Antibody Drug Clearance: An Underexplored Marker of Outcomes with Checkpoint Inhibitors

医学 药品 抗体 肿瘤科 内科学 药理学 免疫学
作者
Yizhen Guo,Bryan Remaily,Justin Thomas,Kyeongmin Kim,Samuel K. Kulp,Thomas A. Mace,Latha P. Ganesan,Dwight H. Owen,Christopher C. Coss,Mitch A. Phelps
出处
期刊:Clinical Cancer Research [American Association for Cancer Research]
卷期号:30 (5): 942-958
标识
DOI:10.1158/1078-0432.ccr-23-1683
摘要

Immune-checkpoint inhibitor (ICI) therapy has dramatically changed the clinical landscape for several cancers, and ICI use continues to expand across many cancer types. Low baseline clearance (CL) and/or a large reduction of CL during treatment correlates with better clinical response and longer survival. Similar phenomena have also been reported with other monoclonal antibodies (mAb) in cancer and other diseases, highlighting a characteristic of mAb clinical pharmacology that is potentially shared among various mAbs and diseases. Though tempting to attribute poor outcomes to low drug exposure and arguably low target engagement due to high CL, such speculation is not supported by the relatively flat exposure-response relationship of most ICIs, where a higher dose or exposure is not likely to provide additional benefit. Instead, an elevated and/or increasing CL could be a surrogate marker of the inherent resistant phenotype that cannot be reversed by maximizing drug exposure. The mechanisms connecting ICI clearance, therapeutic efficacy, and resistance are unclear and likely to be multifactorial. Therefore, to explore the potential of ICI CL as an early marker for efficacy, this review highlights the similarities and differences of CL characteristics and CL-response relationships for all FDA-approved ICIs, and we compare and contrast these to selected non-ICI mAbs. We also discuss underlying mechanisms that potentially link mAb CL with efficacy and highlight existing knowledge gaps and future directions where more clinical and preclinical investigations are warranted to clearly understand the value of baseline and/or time-varying CL in predicting response to ICI-based therapeutics.
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