Despite the success of tyrosine kinase-based cancer therapeutics, for most solid tumors the tyrosine kinases that drive disease remain unknown, limiting our ability to identify drug targets and predict response. Here we present the first large-scale survey of tyrosine kinase activity in lung cancer. Using a phosphoproteomic approach, we characterize tyrosine kinase signaling across 41 non-small cell lung cancer (NSCLC) cell lines and over 150 NSCLC tumors. Profiles of phosphotyrosine signaling are generated and analyzed to identify known oncogenic kinases such as EGFR and c-Met as well as novel ALK and ROS fusion proteins. Other activated tyrosine kinases such as PDGFRalpha and DDR1 not previously implicated in the genesis of NSCLC are also identified. By focusing on activated cell circuitry, the approach outlined here provides insight into cancer biology not available at the chromosomal and transcriptional levels and can be applied broadly across all human cancers.

EGF receptor ͉ c-Met ͉ oncogene dependence ͉ proteomics ͉ stable isotope labeling with amino acids in cell culture

Summary In mice, Lkb1 deletion and activation of KrasG12D results in lung tumors with a high penetrance of lymph node and distant metastases. We analyzed these primary and metastatic de novo lung cancers with integrated genomic and proteomic profiles and have identified gene and phosphoprotein signatures associated with Lkb1 loss and progression to invasive and metastatic lung tumors. These studies revealed that SRC is activated in Lkb1 deficient primary and metastatic lung tumors and that the combined inhibition of SRC, PI3K and MEK1/2 resulted in synergistic tumor regression. These studies demonstrate that integrated genomic and proteomic analyses can be used to identify signaling pathways that may be targeted for treatment.

SUMMARY BYL719, which selectively inhibits the alpha isoform of the phosphatidylinositol 3-kinase (PI3K) catalytic subunit (p110α), is currently in clinical trials for the treatment of solid tumors, especially luminal breast cancers with PIK3CA mutations and/or HER2 amplification. This study reveals that, even among these sensitive cancers, the initial efficacy of p110α inhibition is mitigated by rapid re-accumulation of the PI3K product PIP3 produced by the p110β isoform. Importantly, the reactivation of PI3K mediated by p110β does not invariably restore AKT phosphorylation, demonstrating the limitations of using phospho-AKT as a surrogate to measure PI3K activation. Consistently, we show that the addition of the p110β inhibitor to BYL719 prevents the PIP3 rebound and induces greater antitumor efficacy in HER2-amplified and PIK3CA mutant cancers.

Most tools developed to visualize hierarchically clustered heatmaps generate static images. Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations. Clustergrammer can be used to generate shareable interactive visualizations by uploading a data table to a web-site, or by embedding Clustergrammer in Jupyter Notebooks. The Clustergrammer core libraries can also be used as a toolkit by developers to generate visualizations within their own applications. Clustergrammer is demonstrated using gene expression data from the cancer cell line encyclopedia (CCLE), original post-translational modification data collected from lung cancer cells lines by a mass spectrometry approach, and original cytometry by time of flight (CyTOF) single-cell proteomics data from blood. Clustergrammer enables producing interactive web based visualizations for the analysis of diverse biological data.