AIMC Topic: Receptors, Chimeric Antigen

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Decoding CAR T cell phenotype using combinatorial signaling motif libraries and machine learning.

Science (New York, N.Y.)
Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2300 synthetic costimulatory domains, built from combinations ...

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Computers in biology and medicine
Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of ...

CD147-specific chimeric antigen receptor T cells effectively inhibit T cell acute lymphoblastic leukemia.

Cancer letters
T cell acute lymphoblastic leukemia (T-ALL) is invasive and heterogeneous, and existing therapies are sometimes unsuccessful. Chimeric antigen receptor (CAR) T cell therapy is a breakthrough tumor treatment method, particularly for B cell acute lymph...

Deep-learning-based three-dimensional label-free tracking and analysis of immunological synapses of CAR-T cells.

eLife
The immunological synapse (IS) is a cell-cell junction between a T cell and a professional antigen-presenting cell. Since the IS formation is a critical step for the initiation of an antigen-specific immune response, various live-cell imaging techniq...

Advancing CAR T-cell Therapies with Artificial Intelligence: Opportunities and Challenges.

Blood cancer discovery
Artificial intelligence could enhance chimeric antigen receptor T-cell therapy outcomes through optimization of all steps, from target identification, vector design, and manufacturing to personalized data-driven clinical decisions. In this report, we...