MET-amplified gastric cancers exhibit co-amplifications of BRAF, CDK6, and EGFR.
Summary
This study investigated additional genetic alterations in MET-amplified gastric cancers (GCs), which are associated with poor prognosis and limited response to targeted therapies. Researchers found that MET amplification is frequently accompanied by co-amplifications of other oncogenes located on chromosome 7, such as BRAF, CDK6, and EGFR, in 54% of cases. These co-amplifications exhibit significant intra- and intertumoral heterogeneity. This complex heterogeneity may explain the diagnostic and therapeutic challenges, subclonal evolution, and the failure of targeted therapies in MET-amplified GCs.
Analysis
🔴 CLINIQUE: The identification of co-amplifications of oncogenes like BRAF, CDK6, and EGFR alongside MET in 54% of MET-amplified gastric cancers has major clinical implications. These findings, derived from a validation cohort of 24 cases, suggest that simple detection of MET amplification is insufficient to guide therapy. The high intra- and intertumoral heterogeneity of CNVs implies that multiple biopsies or liquid biopsy approaches might be necessary for comprehensive characterization. This would justify clinical trials evaluating combination therapies targeting several of these oncogenes, potentially with BRAF, CDK4/6, or EGFR inhibitors in addition to MET inhibitors. The time to clinical impact is likely 3-5 years, requiring prospective studies to validate these strategies. 🟢 BIOMOL: This study discovered novel co-amplifications of oncogenes (BRAF, CDK6, EGFR) with MET on chromosome 7, potentially explaining resistance to MET-targeted therapies. The methodology combined multiregional whole-exome sequencing on primary tumor and lymph node metastasis samples for discovery, followed by immunohistochemistry, in situ hybridization (FISH/CISH), and digital droplet PCR (ddPCR) for validation in a larger cohort. The use of these complementary techniques on FFPE and fresh samples allowed for precise characterization of copy number alterations and their heterogeneity. These findings have significant translational impact by identifying resistance mechanisms and poor prognostic factors, paving the way for new predictive biomarkers for combination therapies. 🔵 BIOINFO: Bioinformatic analysis was crucial for identifying non-synonymous mutations and copy number variations (CNVs) from whole-exome sequencing data. The confirmation of results through a cBioPortal database search strengthened the validity of the findings, demonstrating the application of existing bioinformatic tools to validate genomic hypotheses. The observation of marked intra- and intertumoral heterogeneity of CNVs poses challenges for algorithms designed to detect and quantify alterations, requiring robust bioinformatic approaches capable of handling the spatial and temporal complexity of tumor data. This highlights the importance of developing analysis pipelines that can integrate multiregional data for a more precise characterization of the tumor genomic landscape.