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K.E. Ellison
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MINI 13 - Genetic Alterations and Testing (ID 120)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:Y. Koh, R.K. Thomas
- Coordinates: 9/08/2015, 10:45 - 12:15, 205+207
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MINI13.03 - Characterization of MET Gene and MET Protein Expression in Lung Cancer (ID 2155)
10:55 - 11:00 | Author(s): K.E. Ellison
- Abstract
- Presentation
Background:
Activation of the MET signaling pathway can propel the growth of cancer cells in non-small cell lung cancer (NSCLC). Increased MET gene by amplification and/or polysomy can cause MET protein overexpression; less common causes include mutations, translocations, and alternative RNA splicing. Clinical trials using MET as a biomarker for selection of lung cancer patients who might most benefit from targeted therapy have experienced variable outcomes. We aimed to characterize the relationship between MET protein overexpression and MET amplification or mean copy number alterations in patients with NSCLC.
Methods:
The Lung Cancer Mutation Consortium (LCMC) is performing an ongoing study of biomarkers with patients with NSCLC from 16 cancer center sites across the United States. For this analysis, 403 cases had complete data for MET protein expression by immunohistochemistry (IHC, monoclonal antibody SP44, Ventana) and MET gene amplification by fluorescence in-situ hybridization (FISH, MET/CEP7 ratio). Pathologists evaluated MET expression using the H-score, a semi-quantitative assessment of the percentage of tumor cells with no, faint, moderate, and/or strong staining, ranging from 0-300. Spearman's correlation was used to analyze the correlation between MET protein expression (H-scores) and FISH results (MET/CEP7 ratio (N=403) and MET copy number (N=341). Protein overexpression using 5 different cut-offs was compared with amplification defined as MET/CEP7 ≥ 2.2 and high mean copy number defined as ≥ 5 MET gene copies per cell using the Fisher’s exact test. Cox Proportional Hazards models were built to examine the associations of these different definitions of positivity with prognosis, adjusting for stage of disease.
Results:
MET protein expression was significantly correlated with MET copy numbers (r=0.17, p=0.0025), but not MET/CEP7 ratio (r=-0.013, p=0.80). No significant association was observed between protein overexpression using a commonly used definition for MET positivity (“at least moderate staining in ≥ 50% tumor cells”) and MET amplification (p=0.47) or high mean copy number (p=0.09). A definition for MET protein overexpression as “≥ 30% tumor cells with strong staining” was significantly associated with both MET amplification (p=0.03) and high mean copy number (p=0.007), but a definition of “≥ 10% tumor cells with strong staining” was not significantly associated with either. Definitions of protein overexpression based on high H-scores (≥200 or ≥250) were associated with high MET mean copy numbers (p=0.03 and 0.0008, respectively), but not amplification (p=0.46 and 0.12, respectively). All 5 definitions of MET protein overexpression demonstrated a significant association with worse prognosis by survival analyses (p-values ranged from 0.001 to 0.03). High MET copy number (p=0.045) was associated with worse prognosis, but MET amplification was not (p=0.07).
Conclusion:
Evaluation of NSCLC specimens from LCMC sites confirms that MET protein expression is correlated with high MET copy number and protein overexpression is associated with worse prognosis. Definitions of MET protein overexpression as “an H-score ≥250” and “≥30% tumor cells with strong staining” were significantly associated with high mean MET copy number. It may be worth reevaluating the performance of MET as a biomarker by different definitions of positivity to predict response to MET-targeted therapies.
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