MET Expression in Primary and Metastatic Clear Cell Renal Cell Carcinoma: Implications of Correlative Biomarker Assessment to MET Pathway Inhibitors
Aims. Inhibitors of the MET pathway hold promise in the treatment for metastatic kidney cancer. Assessment of predictive biomarkers may be necessary for appropriate patient selection. Understanding MET expression in metastases and the correlation to the primary site is important, as distant tissue...
| Main Authors: | , , , , , , |
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| Format: | Online |
| Language: | English |
| Published: |
Hindawi Publishing Corporation
2015
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4584049/ |
| Summary: | Aims. Inhibitors of the MET pathway hold promise in the treatment for metastatic kidney cancer. Assessment of predictive biomarkers may be necessary for appropriate patient selection. Understanding MET expression in metastases and the correlation to the primary site is important, as distant tissue is not always available. Methods and Results. MET immunofluorescence was performed using automated quantitative analysis and a tissue microarray containing matched nephrectomy and distant metastatic sites from 34 patients with clear cell renal cell carcinoma. Correlations between MET expressions in matched primary and metastatic sites and the extent of heterogeneity were calculated. The mean expression of MET was not significantly different between primary tumors when compared to metastases (P = 0.1). MET expression weakly correlated between primary and matched metastatic sites (R = 0.5) and a number of cases exhibited very high levels of discordance between these tumors. Heterogeneity within nephrectomy specimens compared to the paired metastatic tissues was not significantly different (P = 0.39). Conclusions. We found that MET expression is not significantly different in primary tumors than metastatic sites and only weakly correlates between matched sites. Moderate concordance of MET expression and significant expression heterogeneity may be a barrier to the development of predictive biomarkers using MET targeting agents. |
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