Engineering strategies to overcome the current roadblocks in CAR T cell therapy

Rafiq, Sarwish; Hackett, Christopher S.; Brentjens, Renier J.

doi:10.1038/s41571-019-0297-y

Cited by 1,019 publications

(978 citation statements)

References 247 publications

(298 reference statements)

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“…Targeting CD19, therefore, leads to B-cell aplasia, which is clinically manageable. Targeting linage antigens on solid tumors is not an option due to severe toxicities ( 2 , 20 ). The ideal target for CAR T-cell therapy should be ubiquitously expressed on all tumor cells and be completely absent from healthy tissue to avoid complications such as on-target/off-tumor toxicities, as described above.…”

Section: Car T-cell Therapy In Hematological and Solid Cancersmentioning

confidence: 99%

CAR T-Cell Cancer Therapy Targeting Surface Cancer/Testis Antigens

Jakobsen

Gjerstorff

2020

Front. Immunol.

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Section: Car T-cell Therapy In Hematological and Solid Cancersmentioning

confidence: 99%

CAR T-Cell Cancer Therapy Targeting Surface Cancer/Testis Antigens

Jakobsen

Gjerstorff

2020

Front. Immunol.

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“…Antibodies are also used to deliver cytotoxic payloads into cancer cells such as with T-DM1 [36], and cross-linking cancer cells to cytotoxic T cells with blinatumomab [37]. Furthermore, antibodies are used as a cancer cell-targeting component in chimeric antigen receptor T cell therapy, as seen with tisagenlecleucel and axicabtagene ciloleucel [38]. Additionally, it is well known that the antibody epitope and binding characteristics critically influence efficacy for all these various modes of action [39,40].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning-Guided Prediction of Antigen-Reactive In Silico Clonotypes Based on Changes in Clonal Abundance through Bio-Panning

Yoo

Lee

Jung³

et al. 2020

Biomolecules

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c-Met is a promising target in cancer therapy for its intrinsic oncogenic properties. However, there are currently no c-Met-specific inhibitors available in the clinic. Antibodies blocking the interaction with its only known ligand, hepatocyte growth factor, and/or inducing receptor internalization have been clinically tested. To explore other therapeutic antibody mechanisms like Fc-mediated effector function, bispecific T cell engagement, and chimeric antigen T cell receptors, a diverse panel of antibodies is essential. We prepared a chicken immune scFv library, performed four rounds of bio-panning, obtained 641 clones using a high-throughput clonal retrieval system (TrueRepertoireTM, TR), and found 149 antigen-reactive scFv clones. We also prepared phagemid DNA before the start of bio-panning (round 0) and, after each round of bio-panning (round 1–4), performed next-generation sequencing of these five sets of phagemid DNA, and identified 860,207 HCDR3 clonotypes and 443,292 LCDR3 clonotypes along with their clonal abundance data. We then established a TR data set consisting of antigen reactivity for scFv clones found in TR analysis and the clonal abundance of their HCDR3 and LCDR3 clonotypes in five sets of phagemid DNA. Using the TR data set, a random forest machine learning algorithm was trained to predict the binding properties of in silico HCDR3 and LCDR3 clonotypes. Subsequently, we synthesized 40 HCDR3 and 40 LCDR3 clonotypes predicted to be antigen reactive (AR) and constructed a phage-displayed scFv library called the AR library. In parallel, we also prepared an antigen non-reactive (NR) library using 10 HCDR3 and 10 LCDR3 clonotypes predicted to be NR. After a single round of bio-panning, we screened 96 randomly-selected phage clones from the AR library and found out 14 AR scFv clones consisting of 5 HCDR3 and 11 LCDR3 AR clonotypes. We also screened 96 randomly-selected phage clones from the NR library, but did not identify any AR clones. In summary, machine learning algorithms can provide a method for identifying AR antibodies, which allows for the characterization of diverse antibody libraries inaccessible by traditional methods.

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“…CAR constructs are made up of four main components: the single-chain variable fragment (scFv), the hinge, the transmembrane domain (TM), and the intracellular signaling domains. Each of the four components has been studied and optimized in T cells to maximize tumor detection, T cell activation, and tumor elimination [7].…”

Section: Background Of Chimeric Antigen Receptorsmentioning

confidence: 99%

You Have Got a Fast CAR: Chimeric Antigen Receptor NK Cells in Cancer Therapy

Pfefferle

Huntington

2020

Cancers

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The clinical success stories of chimeric antigen receptor (CAR)-T cell therapy against B-cell malignancies have contributed to immunotherapy being at the forefront of cancer therapy today. Their success has fueled interest in improving CAR constructs, identifying additional antigens to target, and clinically evaluating them across a wide range of malignancies. However, along with the exciting potential of CAR-T therapy comes the real possibility of serious side effects. While the FDA has approved commercialized CAR-T cell therapy, challenges associated with manufacturing, costs, and related toxicities have resulted in increased attention being paid to implementing CAR technology in innate cytotoxic natural killer (NK) cells. Here, we review the current landscape of the CAR-NK field, from successful clinical implementation to outstanding challenges which remain to be addressed to deliver the full potential of this therapy to more patients.

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Engineering strategies to overcome the current roadblocks in CAR T cell therapy

Cited by 1,019 publications

References 247 publications

CAR T-Cell Cancer Therapy Targeting Surface Cancer/Testis Antigens

CAR T-Cell Cancer Therapy Targeting Surface Cancer/Testis Antigens

Machine Learning-Guided Prediction of Antigen-Reactive In Silico Clonotypes Based on Changes in Clonal Abundance through Bio-Panning

You Have Got a Fast CAR: Chimeric Antigen Receptor NK Cells in Cancer Therapy

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