Effective implementation of novel MET pharmacodynamic assays in translational studies
- PMID: 28164088
- PMCID: PMC5253289
- DOI: 10.21037/atm.2016.12.78
Effective implementation of novel MET pharmacodynamic assays in translational studies
Abstract
MET tyrosine kinase (TK) dysregulation is significantly implicated in many types of cancer. Despite over 20 years of drug development to target MET in cancers, a pure anti-MET therapeutic has not yet received market approval. The failure of two recently concluded phase III trials point to a major weakness in biomarker strategies to identify patients who will benefit most from MET therapies. The capability to interrogate oncogenic mutations in MET via circulating tumor DNA (ctDNA) provides an important advancement in identification and stratification of patients for MET therapy. However, a wide range in type and frequency of these mutations suggest there is a need to carefully link these mutations to MET dysregulation, at least in proof-of-concept studies. In this review, we elaborate how we can utilize recently developed and validated pharmacodynamic biomarkers of MET not only to show target engagement, but more importantly to quantitatively measure MET dysregulation in tumor tissues. The MET assay endpoints provide evidence of both canonical and non-canonical MET signaling, can be used as "effect markers" to define biologically effective doses (BEDs) for molecularly targeted drugs, confirm mechanism-of-action in testing combination of drugs, and establish whether a diagnostic test is reporting MET dysregulation. We have established standard operating procedures for tumor biopsy collections to control pre-analytical variables that have produced valid results in proof-of-concept studies. The reagents and procedures are made available to the research community for potential implementation on multiple platforms such as ELISA, quantitative immunofluorescence assay (qIFA), and immuno-MRM assays.
Keywords: MET; immunoassay; pharmacodynamic assay; phosphorylation; preclinical model; translational biomarker.
Conflict of interest statement
The authors have no conflicts of interest to declare.
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References
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