[PubMed] [Google Scholar] 24. scaffolding proteins, sensitized multiple ALK fusion cell lines to the ALK inhibitors crizotinib and alectinib. Collectively, our data provides a resource that enhances our understanding of signaling and drug resistance networks consequent to ALK fusions, and identifies potential targets to improve the efficacy of ALK inhibitors in patients. Introduction Mutations or gene rearrangements of key receptor tyrosine kinases (RTKs) confer oncogenic function by disrupting the balance between downstream pro-survival and pro-apoptotic signaling pathways (1). Direct analysis and modeling support the idea that oncogene inhibition by kinase inhibitors leads to a temporal imbalance in these signals whereby pro-apoptotic signals outweigh pro-survival signals (2). For Ardisiacrispin A example, pro-survival signals from the kinases ERK and AKT, regulated by the epidermal growth factor receptor (EGFR), degrade more quickly in response to EGFR-targeted tyrosine kinase Ardisiacrispin A inhibitors (TKIs) than pro-apoptotic signals from the mitogen-activated protein kinase (MAPK) p38, leading to cell death (1). Changes in downstream signaling that alter the decay rates of survival signals can alter the aggregate survival and death signaling, resulting in changes in tumor cell survival and ultimately tumor growth or regression (2). This model implies that the molecular network circuitry that lies between the oncogene and the distal pro-survival or pro-apoptotic signals could play an important role in affecting the temporal relationships and the ultimate cell decision in response to kinase inhibitors directed against a driver oncogene. This has potential clinical relevance in developing strategies to thwart residual disease in oncogene-driven cancers and eliminate persister cells that give rise to overt disease recurrence (3C5). Downstream of RTKs is a complex network of kinases, Rabbit Polyclonal to EGFR (phospho-Ser1026) phosphatases, adaptor proteins, and negative regulators that tune survival signals emanating from RTKs. A protein network centered on EGFR using literature knowledge identified sub-networks of proteins that influenced sensitivity to EGFR-targeting agents and led to rational combinations that enhanced responses to EGFR antagonists (6). Similarly, an experimentally generated protein network using mass spectrometry-based proteomics centered on mutant EGFR in lung cancer cells was shown to harbor sub-network proteins that affect cell survival (7). Determining the functional relevance of each component in the balance of pro-survival and pro-death signals, as well as tuning responses to kinase inhibition, is complicated by complexity of the network architecture and protein expression levels of each component. Simple signaling models along with mathematical modeling have demonstrated that combination effects of hitting two proteins can be non-obvious and is a manifestation of the topology or circuitry of the signaling network (8). The existence of feedback modules can further drive uncertainly as to the role of particular combination therapies. Counterintuitive results can be observed based on which nodes are inhibited and how the nodes are organized in a network. For these reasons, focused experiments that assess removal of each node within a complex system may be necessary to fully understand their effects. We hypothesized that an RTK-centered protein network could identify sub-network proteins that affect responses to a kinase inhibitor directed against RTK. We hypothesized that a natural area to hunt for such sub-networks would be in the proximal signaling machinery used by RTK to transduce downstream signaling, by virtue of its ability to shape downstream imbalances between pro-survival and pro-apoptotic signals. To test this idea, we explored cells harboring a fusion of the gene encoding anaplastic lymphoma kinase (ALK) with that encoding echinoderm microtubule associated protein-like 4 (EML4). This EML4-ALK rearrangement occurs in approximately 4% to 5% of lung cancer patients, and these patients derive some initial benefit from treatment with ALK TKIs (9C11). However, primary resistance and acquired resistance attenuate the curative potential of ALK TKIs and are thus major hurdles in ALK-directed therapy (12, 13). One resistance mechanism is secondary ALK domain Ardisiacrispin A mutations, which in some cases can be overcome by newer generation ALK TKIs that have activity against secondary mutations (12, 14) (15). A second resistance mechanism class involves bypass signaling mechanisms, such as activation of other RTKs, including EGFR and insulin-like growth factor 1 receptor (IGFR) (16C18). Preclinical results suggest that co-targeting bypass targets,.