The DOI matches its Crossref record; 127 of the 127 references it cites were found in a registry or an index.
Resistance to Checkpoint Inhibition in Cancer Immunotherapy
Open accessAbstract
The interaction of the host immune system with tumor cells in the tissue microenvironment is essential in understanding tumor immunity and development of successful cancer immunotherapy. The presence of lymphocytes in tumors is highly correlated with an improved outcome. T cells have a set of cell surface receptors termed immune checkpoints that when activated suppress T cell function. Upregulation of immune checkpoint receptors such as programmed cell death 1 (PD-1) and cytotoxic T lymphocyte associated protein 4 (CTLA-4) occurs during T cell activation in an effort to prevent damage from an excessive immune response. Immune checkpoint inhibitors allow the adaptive immune system to respond to tumors more effectively. There has been clinical success in different types of cancer blocking immune checkpoint receptors such as PD-1 and CTLA. However, relapse has occurred. The innate and acquired/therapy induced resistance to treatment has been encountered. Aberrant cellular signal transduction is a major contributing factor to resistance to immunotherapy. Combination therapies with other co-inhibitory immune checkpoints such as TIM-3, LAG3 and VISTA are currently being tested to overcome resistance to cancer immunotherapy. Expression of TIM-3 has been associated with resistance to PD-1 blockade and combined blockade of TIM-3 and PD-1 has demonstrated improved responses in preclinical models. LAG3 blockade has the potential to increase the responsiveness of cytotoxic T-cells to tumors. Furthermore, tumors that were found to express VISTA had an increased rate of growth due to the T cell suppression. The growing understanding of the inhibitory immune checkpoints' ligand biology, signaling mechanisms, and T-cell suppression in the tumor microenvironment continues to fuel preclinical and clinical advancements in design, testing, and approval of agents that block checkpoint molecules. Our review seeks to bridge fundamental regulatory mechanisms across inhibitory immune checkpoint receptors that are of great importance in resistance to cancer immunotherapy. We will summarize the biology of different checkpoint molecules, highlight the effect of individual checkpoint inhibition as anti-tumor therapies, and outline the literatures that explore mechanisms of resistance to individual checkpoint inhibition pathways.
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Cites
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Cited by
PD-1 and PD-L1: architects of immune symphony and immunotherapy breakthroughs in cancer treatment
Parvez, A., Choudhary, F., Mudgal, P., Khan, R., Qureshi, K. A., Farooqi, H., & Aspatwar, A. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1296341 · Cited by 216
Metropulos, A. E., Munshi, H. G., & Principe, D. R. (2022) · eBioMedicine · doi:10.1016/j.ebiom.2022.104380 · Cited by 81
Recent updates on innovative approaches to overcome drug resistance for better outcomes in cancer
Sharma, M., Bakshi, A. K., Mittapelly, N., Gautam, S., Marwaha, D., Rai, N., Singh, N., Tiwari, P., Agarwal, N., Kumar, A., et al. (2022) · Journal of Controlled Release · doi:10.1016/j.jconrel.2022.04.007 · Cited by 84
DeNardo, D. G., Galkin, A., Dupont, J., Zhou, L., & Bendell, J. (2021) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2021-003005 · Cited by 53
Revisiting mechanisms of resistance to immunotherapies in metastatic clear-cell renal-cell carcinoma
Chatwal, M. S., Chahoud, J., & Spiess, P. E. (2023) · Cancer Drug Resistance · doi:10.20517/cdr.2023.09 · Cited by 12
Metadata
- Authors
- Barrueto, L., Caminero, F., Cash, L., Makris, C., Lamichhane, P., & Deshmukh, R. R.
- Venue
- Translational Oncology
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 13
- Issue
- 3
- Pages
- 100738
- ISSN
- 1936-5233 (ISSN-L)
- OpenAlex
- W3008389148
- Cited by
- 281
- References
- 127
- FWCI
- 13.95
- Type
- journal article
- Language
- en
- Open access
- gold
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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.