The DOI matches its Crossref record; 165 of the 165 references it cites were found in a registry or an index.
Immune escape and immunotherapy of acute myeloid leukemia
Open accessAbstract
In spite of the recent approval of new promising targeted therapies, the clinical outcome of patients with acute myeloid leukemia (AML) remains suboptimal, prompting the search for additional and synergistic therapeutic rationales. It is increasingly evident that the bone marrow immune environment of AML patients is profoundly altered, contributing to the severity of the disease but also providing several windows of opportunity to prompt or rewire a proficient antitumor immune surveillance. In this Review, we present current evidence on immune defects in AML, discuss the challenges with selective targeting of AML cells, and summarize the clinical results and immunologic insights from studies that are testing the latest immunotherapy approaches to specifically target AML cells (antibodies, cellular therapies) or more broadly reactivate antileukemia immunity (vaccines, checkpoint blockade). Given the complex interactions between AML cells and the many components of their environment, it is reasonable to surmise that the future of immunotherapy in AML lies in the rational combination of complementary immunotherapeutic strategies with chemotherapeutics or other oncogenic pathway inhibitors. Identifying reliable biomarkers of response to improve patient selection and avoid toxicities will be critical in this process.
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Metadata
- Authors
- Vago, L., & Gojo, I.
- Venue
- Journal of Clinical Investigation
- Published
- 2020-04-01
- Volume
- 130
- Issue
- 4
- Pages
- 1552-1564
- ISSN
- 0021-9738 (ISSN-L)
- 1558-8238
- OpenAlex
- W3014109498
- Cited by
- 341
- References
- 165
- FWCI
- 21.87
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Vago, L., & Gojo, I. (2020). Immune escape and immunotherapy of acute myeloid leukemia. Journal of Clinical Investigation. https://doi.org/10.1172/jci129204
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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