Journal
SEMINARS IN CANCER BIOLOGY
Volume 86, Issue -, Pages 137-150Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.semcancer.2022.03.014
Keywords
PD-1/PD-L1; CTLA-4; ICOS; BTLA; LAG-3; TIGIT; TIM-3; VISTA; Immune checkpoint inhibitors; Immune checkpoint stimulators; Signaling
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Immune checkpoint proteins (ICPs) are currently a promising area of immune-oncology research, with ongoing clinical trials to develop immunotherapeutic agents. However, there are challenges such as adverse side effects and lack of response in certain populations. Understanding the expression pattern and cellular mechanism of ICPs is crucial for the safe and effective development of targeted immunotherapy.
Immune checkpoint proteins (ICP) are currently one of the most novel and promising areas of immune-oncology research. This novel way of targeting tumor cells has shown favorable success over the past few years with some FDA approvals such as Ipilimumab, Nivolumab, Pembrolizumab etc. Currently, more than 3000 clinical trials of immunotherapeutic agents are ongoing with majority being ICPs. However, as the number of trials increase so do the challenges. Some challenges such as adverse side effects, non-specific binding on healthy tissues and absence of response in some subset populations are critical obstacles. For a safe and effective further therapeutic development of molecules targeting ICPs, understanding their mechanism at molecular level is crucial. Since ICPs are mostly membrane bound receptors, a number of downstream signaling pathways divaricate following ligand-receptor binding. Most ICPs are expressed on more than one type of immune cell populations. Further, the expression varies within a cell type. This naturally varied expression pattern adds to the difficulty of targeting specific effector immune cell types against cancer. Hence, understanding the expression pattern and cellular mechanism helps lay out the possible effect of any immunotherapy. In this review, we discuss the signaling mechanism, expression pattern among various immune cells and molecular interactions derived using interaction database analysis (BioGRID).
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