Changes in glutathione metabolism mediate the resistance of EGFR-T790M mutant lung cancer cells to erlotinib
Session type: Proffered paper sessions
EGFR tyrosine-kinase inhibitors (eg. erlotinib) are novel agents in the treatment of EGFR-dependent lung cancer. However, their long-term efficiency is impaired by the development of drug-resistance through secondary receptor mutations (eg T790M). Although decreased affinity of the mutants for the inhibitors was suggested to be responsible for this, we show that additional factors are at play.
We used 1H-NMR metabonomics profiling of erlotinib-sensitive/resistant cell pairs to identify metabolic pathways modulated during acquisition of resistance to EGFR TKIs. We then validated one of the pathways identified, using biochemical and molecular biology methods to highlight how these metabolic changes were acquired by T790M erlotinib-resistant cells.
We found that the levels of 13 metabolites were significantly altered in association with TKIs sensitivity, with GSH being considerably reduced in erlotinib-resistant (ER) cells. Using RNA interference, as well as pharmacological inhibitors of GSH pathway enzymes, we demonstrate that increasing GSH levels in ER cells sensitises these to erlotinib. Conversely, reducing the intracellular concentration of GSH renders sensitive cells resistant to the drug. Using qPCR, we show that the reduction in GSH levels in ER cells is associated with the decreased expression of the GSH synthesis enzymes, GCLC and GSS. This correlates with inhibition of NRF2, through increased KEAP1 levels and/or decreased expression of SQSTM1 and PALB2. We demonstrate these changes to be directly linked to acquisition of the T790M mutation, as transfection of this mutant EGFR in HEK293 cells causes a drop in GSH levels and decreased expression of both SQSTM1 and PALB2. Finally, administration of ethacrynic acid, a GST inhibitor that increases intracellular GSH levels, re-sensitises resistant tumours to erlotininb in a xenograft mouse model.
Taken together, our data identify a new resistance mechanism to EGFR TKIs and propose a novel therapeutic strategy to tackle this problem in the clinic.