Background Adaptive CD19-targeted chimeric antigen receptor (CAR) T-cell transfer has become a promising treatment for leukemia. Although patient responses vary across different clinical trials, reliable methods to dissect and predict patient responses to novel therapies are currently lacking. Recently, the depiction of patient responses has been achieved using in silico computational models, with prediction application being limited. Methods We established a computational model of CAR T-cell therapy to recapitulate key cellular mechanisms and dynamics during treatment with responses of continuous remission (CR), non-response (NR), and CD19-positive (CD19 + ) and CD19-negative (CD19 − ) relapse. Real-time CAR T-cell and tumor burden data of 209 patients were collected from clinical studies and standardized with unified units in bone marrow. Parameter estimation was conducted using the stochastic approximation expectation maximization algorithm for nonlinear mixed-effect modeling. Results We revealed critical determinants related to patient responses at remission, resistance, and relapse. For CR, NR, and CD19 + relapse, the overall functionality of CAR T-cell led to various outcomes, whereas loss of the CD19 + antigen and the bystander killing effect of CAR T-cells may partly explain the progression of CD19 − relapse. Furthermore, we predicted patient responses by combining the peak and accumulated values of CAR T-cells or by inputting early-stage CAR T-cell dynamics. A clinical trial simulation using virtual patient cohorts generated based on real clinical patient datasets was conducted to further validate the prediction. Conclusions Our model dissected the mechanism behind distinct responses of leukemia to CAR T-cell therapy. This patient-based computational immuno-oncology model can predict late responses and may be informative in clinical treatment and management.
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A Computational Model of Cytokine Release Syndrome during CAR T‐Cell Therapy
Cytokine release syndrome (CRS) is a lethal adverse event in chimeric antigen receptor (CAR) T‐cell therapy, hindering this promising therapy for cancers, such as B‐cell acute lymphoblastic leukemia (B‐ALL). Clinical management of CRS requires a better understanding of its underlying mechanisms. In this study, a computational model of CRS during CAR T‐cell therapy is built to depict how the cellular interactions among CAR T‐cells, B‐ALL cells, and bystander monocytes, as well as the accompanying molecular interactions among various inflammatory cytokines, influence the severity of CRS. The model successfully defines the factors related to severe CRS and studies the effects of immunomodulatory therapy on CRS. The use of the model is also demonstrated as a precision medicine tool to optimize the treatment scheme, including personalized choice of CAR T‐cell products and control of switchable CAR T‐cell activity, for a more efficient and safer immunotherapy. This new computational oncology model can serve as a precision medicine tool to guide the clinical management of CRS during CAR T cell therapy.
more » « less- Award ID(s):
- 2103219
- NSF-PAR ID:
- 10377047
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Therapeutics
- Volume:
- 5
- Issue:
- 10
- ISSN:
- 2366-3987
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Background Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles.
Methods The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses.
Results Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires.
Conclusions Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences.
Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012. -
Developing the next generation of cellular therapies will depend on fast, versatile, and efficient cellular reprogramming. Novel biomaterials will play a central role in this process by providing scaffolding and bioactive signals that shape cell fate and function. Previously, our lab reported that dry macroporous alginate scaffolds mediate retroviral transduction of primary T cells with efficiencies that rival the gold-standard clinical spinoculation procedures, which involve centrifugation on Retronectin-coated plates. This scaffold transduction required the scaffolds to be both macroporous and dry. Transduction by dry, macroporous scaffolds, termed “Drydux transduction,” provides a fast and inexpensive method for transducing cells for cellular therapy, including for the production of CAR T cells. In this study, we investigate the mechanism of action by which Drydux transduction works through exploring the impact of pore size, stiffness, viral concentration, and absorption speed on transduction efficiency. We report that Drydux scaffolds with macropores ranging from 50–230 μm and with Young's moduli ranging from 25–620 kPa all effectively transduce primary T cells, suggesting that these parameters are not central to the mechanism of action, but also demonstrating that Drydux scaffolds can be tuned without losing functionality. Increasing viral concentrations led to significantly higher transduction efficiencies, demonstrating that increased cell–virus interaction is necessary for optimal transduction. Finally, we discovered that the rate with which the cell–virus solution is absorbed into the scaffold is closely correlated to viral transduction efficiency, with faster absorption producing significantly higher transduction. A computational model of liquid flow through porous media validates this finding by showing that increased fluid flow substantially increases collisions between virus particles and cells in a porous scaffold. Taken together, we conclude that the rate of liquid flow through the scaffolds, rather than pore size or stiffness, serves as a central regulator for efficient Drydux transduction.more » « less
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Abstract Cancer immunotherapy based on the engineering of chimeric antigen receptors (CAR) on T cells has emerged as one of the most promising new therapies for patients with B‐cell malignancies. Preclinical assessments of essential CAR T cell functions such as trafficking and cytotoxicity are critical for accelerating the development of highly effective therapeutic candidates. However, current tools for evaluating CAR‐T functions lack sufficient precision. Here, a micropatterned tumor array (MiTA) is described that enables detailed and dynamic characterization of CAR T cell trafficking toward tumor‐cell islands and subsequent killing of tumor cells. It is shown that CAR T cells often merge into large clusters that envelop and kill the tumor cells with high efficiency. Significant differences are also measured between CAR T cells from different donors and between various CAR T cell constructs. Overall, the assay allows for multifaceted, dynamic, high‐content evaluation of CAR T trafficking, clustering, and killing and could eventually become a useful tool for immune‐oncology research and preclinical assessments of cell‐based immunotherapies.
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Chimeric antigen receptor (CAR) T-cells targeting CD19 demonstrate remarkable efficacy in treating B-lineage acute lymphoblastic leukemia (BL-ALL), yet up to 39% of treated patients relapse with CD19(−) disease. We report that CD19(−) escape is associated with downregulation, but preservation, of targetable expression of CD20 and CD22. Accordingly, we reasoned that broadening the spectrum of CD19CAR T-cells to include both CD20 and CD22 would enable them to target CD19(−) escape BL-ALL while preserving their upfront efficacy. We created a CD19/20/22-targeting CAR T-cell by coexpressing individual CAR molecules on a single T-cell using one tricistronic transgene. CD19/20/22CAR T-cells killed CD19(−) blasts from patients who relapsed after CD19CAR T-cell therapy and CRISPR/Cas9 CD19 knockout primary BL-ALL both in vitro and in an animal model, while CD19CAR T-cells were ineffective. At the subcellular level, CD19/20/22CAR T-cells formed dense immune synapses with target cells that mediated effective cytolytic complex formation, were efficient serial killers in single-cell tracking studies, and were as efficacious as CD19CAR T-cells against primary CD19(+) disease. In conclusion, independent of CD19 expression, CD19/20/22CAR T-cells could be used as salvage or front-line CAR therapy for patients with recalcitrant disease.more » « less
