Targeting MET in Non-Small Cell Lung Cancer (NSCLC): A New Old Story?
Calogera Claudia SpagnoloGiuliana CiappinaElisa GiovannettiAndrea SqueriBarbara GranataChiara LazzariGiulia PretelliGiulia PaselloMariacarmela SantarpiaPublished in: International journal of molecular sciences (2023)
In recent years, we have seen the development and approval for clinical use of an increasing number of therapeutic agents against actionable oncogenic drivers in metastatic non-small cell lung cancer (NSCLC). Among them, selective inhibitors, including tyrosine kinase inhibitors (TKIs) and monoclonal antibodies targeting the mesenchymal-epithelial transition (MET) receptor, have been studied in patients with advanced NSCLC with MET deregulation, primarily due to exon 14 skipping mutations or MET amplification. Some MET TKIs, including capmatinib and tepotinib, have proven to be highly effective in this molecularly defined subgroup of patients and are already approved for clinical use. Other similar agents are being tested in early-stage clinical trials with promising antitumor activity. The purpose of this review is to provide an overview of MET signaling pathways, MET oncogenic alterations primarily focusing on exon 14 skipping mutations, and the laboratory techniques used to detect MET alterations. Furthermore, we will summarize the currently available clinical data and ongoing studies on MET inhibitors, as well as the mechanisms of resistance to MET TKIs and new potential strategies, including combinatorial approaches, to improve the clinical outcomes of MET exon 14-altered NSCLC patients.
Keyphrases
- tyrosine kinase
- small cell lung cancer
- end stage renal disease
- early stage
- clinical trial
- chronic kidney disease
- newly diagnosed
- ejection fraction
- peritoneal dialysis
- stem cells
- squamous cell carcinoma
- signaling pathway
- advanced non small cell lung cancer
- randomized controlled trial
- transcription factor
- lymph node
- cancer therapy
- climate change
- big data
- patient reported outcomes
- open label
- study protocol
- data analysis