CTLA-4: a moving target in immunotherapy
Open accessAbstract
CD28 and CTLA-4 are members of a family of immunoglobulin-related receptors that are responsible for various aspects of T-cell immune regulation. The family includes CD28, CTLA-4, and ICOS as well as other proteins, including PD-1, BTLA, and TIGIT. These receptors have both stimulatory (CD28, ICOS) and inhibitory roles (CTLA-4, PD-1, BTLA, and TIGIT) in T-cell function. Increasingly, these pathways are targeted as part of immune modulatory strategies to treat cancers, referred to generically as immune checkpoint blockade, and conversely to treat autoimmunity and CTLA-4 deficiency. Here, we focus on the biology of the CD28/CTLA-4 pathway as a framework for understanding the impacts of therapeutic manipulation of this pathway.
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Cancer immunotherapies based on antibodies or cells carry intrinsic risks of activating bystander immune responses beyond their intended anti-tumor action.
“Antibody or cell-based immunotherapeutics for cancer carry inherent risks of bystander immune activation, in addition to the effects of treating the intended tumor target [1–5].”
From Immune reconstitution and clinical recovery following anti-CD28 antibody (TGN1412)-induced cytokine storm (2021) · cites this paper as [2]
In “Targeting the CTLA-4 pathway: lessons from the clinic” (page not provided), the paper reports autoimmune effects and immune-related adverse events alongside tumor control with anti-CTLA-4 antibodies. It does not establish the same risk for cell-based immunotherapies or for antibody-based cancer immunotherapies generally. (LLM, conf=0.84)
Experimental — accuracy not yet measuredCTLA-4 blockade did not produce substantial autoimmunity in preclinical models, unlike complete absence of CTLA-4.
“CTLA-4 blockade did not demonstrate substantial autoimmunity (Leach et al., 1996; Rowshanravan et al., 2018).”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Rowshanravan et al., 2018
Immune checkpoint blockade in preclinical models did not cause overwhelming autoimmune pathology.
“ICB treatment in pre-clinical models did not lead to overwhelming autoimmune pathology”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Rowshanravan et al., 2018
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- Authors
- Rowshanravan, B., Halliday, N., & Sansom, D. M.
- Affiliations
- The Royal Free Hospital (GB)
- Venue
- Blood
- Publisher
- American Society of Hematology
- Published
- 2018-01-04
- Volume
- 131
- Issue
- 1
- Pages
- 58-67
- ISSN
- 0006-4971 (ISSN-L)
- 1528-0020
- PMC
- PMC6317697
- OpenAlex
- W2767343890
- Cited by
- 1,233
- References
- 139
- Citations by year
- 2026: 132 · 2025: 169 · 2024: 224 · 2023: 186 · 2022: 180 · 2021: 157 · 2020: 125 · 2019: 46 · 2018: 13
- FWCI
- 5.28
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Blood (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust
- Biotechnology and Biological Sciences Research Council (BB/M009203/1)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- CTLA-4, CD28, immune checkpoint blockade, T cell regulation, immunotherapy, cancer immunotherapy, autoimmunity, ICOS, PD-1, BTLA, TIGIT, inhibitory receptors
- MeSH terms
- Animals, Antibodies, Monoclonal, Humans, Immunotherapy, Neoplasms, CTLA-4 Antigen
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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