FAS and NF-κB signalling modulate dependence of lung cancers on mutant EGFR

Human lung adenocarcinomas with activating mutations in EGFR (epidermal growth factor receptor) often respond to treatment with EGFR tyrosine kinase inhibitors (TKIs), but the magnitude of tumour regression is variable and transient. This heterogeneity in treatment response could result from genetic modifiers that regulate the degree to which tumour cells are dependent on mutant EGFR. Through a pooled RNA interference screen, we show that knockdown of FAS and several components of the NF-κB pathway specifically enhanced cell death induced by the EGFR TKI erlotinib in EGFR-mutant lung cancer cells. Activation of NF-κB through overexpression of c-FLIP or IKK (also known as CFLAR and IKBKB, respectively), or silencing of IκB (also known as NFKBIA), rescued EGFR-mutant lung cancer cells from EGFR TKI treatment. Genetic or pharmacologic inhibition of NF-κB enhanced erlotinib-induced apoptosis in erlotinib-sensitive and erlotinib-resistant EGFR-mutant lung cancer models. Increased expression of the NF-κB inhibitor IκB predicted for improved response and survival in EGFR-mutant lung cancer patients treated with EGFR TKI. These data identify NF-κB as a potential companion drug target, together with EGFR, in EGFR-mutant lung cancers and provide insight into the mechanisms by which tumour cells escape from oncogene dependence.     

Activation of the AXL kinase causes resistance to EGFR-targeted therapy in lung cancer

Human non-small cell lung cancers (NSCLCs) with activating mutations in EGFR frequently respond to treatment with EGFR-targeted tyrosine kinase inhibitors (TKIs), such as erlotinib, but responses are not durable, as tumors acquire resistance. Secondary mutations in EGFR (such as T790M) or upregulation of the MET kinase are found in over 50% of resistant tumors. Here, we report increased activation of AXL and evidence for epithelial-to-mesenchymal transition (EMT) in multiple in vitro and in vivo EGFR-mutant lung cancer models with acquired resistance to erlotinib in the absence of the EGFR p.Thr790Met alteration or MET activation. Genetic or pharmacological inhibition of AXL restored sensitivity to erlotinib in these tumor models. Increased expression of AXL and, in some cases, of its ligand GAS6 was found in EGFR-mutant lung cancers obtained from individuals with acquired resistance to TKIs. These data identify AXL as a promising therapeutic target whose inhibition could prevent or overcome acquired resistance to EGFR TKIs in individuals with EGFR-mutant lung cancer.     

Targeted cancer therapy

Disruption of the normal regulation of cell-cycle progression and division lies at the heart of the events leading to cancer. Complex networks of regulatory factors, the tumour microenvironment and stress signals, such as those resulting from damaged DNA, dictate whether cancer cells proliferate or die. Recent progress in understanding the molecular changes that underlie cancer development offer the prospect of specifically targeting malfunctioning molecules and pathways to achieve more effective and rational cancer therapy.     

The cancer biomarker problem

Genomic technologies offer the promise of a comprehensive understanding of cancer. These technologies are being used to characterize tumours at the molecular level, and several clinical successes have shown that such information can guide the design of drugs targeted to a relevant molecule. One of the main barriers to further progress is identifying the biological indicators, or biomarkers, of cancer that predict who will benefit from a particular targeted therapy.     

Dynamics of chronic myeloid leukaemia

The clinical success of the ABL tyrosine kinase inhibitor imatinib in chronic myeloid leukaemia (CML) serves as a model for molecularly targeted therapy of cancer, but at least two critical questions remain. Can imatinib eradicate leukaemic stem cells? What are the dynamics of relapse due to imatinib resistance, which is caused by mutations in the ABL kinase domain? The precise understanding of how imatinib exerts its therapeutic effect in CML and the ability to measure disease burden by quantitative polymerase chain reaction provide an opportunity to develop a mathematical approach. We find that a four-compartment model, based on the known biology of haematopoietic differentiation, can explain the kinetics of the molecular response to imatinib in a 169-patient data set. Successful therapy leads to a biphasic exponential decline of leukaemic cells. The first slope of 0.05 per day represents the turnover rate of differentiated leukaemic cells, while the second slope of 0.008 per day represents the turnover rate of leukaemic progenitors. The model suggests that imatinib is a potent inhibitor of the production of differentiated leukaemic cells, but does not deplete leukaemic stem cells. We calculate the probability of developing imatinib resistance mutations and estimate the time until detection of resistance. Our model provides the first quantitative insights into the in vivo kinetics of a human cancer.