Simulating the Evolution of Signaling Signatures During CART-Cell and Tumor Cell Interactions. Annu Int Conf IEEE Eng Med Biol Soc 2023 Jul;2023:1-5
Date
12/12/2023Pubmed ID
38083755DOI
10.1109/EMBC40787.2023.10340076Scopus ID
2-s2.0-85179638579 (requires institutional sign-in at Scopus site)Abstract
Immunotherapies have been proven to have significant therapeutic efficacy in the treatment of cancer. The last decade has seen adoptive cell therapies, such as chimeric antigen receptor T-cell (CART-cell) therapy, gain FDA approval against specific cancers. Additionally, there are numerous clinical trials ongoing investigating additional designs and targets. Nevertheless, despite the excitement and promising potential of CART-cell therapy, response rates to therapy vary greatly between studies, patients, and cancers. There remains an unmet need to develop computational frameworks that more accurately predict CART-cell function and clinical efficacy. Here we present a coarse-grained model simulated with logical rules that demonstrates the evolution of signaling signatures following the interaction between CART-cells and tumor cells and allows for in silico based prediction of CART-cell functionality prior to experimentation.Clinical Relevance- Analysis of CART-cell signaling signatures can inform future CAR receptor design and combination therapy approaches aimed at improving therapy response.
Author List
Shah V, Womack J, Zamora AE, Terhune SS, Dash RKAuthors
Ranjan K. Dash PhD Professor in the Biomedical Engineering department at Medical College of WisconsinAnthony E. Zamora PhD Assistant Professor in the Medicine department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
Cell CommunicationHumans
Immunotherapy, Adoptive
Neoplasms
Signal Transduction
T-Lymphocytes
