6011 Background: Epithelial-mesenchymal transition (EMT) has been associated with EGFR inhibitor resistance in preclinical studies of head and neck squamous cell carcinoma (HNSCC). Recently, we developed an EMT signature that predicts EGFR inhibitor resistance in lung cancer. Using this signature, we explored the association between EMT and drug response in HNSCC, focusing on the tyrosine kinase Axl as a potential therapeutic target. Methods: We conducted an integrated molecular and drug response analysis in HNSCC. A 76-gene EMT signature previously developed and validated in lung cancer was tested in HNSCC cell lines (n>50) and patient tumors from The Cancer Genome Atlas (TCGA) (n=113) and a MDACC cohort (n=105). Reverse phase protein array (RPPA) and proliferation assays were used to measure protein expression and sensitivity to erlotinib and the Axl inhibitors SGI-7079 and TP-0930. Results: The EMT signature identified distinct epithelial and mesenchymal subsets of HNSCC among cell lines and patient tumors. RPPA experiments revealed higher protein levels of the receptor tyrosine kinase Axl, vimentin, and N-cadherin and lower expression of E-cadherin and beta-catenin in mesenchymal HNSCC (p-values <0.02). Elevated Axl expression was also associated with significantly shorter overall survival in patients with locally advanced HNSCC (p<0.001 in TCGA cohort; p=0.003 MDACC). Consistent with previous studies, mesenchymal HNSCC cells exhibited resistance to erlotinib (IC50 >10μM); however, we discovered that mesenchymal HNSCC were highly sensitive to two Axl inhibitors, SGI-7079 and TP-0930 (IC50s ≤1.2μM and 0.2uM, respectively). Conclusions: Our EMT gene expression signature identified discrete epithelial and mesenchymal subgroups of HNSCC. Mesenchymal HNSCC cells expressed higher levels of Axl protein and exhibited sensitivity to Axl inhibition, but resistance to erlotinib. These results highlight differences in drug response between epithelial and mesenchymal cancers and support Axl as a potential therapeutic target and predictive marker of EGFR inhibitor resistance in HNSCC. (Funded in part by 5 P50 CA097007-10)
Exploiting Synthetic Lethality and Network Biology to Overcome EGFR Inhibitor Resistance in Lung Cancer
