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The response and remission rates in this highly generalizable sample with substantial axis I and axis III comorbidity closely resemble those seen in 8-week efficacy trials. The systematic use of easily implemented measurement-based care procedures may have assisted in achieving these results.

LTHOUGH COMMUNITY SURveys of mental disorders have been conducted in the United States since the end of World War II, 1-3 it was not until the early 1980s that fully structured lay interviews were developed to diagnose specific mental disorders. The first such instrument was the Diagnostic Interview Schedule (DIS), 4 which was developed for use in the Epidemiologic Catchment Area (ECA) study 5 to estimate the general population prevalence of mental disorders by Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM-III) criteria. 6 Major depressive disorder (MDD) prevalence estimates in the ECA sites were 3.0% to 5.9% for lifetime and 1.7% to 3.4% for 12-month. 7 The first nationally representative survey using a method similar to the ECA, the National Comorbidity Survey (NCS), 8 was conducted a decade later in 1990-1992. The NCS diagnostic instrument was a modified version of the Composite International Diagnostic Interview (CIDI) 9 to assess mental disorders by Author Affiliations are listed at the end of this article.

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.

Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.