@article{labelle_zhang_hunsucker_armistead_allbritton_2022, title={Microraft arrays for serial-killer CD19 chimeric antigen receptor T cells and single cell isolation}, ISSN={["1552-4930"]}, DOI={10.1002/cyto.a.24678}, abstractNote={Chimeric antigen receptor T (CAR‐T) cell immunotherapies have seen success in treating hematological malignancies in recent years; however, the results can be highly variable. Single cell heterogeneity plays a key role in the variable efficacy of CAR‐T cell treatments yet is largely unexplored. A major challenge is to understand the killing behavior and phenotype of individual CAR‐T cells, which are able to serially kill targets. Thus, a platform capable of measuring time‐dependent CAR‐T cell mediated killing and then isolating single cells for downstream assays would be invaluable in characterizing CAR‐T cells. An automated microraft array platform was designed to track CD19 CAR‐T cell killing of CD19+ target cells and CAR‐T cell motility over time followed by CAR‐T cell collection based on killing behavior. The platform demonstrated automated CAR‐T cell counting with up to 98% specificity and 96% sensitivity, and single cells were isolated with 89% efficiency. On average, 2.3% of single CAR‐T cells were shown to participate in serial‐killing of target cells, killing a maximum of three target cells in a 6 h period. The cytotoxicity and motility of >7000 individual CAR‐T cells was tracked across four microraft arrays. The automated microraft array platform measured temporal cell‐mediated cytotoxicity, CAR‐T cell motility, CAR‐T cell death, and CAR‐T cell to target cell distances, followed by the capability to sort any desired CAR‐T cell. The pipeline has the potential to further our understanding of T cell‐based cancer immunotherapies and improve cell‐therapy products for better patient outcomes.}, journal={CYTOMETRY PART A}, author={LaBelle, Cody A. and Zhang, Raymond J. and Hunsucker, Sally A. and Armistead, Paul M. and Allbritton, Nancy L.}, year={2022}, month={Aug} }
 @article{labelle_zhang_armistead_allbritton_2020, title={Assay and Isolation of Single Proliferating CD4+Lymphocytes Using an Automated Microraft Array Platform}, volume={67}, ISSN={["1558-2531"]}, DOI={10.1109/TBME.2019.2956081}, abstractNote={Objective: While T lymphocytes have been employed as a cancer immunotherapy, the development of effective and specific T-cell-based therapeutics remains challenging. A key obstacle is the difficulty in identifying T cells reactive to cancer-associated antigens. The objective of this research was to develop a versatile platform for single cell analysis and isolation that can be applied in immunology research and clinical therapy development. Methods: An automated microscopy and cell sorting system was developed to track the proliferative behavior of single-cell human primary CD4+ lymphocytes in response to stimulation using allogeneic lymphoblastoid feeder cells. Results: The system identified single human T lymphocytes with a sensitivity of 98% and specificity of 99% and possessed a cell collection efficiency of 86%. Time-lapse imaging simultaneously tracked 4,534 alloreactive T cells on a single array; 19% of the arrayed cells formed colonies of ≥2 cells. From the array, 130 clonal colonies were isolated and 7 grew to colony sizes of >10,000 cells, consistent with the known proliferative capacity of T cells in vitro and their tendency to become exhausted with prolonged stimulation. The isolated colonies underwent ELISA assay to detect interferon-γ secretion and Sanger sequencing to determine T cell receptor β sequences with a 100% success rate. Conclusion: The platform is capable of both identification and isolation of proliferative T cells in an automated manner. Significance: This novel technology enables the identification of TCR sequences based on T cell proliferation which is expected to speed the development of future cancer immunotherapies.}, number={8}, journal={IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING}, author={LaBelle, Cody A. and Zhang, Raymond J. and Armistead, Paul M. and Allbritton, Nancy L.}, year={2020}, pages={2166–2175} }
 @misc{labelle_massaro_cortes-llanos_sims_allbritton_2020, title={Image-Based Live Cell Sorting}, volume={39}, ISSN={["1879-3096"]}, DOI={10.1016/j.tibtech.2020.10.006}, abstractNote={Technologies capable of cell separation based on cell images provide powerful tools enabling cell selection criteria that rely on spatially or temporally varying properties. Image-based cell sorting (IBCS) systems utilize microfluidic or microarray platforms, each having unique characteristics and applications. The advent of IBCS marks a new paradigm in which cell phenotype and behavior can be explored with high resolution and tied to cellular physiological and omics data, providing a deeper understanding of single-cell physiology and the creation of cell lines with unique properties. Cell sorting guided by high-content image information has far-reaching implications in biomedical research, clinical medicine, and pharmaceutical development.}, number={6}, journal={TRENDS IN BIOTECHNOLOGY}, author={LaBelle, Cody A. and Massaro, Angelo and Cortes-Llanos, Belen and Sims, Christopher E. and Allbritton, Nancy L.}, year={2020}, month={Jun}, pages={613–623} }