Dataset Information

MET-dependent solid tumours - molecular diagnosis and targeted therapy.

ABSTRACT: Attempts to develop MET-targeted therapies have historically focused on MET-expressing cancers, with limited success. Thus, MET expression in the absence of a genomic marker of MET dependence is a poor predictor of benefit from MET-targeted therapy. However, owing to the development of more sensitive methods of detecting genomic alterations, high-level MET amplification and activating MET mutations or fusions are all now known to be drivers of oncogenesis. MET mutations include those affecting the kinase or extracellular domains and those that result in exon 14 skipping. The activity of MET tyrosine kinase inhibitors varies by MET alteration category. The likelihood of benefit from MET-targeted therapies increases with increasing levels of MET amplification, although no consensus exists on the optimal diagnostic cut-off point for MET copy number gains identified using fluorescence in situ hybridization and, in particular, next-generation sequencing. Several agents targeting exon 14 skipping alterations are currently in clinical development, with promising data available from early-phase trials. By contrast, the therapeutic implications of MET fusions remain underexplored. Here we summarize and evaluate the utility of various diagnostic techniques and the roles of different classes of MET-targeted therapies in cancers with MET amplification, mutation and fusion, and MET overexpression.

SUBMITTER: Guo R

PROVIDER: S-EPMC7478851 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MET-dependent solid tumours - molecular diagnosis and targeted therapy.

Guo Robin R Luo Jia J Chang Jason J Rekhtman Natasha N Arcila Maria M Drilon Alexander A

Nature reviews. Clinical oncology 20200608 9

Attempts to develop MET-targeted therapies have historically focused on MET-expressing cancers, with limited success. Thus, MET expression in the absence of a genomic marker of MET dependence is a poor predictor of benefit from MET-targeted therapy. However, owing to the development of more sensitive methods of detecting genomic alterations, high-level MET amplification and activating MET mutations or fusions are all now known to be drivers of oncogenesis. MET mutations include those affecting t ...[more]

PMID: 32514147

Similar Datasets

Project description:BackgroundConstitutive MET signaling promotes invasiveness in most primary and recurrent GBM. However, deployment of available MET-targeting agents is confounded by lack of effective biomarkers for selecting suitable patients for treatment. Because endogenous HGF overexpression often causes autocrine MET activation, and also indicates sensitivity to MET inhibitors, we investigated whether it drives the expression of distinct genes which could serve as a signature indicating vulnerability to MET-targeted therapy in GBM.MethodsInterrogation of genomic data from TCGA GBM (Student's t test, GBM patients with high and low HGF expression, p ≤ 0.00001) referenced against patient-derived xenograft (PDX) models (Student's t test, sensitive vs. insensitive models, p ≤ 0.005) was used to identify the HGF-dependent signature. Genomic analysis of GBM xenograft models using both human and mouse gene expression microarrays (Student's t test, treated vs. vehicle tumors, p ≤ 0.01) were performed to elucidate the tumor and microenvironment cross talk. A PDX model with EGFR(amp) was tested for MET activation as a mechanism of erlotinib resistance.ResultsWe identified a group of 20 genes highly associated with HGF overexpression in GBM and were up- or down-regulated only in tumors sensitive to MET inhibitor. The MET inhibitors regulate tumor (human) and host (mouse) cells within the tumor via distinct molecular processes, but overall impede tumor growth by inhibiting cell cycle progression. EGFR (amp) tumors undergo erlotinib resistance responded to a combination of MET and EGFR inhibitors.ConclusionsCombining TCGA primary tumor datasets (human) and xenograft tumor model datasets (human tumor grown in mice) using therapeutic efficacy as an endpoint may serve as a useful approach to discover and develop molecular signatures as therapeutic biomarkers for targeted therapy. The HGF dependent signature may serve as a candidate predictive signature for patient enrollment in clinical trials using MET inhibitors. Human and mouse microarrays maybe used to dissect the tumor-host interactions. Targeting MET in EGFR (amp) GBM may delay the acquired resistance developed during treatment with erlotinib.

Dataset Information

MET-dependent solid tumours - molecular diagnosis and targeted therapy.

Publications

MET-dependent solid tumours - molecular diagnosis and targeted therapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets