Somatostatin receptor 2 signaling promotes growth and tumor survival in small-cell lung cancer.

Somatostatin receptor 2 (SSTR2) is overexpressed in a majority of neuroendocrine neoplasms, including small-cell lung carcinomas (SCLCs). SSTR2 was previously considered an inhibitory receptor on cell growth, but its agonists had poor clinical responses in multiple clinical trials. The role of this receptor as a potential therapeutic target in lung cancer merits further investigation. We evaluated the expression of SSTR2 in a cohort of 96 primary tumors from patients with SCLC and found 48% expressed SSTR2. Correlation analysis in both CCLE and an SCLC RNAseq cohort confirmed high-level expression and identified an association between NEUROD1 and SSTR2. There was a significant association with SSTR2 expression profile and poor clinical outcome. We tested whether SSTR2 expression might contribute to tumor progression through activation of downstream signaling pathways, using in vitro and in vivo systems and downregulated SSTR2 expression in lung cancer cells by shRNA. SSTR2 downregulation led to increased apoptosis and dramatically decreased tumor growth in vitro and in vivo in multiple cell lines with decreased AMPKα phosphorylation and increased oxidative metabolism. These results demonstrate a role for SSTR2 signaling in SCLC and suggest that SSTR2 is a poor prognostic biomarker in SCLC and potential future therapeutic signaling target.

The RNA binding protein FXR1 is a new driver in the 3q26-29 amplicon and predicts poor prognosis in human cancers.

Aberrant expression of RNA-binding proteins has profound implications for cellular physiology and the pathogenesis of human diseases such as cancer. We previously identified the Fragile X-Related 1 gene (FXR1) as one amplified candidate driver gene at 3q26-29 in lung squamous cell carcinoma (SCC). FXR1 is an autosomal paralog of Fragile X mental retardation 1 and has not been directly linked to human cancers. Here we demonstrate that FXR1 is a key regulator of tumor progression and its overexpression is critical for nonsmall cell lung cancer (NSCLC) cell growth in vitro and in vivo. We identified the mechanisms by which FXR1 executes its regulatory function by forming a novel complex with two other oncogenes, protein kinase C, iota and epithelial cell transforming 2, located in the same amplicon via distinct binding mechanisms. FXR1 expression is a candidate biomarker predictive of poor survival in multiple solid tumors including NSCLCs. Because FXR1 is overexpressed and associated with poor clinical outcomes in multiple cancers, these results have implications for other solid malignancies.

Identification of Proteomic Features To Distinguish Benign Pulmonary Nodules from Lung Adenocarcinoma.

We hypothesized that distinct protein expression features of benign and malignant pulmonary nodules may reveal novel candidate biomarkers for the early detection of lung cancer. We performed proteome profiling by liquid chromatography-tandem mass spectrometry to characterize 34 resected benign lung nodules, 24 untreated lung adenocarcinomas (ADCs), and biopsies of bronchial epithelium. Group comparisons identified 65 proteins that differentiate nodules from ADCs and normal bronchial epithelium and 66 proteins that differentiate ADCs from nodules and normal bronchial epithelium. We developed a multiplexed parallel reaction monitoring (PRM) assay to quantify a subset of 43 of these candidate biomarkers in an independent cohort of 20 benign nodules, 21 ADCs, and 20 normal bronchial biopsies. PRM analyses confirmed significant nodule-specific abundance of 10 proteins including ALOX5, ALOX5AP, CCL19, CILP1, COL5A2, ITGB2, ITGAX, PTPRE, S100A12, and SLC2A3 and significant ADC-specific abundance of CEACAM6, CRABP2, LAD1, PLOD2, and TMEM110-MUSTN1. Immunohistochemistry analyses for seven selected proteins performed on an independent set of tissue microarrays confirmed nodule-specific expression of ALOX5, ALOX5AP, ITGAX, and SLC2A3 and cancer-specific expression of CEACAM6. These studies illustrate the value of global and targeted proteomics in a systematic process to identify and qualify candidate biomarkers for noninvasive molecular diagnosis of lung cancer.

Targeting SLC1a5-mediated glutamine dependence in non-small cell lung cancer.

We previously elucidated the pleotropic role of solute carrier family A1 member 5 (SLC1A5) as the primary transporter of glutamine (Gln), a modulator of cell growth and oxidative stress in non-small cell lung cancer (NSCLC). The aim of our study was to evaluate SLC1A5 as a potential new therapeutic target and candidate biomarker predictive of survival and response to therapy. SLC1A5 targeting was examined in a panel of NSCLC and human bronchial cell lines by RNA interference and by a small molecular inhibitor, gamma-l-glutamyl-p-nitroanilide (GPNA). The effects of targeting SLC1A5 on cell growth, Gln uptake, ATP level, autophagy and cell death were examined. Inactivation of SLC1A5 genetically or pharmacologically decreased Gln consumption, inhibited cell growth, induced autophagy and apoptosis in a subgroup of NSCLC cell lines that overexpress SLC1A5. Targeting SLC1A5 function decreased tumor growth in NSCLC xenografts. A multivariate Cox proportional hazards analysis indicates that patients with increased SLC1A5 mRNA expression have significantly shorter overall survival (p = 0.01, HR = 1.24, 95% CI: 1.05-1.46), adjusted for age, gender, smoking history and disease stage. In an immunohistochemistry study on 207 NSCLC patients, SLC1A5 protein expression remained highly significant prognostic value in both univariate (p < 0.0001, HR = 1.45, 95% CI: 1.15-1.50) and multivariate analyses (p = 0.04, HR = 1.22, 95% CI: 1.01-1.31). These results position SLC1A5 as a new candidate prognostic biomarker for selective targeting of Gln-dependent NSCLC.

Toward rapid, high-sensitivity, volume-constrained biomarker quantification and validation using backscattering interferometry.

Realizing personalized medicine, which promises to enable early disease detection, efficient diagnostic staging, and therapeutic efficacy monitoring, hinges on biomarker quantification in patient samples. Yet, the lack of a sensitive technology and assay methodology to rapidly validate biomarker candidates continues to be a bottleneck for clinical translation. In our first direct and quantitative comparison of backscattering interferometry (BSI) to fluorescence sensing by ELISA, we show that BSI could aid in overcoming this limitation. The analytical validation study was performed against ELISA for two biomarkers for lung cancer detection: Cyfra 21-1 and Galectin-7. Spiked serum was used for calibration and comparison of analytical figures of merit, followed by analysis of blinded patient samples. Using the ELISA antibody as the probe chemistry in a mix-and-read assay, BSI provided significantly lower detection limits for spiked serum samples with each of the biomarkers. The limit of quantification (LOQ) for Cyrfa-21-1 was measured to be 230 pg/mL for BSI versus 4000 pg/mL for ELISA, and for Galectin-7, it was 13 pg/mL versus 500 pg/mL. The coefficient of variation for 5 day, triplicate determinations was <15% for BSI and <10% for ELISA. The two techniques correlated well, ranging from 3-29% difference for Cyfra 21-1 in a blinded patient sample analysis. The label-free and free-solution operation of BSI allowed for a significant improvement in analysis speed, with greater ease, improved LOQ values, and excellent day-to-day reproducibility. In this unoptimized format, BSI required 5.5-fold less sample quantity needed for ELISA (a 10 point calibration curve measured in triplicate required 36 µL of serum for BSI vs 200 µL for ELISA). The results indicate that the BSI platform can enable rapid, sensitive analytical validation of serum biomarkers and should significantly impact the validation bottleneck of biomarkers.

In-depth proteomic analysis of nonsmall cell lung cancer to discover molecular targets and candidate biomarkers.

Advances in proteomic analysis of human samples are driving critical aspects of biomarker discovery and the identification of molecular pathways involved in disease etiology. Toward that end, in this report we are the first to use a standardized shotgun proteomic analysis method for in-depth tissue protein profiling of the two major subtypes of nonsmall cell lung cancer and normal lung tissues. We identified 3621 proteins from the analysis of pooled human samples of squamous cell carcinoma, adenocarcinoma, and control specimens. In addition to proteins previously shown to be implicated in lung cancer, we have identified new pathways and multiple new differentially expressed proteins of potential interest as therapeutic targets or diagnostic biomarkers, including some that were not identified by transcriptome profiling. Up-regulation of these proteins was confirmed by multiple reaction monitoring mass spectrometry. A subset of these proteins was found to be detectable and differentially present in the peripheral blood of cases and matched controls. Label-free shotgun proteomic analysis allows definition of lung tumor proteomes, identification of biomarker candidates, and potential targets for therapy.

Compensated Interferometry Measures of CYFRA 21-1 Improve Diagnosis of Lung Cancer.

Diagnosis of lung cancer patients with indeterminate pulmonary nodules (IPNs) presents a significant clinical challenge, with morbidity and management costs of $28 billion/year. We show that a quantitative free-solution assay (FSA), coupled with a compensated interferometric reader (CIR), improves the diagnostic performance of CYFRA 21-1 as a lung cancer biomarker. FSA-CIR is a rapid, mix-and-read, isothermal, label- and enzyme-free, matrix-insensitive, and target and probe-agnostic assay. Operating FSA-CIR at ∼40, 0.75 µL samples/day delivered a serum CYFRA 21-1 limit of quantification (LOQ) of 81 pg/mL with intra-assay and interassay CVs of 4.9% and 9.6% for four-day replicate determinations. Blinded analysis of a 225 patient cohort, consisting of 75 nonmalignant nodules, 45 adenocarcinomas, 44 squamous cell carcinomas, and 61 small cell lung cancers, gave a clear separation of cases and controls, not observed in the Cobas ECL analysis. The area under the curve (AUC) for the Mayo model increased from 0.595 to 0.923 when combined with the FSA-CIR CYFRA 21-1 measurements. In a population with nodules between 6 and 30 mm, the AUC increased from 0.567 to 0.943. In this subgroup, the positive predictive value (PPV) for all tumors by the CYFRA 21-1 assay was 98.7%. Our results demonstrate increased performance of the CYFRA 21-1 assay using FSA-CIR and represents a proof of concept for redefining the performance characteristics of this important candidate biomarker.

xCT (SLC7A11)-mediated metabolic reprogramming promotes non-small cell lung cancer progression.

Many tumors increase uptake and dependence on glucose, cystine or glutamine. These basic observations on cancer cell metabolism have opened multiple new diagnostic and therapeutic avenues in cancer research. Recent studies demonstrated that smoking could induce the expression of xCT (SLC7A11) in oral cancer cells, suggesting that overexpression of xCT may support lung tumor progression. We hypothesized that overexpression of xCT occurs in lung cancer cells to satisfy the metabolic requirements for growth and survival. Our results demonstrated that 1) xCT was highly expressed at the cytoplasmic membrane in non-small cell lung cancer (NSCLC), 2) the expression of xCT was correlated with advanced stage and predicted a worse 5-year survival, 3) targeting xCT transport activity in xCT overexpressing NSCLC cells with sulfasalazine decreased cell proliferation and invasion in vitro and in vivo and 4) increased dependence on glutamine was observed in xCT overexpressed normal airway epithelial cells. These results suggested that xCT regulate metabolic requirements during lung cancer progression and be a potential therapeutic target in NSCLC.

Novel Hybrid Phenotype Revealed in Small Cell Lung Cancer by a Transcription Factor Network Model That Can Explain Tumor Heterogeneity.

Small cell lung cancer (SCLC) is a devastating disease due to its propensity for early invasion and refractory relapse after initial treatment response. Although these aggressive traits have been associated with phenotypic heterogeneity, our understanding of this association remains incomplete. To fill this knowledge gap, we inferred a set of 33 transcription factors (TF) associated with gene signatures of the known neuroendocrine/epithelial (NE) and non-neuroendocrine/mesenchymal-like (ML) SCLC phenotypes. The topology of this SCLC TF network was derived from prior knowledge and was simulated using Boolean modeling. These simulations predicted that the network settles into attractors, or TF expression patterns, that correlate with NE or ML phenotypes, suggesting that TF network dynamics underlie the emergence of heterogeneous SCLC phenotypes. However, several cell lines and patient tumor specimens failed to correlate with either the NE or ML attractors. By flow cytometry, single cells within these cell lines simultaneously expressed surface markers of both NE and ML differentiation, confirming the existence of a "hybrid" phenotype. Upon exposure to standard-of-care cytotoxic drugs or epigenetic modifiers, NE and ML cell populations converged toward the hybrid state, suggesting possible escape from treatment. Our findings indicate that SCLC phenotypic heterogeneity can be specified dynamically by attractor states of a master regulatory TF network. Thus, SCLC heterogeneity may be best understood as states within an epigenetic landscape. Understanding phenotypic transitions within this landscape may provide insights to clinical applications. Cancer Res; 77(5); 1063-74. ©2016 AACR.

Fluorescence-based measurement of cystine uptake through xCT shows requirement for ROS detoxification in activated lymphocytes.

T and B lymphocytes undergo metabolic re-programming upon activation that is essential to allow bioenergetics, cell survival, and intermediates for cell proliferation and function. To support changes in the activity of signaling pathways and to provide sufficient and necessary intracellular metabolites, uptake of extracellular nutrients increases sharply with metabolic re-programming. One result of increased metabolic activity can be reactive oxygen species (ROS), which can be toxic when accumulated in excess. Uptake of cystine allows accumulation of cysteine that is necessary for glutathione synthesis and ROS detoxification. Cystine uptake is required for T cell activation and function but measurements based on radioactive labeling do not allow analysis on single cell level. Here we show the critical role for cystine uptake in T cells using a method for measurement of cystine uptake using a novel CystineFITC probe. T cell receptor stimulation lead to upregulation of the cystine transporter xCT (SLC7a11) and increased cystine uptake in CD4+ and CD8+ human T cells. Similarly, lipopolysaccharide stimulation increased cystine uptake in human B cells. The CystineFITC probe was not toxic and could be metabolized to prevent cystine starvation induced cell death. Furthermore, blockade of xCT or competition with natural cystine decreased uptake of CystineFITC. CystineFITC is thus a versatile tool that allows measurement of cystine uptake on single cell level and shows the critical role for cystine uptake for T cell ROS regulation and activation.

Preclinical Evaluation of 4-[18F]Fluoroglutamine PET to Assess ASCT2 Expression in Lung Cancer.

PURPOSE: Alanine-serine-cysteine transporter 2 (ASCT2) expression has been demonstrated as a promising lung cancer biomarker. (2S,4R)-4-[(18)F]Fluoroglutamine (4-[(18)F]fluoro-Gln) positron emission tomography (PET) was evaluated in preclinical models of non-small cell lung cancer as a quantitative, non-invasive measure of ASCT2 expression. PROCEDURES: In vivo microPET studies of 4-[(18)F]fluoro-Gln uptake were undertaken in human cell line xenograft tumor-bearing mice of varying ASCT2 levels, followed by a genetically engineered mouse model of epidermal growth factor receptor (EGFR)-mutant lung cancer. The relationship between a tracer accumulation and ASCT2 levels in tumors was evaluated by IHC and immunoblotting. RESULT: 4-[(18)F]Fluoro-Gln uptake, but not 2-deoxy-2-[(18)F]fluoro-D-glucose, correlated with relative ASCT2 levels in xenograft tumors. In genetically engineered mice, 4-[(18)F]fluoro-Gln accumulation was significantly elevated in lung tumors, relative to normal lung and cardiac tissues. CONCLUSIONS: 4-[(18)F]Fluoro-Gln PET appears to provide a non-invasive measure of ASCT2 expression. Given the potential of ASCT2 as a lung cancer biomarker, this and other tracers reflecting ASCT2 levels could emerge as precision imaging diagnostics in this setting.

The airway epithelium undergoes metabolic reprogramming in individuals at high risk for lung cancer.

The molecular determinants of lung cancer risk remain largely unknown. Airway epithelial cells are prone to assault by risk factors and are considered to be the primary cell type involved in the field of cancerization. To investigate risk-associated changes in the bronchial epithelium proteome that may offer new insights into the molecular pathogenesis of lung cancer, proteins were identified in the airway epithelial cells of bronchial brushing specimens from risk-stratified individuals by shotgun proteomics. Differential expression of selected proteins was validated by parallel reaction monitoring mass spectrometry in an independent set of individual bronchial brushings. We identified 2,869 proteins, of which 312 proteins demonstrated a trend in expression. Pathway analysis revealed enrichment of carbohydrate metabolic enzymes in high-risk individuals. Glucose consumption and lactate production were increased in human bronchial epithelial BEAS2B cells treated with cigarette smoke condensate for 7 months. Increased lipid biosynthetic capacity and net reductive carboxylation were revealed by metabolic flux analyses of [U-13C5] glutamine in this in vitro model, suggesting profound metabolic reprogramming in the airway epithelium of high-risk individuals. These results provide a rationale for the development of potentially new chemopreventive strategies and selection of patients for surveillance programs.

Inhibition of the Biosynthesis of Prostaglandin E2 By Low-Dose Aspirin: Implications for Adenocarcinoma Metastasis.

Meta-analyses have demonstrated that low-dose aspirin reduces the risk of developing adenocarcinoma metastasis, and when colon cancer is detected during aspirin treatment, there is a remarkable 83% reduction in risk of metastasis. As platelets participate in the metastatic process, the antiplatelet action of low-dose aspirin likely contributes to its antimetastatic effect. Cycloxooxygenase-2 (COX-2)-derived prostaglandin E2 (PGE2) also contributes to metastasis, and we addressed the hypothesis that low-dose aspirin also inhibits PGE2 biosynthesis. We show that low-dose aspirin inhibits systemic PGE2 biosynthesis by 45% in healthy volunteers (P < 0.0001). Aspirin is found to be more potent in colon adenocarcinoma cells than in the platelet, and in lung adenocarcinoma cells, its inhibition is equivalent to that in the platelet. Inhibition of COX by aspirin in colon cancer cells is in the context of the metastasis of colon cancer primarily to the liver, the organ exposed to the same high concentrations of aspirin as the platelet. We find that the interaction of activated platelets with lung adenocarcinoma cells upregulates COX-2 expression and PGE2 biosynthesis, and inhibition of platelet COX-1 by aspirin inhibits PGE2 production by the platelet-tumor cell aggregates. In conclusion, low-dose aspirin has a significant effect on extraplatelet cyclooxygenase and potently inhibits COX-2 in lung and colon adenocarcinoma cells. This supports a hypothesis that the remarkable prevention of metastasis from adenocarcinomas, and particularly from colon adenocarcinomas, by low-dose aspirin results from its effect on platelet COX-1 combined with inhibition of PGE2 biosynthesis in metastasizing tumor cells. Cancer Prev Res; 9(11); 855-65. ©2016 AACR.

Acyl-coenzyme A-binding protein regulates Beta-oxidation required for growth and survival of non-small cell lung cancer.

We identified acyl-coenzyme A-binding protein (ACBP) as part of a proteomic signature predicting the risk of having lung cancer. Because ACBP is known to regulate ß-oxidation, which in turn controls cellular proliferation, we hypothesized that ACBP contributes to regulation of cellular proliferation and survival of non-small cell lung cancer (NSCLC) by modulating ß-oxidation. We used matrix-assisted laser desorption/ionization-imaging mass spectrometry (MALDI-IMS) and immunohistochemistry (IHC) to confirm the tissue localization of ABCP in pre-invasive and invasive NSCLCs. We correlated ACBP gene expression levels in NSCLCs with clinical outcomes. In loss-of-function studies, we tested the effect of the downregulation of ACBP on cellular proliferation and apoptosis in normal bronchial and NSCLC cell lines. Using tritiated-palmitate ((3)H-palmitate), we measured ß-oxidation levels and tested the effect of etomoxir, a ß-oxidation inhibitor, on proliferation and apoptosis. MALDI-IMS and IHC analysis confirmed that ACBP is overexpressed in pre-invasive and invasive lung cancers. High ACBP gene expression levels in NSCLCs correlated with worse survival (HR = 1.73). We observed a 40% decrease in ß-oxidation and concordant decreases in proliferation and increases in apoptosis in ACBP-depleted NSCLC cells as compared with bronchial airway epithelial cells. Inhibition of ß-oxidation by etomoxir in ACBP-overexpressing cells produced dose-dependent decrease in proliferation and increase in apoptosis (P = 0.01 and P < 0.001, respectively). These data suggest a role for ACBP in controlling lung cancer progression by regulating ß-oxidation.

