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Piscopo, N.

Publications and source records attributed to Piscopo, N..

2 recordsLinked to original sources

CRISPR-mediated insertion of a chimeric antigen receptor produces nonviral T cell products capable of inducing solid tumor regression

BackgroundChimeric antigen receptor (CAR) T cells traditionally harbor viral vector-based sequences that encode the CAR transgene in the genome. These T cell products have yet to show consistent anti-tumor activity in patients with solid tumors. Further, viral vector manufacturing is resource intensive, suffers from batch-to-batch variability, and includes several animal components, adding regulatory and supply chain pressures. MethodsAnti-GD2 CAR T cells were generated using CRISPR/Cas9 within nine days using recombinant Cas9 protein and nucleic acids, without any viral vectors or animal components. The CAR was specifically targeted to the T Cell Receptor Alpha Constant gene (TRAC). T cell products were characterized at the level of the genome, transcriptome, proteome, and secretome using CHANGE-seq, scRNA-seq, spectral cytometry, and ELISA assays. Functionality was evaluated in vivo in an NSG xenograft neuroblastoma model. ResultsIn comparison to traditional retroviral CAR T cells, virus-free CRISPR CAR (VFC-CAR) T cells exhibit TRAC-targeted genomic integration of the CAR transgene, elevation of transcriptional and protein characteristics associated with a memory phenotype, and low tonic signaling prior to infusion arising in part from the the knockout of the TCR. Upon exposure to the GD2 target antigen, anti-GD2 VFC-CAR T cells exhibited specific cytotoxicity against GD2+ cells in vitro and induced solid tumor regression in vivo, with robust homing, persistence, and low exhaustion against a human neuroblastoma xenograft model. ConclusionsThis proof-of-principle study leveraging virus-free genome editing technology could enable flexible manufacturing of clinically relevant, high-quality CAR T cells to treat cancers, including solid tumors.

bioengineering↗

Label-free Method for Classification of T cell Activation

T cells have a range of cytotoxic and immune-modulating functions, depending on activation state and subtype. However, current methods to assess T cell function use exogenous labels that often require cell permeabilization, which is limiting for time-course studies of T cell activation and non-destructive quality control of immunotherapies. Label-free optical imaging is an attractive solution. Here, we use autofluorescence imaging of NAD(P)H and FAD, co-enzymes of metabolism, to quantify optical imaging endpoints in quiescent and activated T cells. Machine learning classification models were developed for label-free, non-destructive determination of T cell activation state. T cells were isolated from the peripheral blood of human donors, and a subset were activated with a tetrameric antibody against CD2/CD3/CD28 surface ligands. NAD(P)H and FAD autofluorescence intensity and lifetime of the T cells were imaged using a multiphoton fluorescence lifetime microscope. Significant differences in autofluorescence imaging end-points were observed between quiescent and activated T cells. Feature selection methods revealed that the contribution of the short NAD(P)H lifetime (1) is the most important feature for classification of activation state, across multiple donors and T cell subsets. Logistic regression models achieved 97-99% accuracy for classification of T cell activation from the autofluorescence imaging endpoints. Additionally, autofluorescence imaging revealed NAD(P)H and FAD autofluorescence differences between CD3+CD8+ and CD3+CD4+ T cells, and random forest models of the autofluorescence imaging endpoints achieved 97+% accuracy for four-group classification of quiescent and activated CD3+CD8+ and CD3+CD4+ T cells. Altogether these results indicate that autofluorescence imaging of NAD(P)H and FAD is a powerful method for label-free, non-destructive determination of T cell activation and subtype, which could have important applications for the treatment of cancer, autoimmune, infectious, and other diseases.

bioengineering↗