Abstract
LKB1 is a commonly mutated tumor suppressor in non-small cell lung cancer that exerts complex effects on signal transduction and transcriptional regulation. To better understand the downstream impact of loss of functional LKB1, we developed a transcriptional fingerprint assay representing this phenotype. This assay was predictive of LKB1 functional loss in cell lines and clinical specimens, even those without detected sequence alterations in the gene. In silico screening of drug sensitivity data identified putative LKB1-selective drug candidates, revealing novel associations not apparent from analysis of LKB1 mutations alone. Among the candidates, MEK inhibitors showed robust association with signature expression in both training and testing datasets independent of RAS/RAF mutations. This susceptibility phenotype is directly altered by RNA interference-mediated LKB1 knockdown or by LKB1 re-expression into mutant cell lines and is readily observed in vivo using a xenograft model. MEK sensitivity is dependent on LKB1-induced changes in AKT and FOXO3 activation, consistent with genomic and proteomic analyses of LKB1-deficient lung adenocarcinomas. Our findings implicate the MEK pathway as a potential therapeutic target for LKB1-deficient cancers and define a practical NanoString biomarker to identify functional LKB1 loss. Cancer Res; 77(1); 153-63. ©2016 AACR.