CARTAR: a comprehensive web tool for identifying potential targets in chimeric antigen receptor therapies using TCGA and GTEx data
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Oxford Academic
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Chimeric antigen receptor (CAR) therapy has emerged as a ground-breaking advancement in cancer treatment, harnessing the power of engineered human immune cells to target and eliminate cancer cells. The escalating interest and investment in CAR therapy in recent years emphasize its profound significance in clinical research, positioning it as a rapidly expanding frontier in the field of personalized cancer therapies. A crucial step in CAR therapy design is choosing the right target as it determines the therapy’s effectiveness, safety and specificity against cancer cells, while sparing healthy tissues. Herein, we propose a suite of tools for the identification and analysis of potential CAR targets leveraging expression data from The Cancer Genome Atlas and Genotype-Tissue Expression Project, which are implemented in CARTAR website. These tools focus on pinpointing tumor-associated antigens, ensuring target selectivity and assessing specificity to avoid off-tumor toxicities and can be used to rationally designing dual CARs. In addition, candidate target expression can be explored in cancer cell lines using the expression data for the Cancer Cell Line Encyclopedia. To our best knowledge, CARTAR is the first website dedicated to the systematic search of suitable candidate targets for CAR therapy. CARTAR is publicly accessible at https://gmxenomica.github.io/CARTAR/
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Briefings in Bioinformatics, 2024, 25(4), bbae326
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https://doi.org/10.1093/bib/bbae326Sponsors
This work was supported by grants from Xunta de Galicia (ED431G 2019/02; ED481A 2022)
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Atribución 4.0 Internacional
© The Author(s) 2024. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited
© The Author(s) 2024. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited








