The DOI matches its Crossref record; 116 of the 116 references it cites were found in a registry or an index.
LAG-3: from molecular functions to clinical applications
Open accessAbstract
To prevent the destruction of tissues owing to excessive and/or inappropriate immune responses, immune cells are under strict check by various regulatory mechanisms at multiple points. Inhibitory coreceptors, including programmed cell death 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA-4), serve as critical checkpoints in restricting immune responses against self-tissues and tumor cells. Immune checkpoint inhibitors that block PD-1 and CTLA-4 pathways significantly improved the outcomes of patients with diverse cancer types and have revolutionized cancer treatment. However, response rates to such therapies are rather limited, and immune-related adverse events are also observed in a substantial patient population, leading to the urgent need for novel therapeutics with higher efficacy and lower toxicity. In addition to PD-1 and CTLA-4, a variety of stimulatory and inhibitory coreceptors are involved in the regulation of T cell activation. Such coreceptors are listed as potential drug targets, and the competition to develop novel immunotherapies targeting these coreceptors has been very fierce. Among such coreceptors, lymphocyte activation gene-3 (LAG-3) is expected as the foremost target next to PD-1 in the development of cancer therapy, and multiple clinical trials testing the efficacy of LAG-3-targeted therapy are underway. LAG-3 is a type I transmembrane protein with structural similarities to CD4. Accumulating evidence indicates that LAG-3 is an inhibitory coreceptor and plays pivotal roles in autoimmunity, tumor immunity, and anti-infection immunity. In this review, we summarize the current understanding of LAG-3, ranging from its discovery to clinical application.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Cancer immunotherapy using checkpoint blockade
Ribas, A., & Wolchok, J. D. (2018) · Science · doi:10.1126/science.aar4060 · Cited by 6,791
Immune-Related Adverse Events Associated with Immune Checkpoint Blockade
Postow, M. A., Sidlow, R., & Hellmann, M. D. (2018) · New England Journal of Medicine · doi:10.1056/nejmra1703481 · Cited by 4,849
Tivol, E. A., Borriello, F., Schweitzer, A. N., Lynch, W. P., Bluestone, J. A., & Sharpe, A. H. (1995) · Immunity · doi:10.1016/1074-7613(95)90125-6 · Cited by 2,914
Lymphoproliferative Disorders with Early Lethality in Mice Deficient in Ctla-4
Waterhouse, P., Penninger, J. M., Timms, E., Wakeham, A., Shahinian, A., Lee, K. P., Thompson, C. B., Griesser, H., & Mak, T. W. (1995) · Science · doi:10.1126/science.270.5238.985 · Cited by 2,766
Nishimura, H., Nose, M., Hiai, H., Minato, N., & Honjo, T. (1999) · Immunity · doi:10.1016/s1074-7613(00)80089-8 · Cited by 2,749
Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy
Topalian, S. L., Taube, J. M., Anders, R. A., & Pardoll, D. M. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.36 · Cited by 2,733
Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance
Martins, F., Sofiya, L., Sykiotis, G. P., Lamine, F., Maillard, M., Fraga, M., Shabafrouz, K., Ribi, C., Cairoli, A., Guex-Crosier, Y., et al. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0218-0 · Cited by 2,314
Regulation and Function of the PD-L1 Checkpoint
Sun, C., Mezzadra, R., & Schumacher, T. N. (2018) · Immunity · doi:10.1016/j.immuni.2018.03.014 · Cited by 2,193
Blackburn, S. D., Shin, H., Haining, W. N., Zou, T., Workman, C. J., Polley, A., Betts, M. R., Freeman, G. J., Vignali, D. A. A., & Wherry, E. J. (2009) · Nature Immunology · doi:10.1038/ni.1679 · Cited by 2,062
Towards a systems understanding of MHC class I and MHC class II antigen presentation
Neefjes, J., Jongsma, M. L. M., Paul, P., & Bakke, O. (2011) · Nature Reviews Immunology · doi:10.1038/nri3084 · Cited by 2,044
Cited by
Immune checkpoint therapy—current perspectives and future directions
Sharma, P., Goswami, S., Raychaudhuri, D., Siddiqui, B. A., Singh, P., Nagarajan, A., Liu, J., Subudhi, S. K., Poon, C., Gant, K. L., et al. (2023) · Cell · doi:10.1016/j.cell.2023.03.006 · Cited by 1,206
Baessler, A., & Vignali, D. A. A. (2024) · Annual Review of Immunology · doi:10.1146/annurev-immunol-090222-110914 · Cited by 420
Huo, J.-L., Wang, Y.-T., Fu, W.-J., Lu, N., & Liu, Z.-S. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.956090 · Cited by 176
Current Progress and Future Perspectives of Immune Checkpoint in Cancer and Infectious Diseases
Cai, X., Zhan, H., Ye, Y., Yang, J., Zhang, M., Li, J., & Zhuang, Y. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.785153 · Cited by 66
The role of immune checkpoints in antitumor response: a potential antitumor immunotherapy
Mejía-Guarnizo, L. V., Monroy-Camacho, P. S., Turizo-Smith, A. D., & Rodríguez-García, J. A. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1298571 · Cited by 48
Metadata
- Authors
- Maruhashi, T., Sugiura, D., Okazaki, I.-M., & Okazaki, T.
- Venue
- Journal for ImmunoTherapy of Cancer
- Publisher
- BMJ
- Published
- 2020-09
- Volume
- 8
- Issue
- 2
- Pages
- e001014
- ISSN
- 2051-1426 (ISSN-L)
- OpenAlex
- W3085860981
- Cited by
- 459
- References
- 116
- FWCI
- 20.05
- Type
- journal article
- Language
- en
- Open access
- gold
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: LAG-3: from molecular functions to clinical applications. https://app.cochat.ai/papers/10.1136/jitc-2020-001014
- The paper
- Maruhashi, T., Sugiura, D., Okazaki, I.-M., & Okazaki, T. (2020). LAG-3: from molecular functions to clinical applications. Journal for ImmunoTherapy of Cancer. https://doi.org/10.1136/jitc-2020-001014
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
