Cutaneous adverse effects associated with LAG-3 inhibitor use in cancer treatment: A systematic review.
Hira GhaniSamavia KhanMarielle JamgochianBeth RichardsErica DeCeccoRebecca FliorentNithisha CheendallaKhalil KhatriBabar RaoPublished in: Skin health and disease (2023)
Immunotherapy has become a mainstay of treatment for many cancers. Multiple immune checkpoint inhibitors have been used to treat malignancies, including anti-programed death-1 (PD1) and anti-cytotoxic T-lymphocyte-associated protein (anti-CTLA4). However, a significant percentage of patients develop resistance to these immunotherapy drugs. Therefore, novel strategies were developed to target other aspects of the immune response. Lymphocyte activation gene-3 (LAG-3) is a cell-surface molecule found on natural killer cells and activated T-cells which negatively regulates T-cell proliferation and function. LAG-3 inhibitors interact with LAG-3 ligands on the surface of T-cells to block T-regulatory (Treg) cell activity, suppress cytokine secretion and restore dysfunctional effector T-cells which subsequently attack and destroy cancer cells. This review reports the dermatologic side effects associated with LAG-3 inhibitors used in the treatment of melanomas. Using PRISMA 2022 guidelines, a comprehensive literature review of PubMed, Google Scholar, Embase, Cochrane, and Web of Science databases was conducted. Three studies were identified that demonstrated that the use of LAG-3 inhibitors, whether as a single agent or in combination with other immune checkpoint inhibitors, resulted in stomatitis, pruritus, rash, dry skin, erythema, and vitiligo. Further research is warranted to assess the cutaneous adverse events observed with LAG-3 inhibitors in treating melanoma and to identify populations most vulnerable to such side effects.
Keyphrases
- immune response
- cell proliferation
- natural killer cells
- end stage renal disease
- public health
- case report
- newly diagnosed
- systematic review
- emergency department
- dendritic cells
- stem cells
- transcription factor
- machine learning
- randomized controlled trial
- gene expression
- peritoneal dialysis
- prognostic factors
- genome wide
- single cell
- regulatory t cells
- young adults
- bone marrow
- patient reported outcomes
- artificial intelligence
- adverse drug
- type iii