and 53 for Control, PMA/Ionomycin-­‐treated and PMA/Ionomycin/IFN-­‐γ-­‐treated cells respecEvely. Fig 4. Co-­‐encapsulaEon of tumor-­‐lysate pulsed DC, T cells and tumor cells. The top panel represents microscopic images of various stages of interacEon between the immune and tumor cells. Movement of DC, T cells and Tumor cells are indicated by (a) Freely moEle DC and T cells move towards each other in droplets. (b) DC-­‐T conjugates are formed. (c) DC-­‐T conjugates dissociate and cells become moEle again. T cells and tumor cells establish contact. (d) T cells dissociate from tumor. (e) Tumor cells depict morphological changes, blebbing and membrane rupture. Right panel: Tumor cell death indicated by uptake of ethidium homodimer. BoWom Panel: Magnified images of the corresponding panels in (B). Scale bar: 20µm. CONCLUSION Our results indicate that dynamic immune-­‐oncological interacEons can be monitored in a high throughput manner in the droplet microfluidic pla[orm. In future studies, we intend to measure downstream effects including secretory profiling using our pla[orm.