The DOI matches its Crossref record; 108 of the 108 references it cites were found in a registry or an index.
Integrating Proteomics and Transcriptomics for Systematic Combinatorial Chimeric Antigen Receptor Therapy of AML
Open accessAbstract
Summary Chimeric antigen receptor (CAR) therapy targeting CD19 has yielded remarkable outcomes in patients with acute lymphoblastic leukemia. To identify potential CAR targets in acute myeloid leukemia (AML), we probed the AML surfaceome for over-expressed molecules with tolerable systemic expression. We integrated large transcriptomics and proteomics data sets from malignant and normal tissues, and developed an algorithm to identify potential targets expressed in leukemia stem cells, but not in normal CD34+CD38− hematopoietic cells, T cells or vital tissues. As these investigations did not uncover candidate targets with a profile as favorable as CD19, we developed a generalizable combinatorial targeting strategy fulfilling stringent efficacy and safety criteria. Our findings indicate that several target pairings hold great promise for CAR therapy of AML.
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Self-citationCAR T cells: Continuation in a revolution of immunotherapy
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Metadata
- Authors
- Perna, F., Berman, S. H., Soni, R. K., Mansilla-Soto, J., Eyquem, J., Hamieh, M., Hendrickson, R. C., Brennan, C. W., & Sadelain, M.
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2017-10
- Volume
- 32
- Issue
- 4
- Pages
- 506-519.e5
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W2761903029
- Cited by
- 346
- References
- 108
- FWCI
- 10.88
- Type
- journal article
- Language
- en
- Open access
- bronze
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- The paper
- Perna, F., Berman, S. H., Soni, R. K., Mansilla-Soto, J., Eyquem, J., Hamieh, M., Hendrickson, R. C., Brennan, C. W., & Sadelain, M. (2017). Integrating Proteomics and Transcriptomics for Systematic Combinatorial Chimeric Antigen Receptor Therapy of AML. Cancer Cell. https://doi.org/10.1016/j.ccell.2017.09.004
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
