Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence
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Summary
The literature about specific combination partners for ICI is summarized and the applicability of artificial intelligence to predict ICI therapy responses is summarized to help select patients who will benefit most from ICI.
- Type
- review
- Published
- 2020-04-01
- Cited by
- 50
- References
- 205
- Access
- Open access
- OpenAlex
- https://openalex.org/W3016825425
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:216108495
Keywords
Medicine, Chimeric antigen receptor, Immunotherapy, Immune checkpoint, Immune system
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Cited by
- Combining Immune Checkpoint Blockade and Tumor-Specific Vaccine for Patients With Incurable Human Papillomavirus 16–Related Cancer: A Phase 2 Clinical Trial
- CRISPR/Cas9-mediated PD-1 disruption enhances human mesothelin-targeted CAR T cell effector functions
- VEGF-A drives TOX-dependent T cell exhaustion in anti–PD-1–resistant microsatellite stable colorectal cancers
- Capturing Hyperprogressive Disease with Immune-Checkpoint Inhibitors Using RECIST 1.1 Criteria
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- Construction of a prognostic immune signature for lower grade glioma that can be recognized by MRI radiomics features to predict survival in LGG patients
- Safety and Efficacy of Personalized Cancer Vaccines in Combination With Immune Checkpoint Inhibitors in Cancer Treatment
- Evidence for Non-Cancer-Specific T Cell Exhaustion in the Tcl1 Mouse Model for Chronic Lymphocytic Leukemia
- Interplay between Neutrophils, NETs and T-Cells in SARS-CoV-2 Infection—A Missing Piece of the Puzzle in the COVID-19 Pathogenesis?
- “Built‐in” PD‐1 blocker to rescue NK‐92 activity from PD‐L1–mediated tumor escape mechanisms
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- Expression, prognosis value, and immune infiltration of lncRNA ASB16-AS1 identified by pan-cancer analysis
- The Past, Present, and Future of Clinically Applied Chimeric Antigen Receptor-T-Cell Therapy
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