283666 Single-Cell Characterization of CD19-Specific CAR+ T Cells for Immunotherapy

Wednesday, October 31, 2012
Hall B (Convention Center )
Ivan Liadi1, Jason Roszik2, Amin Merouane3, Gabrielle Romain1, Badri Roysam3, Laurence Cooper2 and Navin Varadarajan4, (1)Dept. of Chemical & Biomolecular Engineering, The University of Houston, Houston, TX, (2)Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, (3)Dept. of Electrical and Computer Engineering, The University of Houston, Houston, TX, (4)Chemical and Biomolecular Engineering, The University of Houston, Houston, TX

In the last decade cancer immunotherapy using adoptive cell therapy (ACT) has emerged as a highly effective treatment option for diverse human cancers. In particular, the use of chimeric antigen receptor (CAR) T cells rendered specific for CD19 have demonstrated significant anti-tumor effects in patients with CD19+ chronic lymphocytic leukemia (CLL) that were considered untreatable, including the use of stem-cell transplantation. In spite of the clinical promise of ACT in achieving complete responses, their efficacy remains unpredictable and new approaches are needed to address a priori define the therapeutic potential of T-cell based therapies. In our current work, we have characterized the functionality of CD19-specific CAR+ T cells using a novel methodology that determines the cytotoxic ability and cytokine secretion capability of these cells at the single-cell level. Using our assay, we have studied the interaction of CD19-specific CAR+ T cells (CART19) with CD19-expressing EL4 target cells (EL4-CD19+) and NALM-6 tumor cells by encapsulating them in arrays of nanowells (~100k wells/array). For each single CAR+ T-cell the ability to engage and kill multiple target cells as well as the ability to secrete cytokines upon target conjugation has been scored. These composite functional profiles at the single-cell resolution are being used to determine the in vitro potency of CAR+ T cells and in combination with clinical data will help design the next generation of clinical trials.

Extended Abstract: File Not Uploaded