Integrative genomics analysis identifies candidate drivers at 3q26-29 amplicon in squamous cell carcinoma of the lung.

PURPOSE: Chromosome 3q26-29 is a critical region of genomic amplification in lung squamous cell carcinomas (SCC). Identification of candidate drivers in this region could help uncover new mechanisms in the pathogenesis and potentially new targets in SCC of the lung. EXPERIMENTAL DESIGN: We conducted a meta-analysis of seven independent datasets containing a total of 593 human primary SCC samples to identify consensus candidate drivers in 3q26-29 amplicon. Through integrating protein-protein interaction network information, we further filtered for candidates that may function together in a network. Computationally predicted candidates were validated using RNA interference (RNAi) knockdown and cell viability assays. Clinical relevance of the experimentally supported drivers was evaluated in an independent cohort of 52 lung SCC patients using survival analysis. RESULTS: The meta-analysis identified 20 consensus candidates, among which four (SENP2, DCUN1D1, DVL3, and UBXN7) are involved in a small protein-protein interaction network. Knocking down any of the four proteins led to cell growth inhibition of the 3q26-29-amplified SCC. Moreover, knocking down of SENP2 resulted in the most significant cell growth inhibition and downregulation of DCUN1D1 and DVL3. Importantly, a gene expression signature composed of SENP2, DCUN1D1, and DVL3 stratified patients into subgroups with different response to adjuvant chemotherapy. CONCLUSION: Together, our findings show that SENP2, DCUN1D1, and DVL3 are candidate driver genes in the 3q26-29 amplicon of SCC, providing novel insights into the molecular mechanisms of disease progression and may have significant implication in the management of SCC of the lung.

SLC1A5 mediates glutamine transport required for lung cancer cell growth and survival.

PURPOSE: We have previously identified solute-linked carrier family A1 member 5 (SLC1A5) as an overexpressed protein in a shotgun proteomic analysis of stage I non-small cell lung cancer (NSCLC) when compared with matched controls. We hypothesized that overexpression of SLC1A5 occurs to meet the metabolic demand for lung cancer cell growth and survival. EXPERIMENTAL DESIGN: To test our hypothesis, we first analyzed the protein expression of SLC1A5 in archival lung cancer tissues by immunohistochemistry and immunoblotting (N = 98) and in cell lines (N = 36). To examine SLC1A5 involvement in amino acid transportation, we conducted kinetic analysis of l-glutamine (Gln) uptake in lung cancer cell lines in the presence and absence of a pharmacologic inhibitor of SLC1A5, gamma-l-Glutamyl-p-Nitroanilide (GPNA). Finally, we examined the effect of Gln deprivation and uptake inhibition on cell growth, cell-cycle progression, and growth signaling pathways of five lung cancer cell lines. RESULTS: Our results show that (i) SLC1A5 protein is expressed in 95% of squamous cell carcinomas (SCC), 74% of adenocarcinomas (ADC), and 50% of neuroendocrine tumors; (ii) SLC1A5 is located at the cytoplasmic membrane and is significantly associated with SCC histology and male gender; (iii) 68% of Gln is transported in a Na(+)-dependent manner, 50% of which is attributed to SLC1A5 activity; and (iv) pharmacologic and genetic targeting of SLC1A5 decreased cell growth and viability in lung cancer cells, an effect mediated in part by mTOR signaling. CONCLUSIONS: These results suggest that SLC1A5 plays a key role in Gln transport controlling lung cancer cells' metabolism, growth, and survival.

Co-expression network analysis identifies Spleen Tyrosine Kinase (SYK) as a candidate oncogenic driver in a subset of small-cell lung cancer.

BACKGROUND: Oncogenic mechanisms in small-cell lung cancer remain poorly understood leaving this tumor with the worst prognosis among all lung cancers. Unlike other cancer types, sequencing genomic approaches have been of limited success in small-cell lung cancer, i.e., no mutated oncogenes with potential driver characteristics have emerged, as it is the case for activating mutations of epidermal growth factor receptor in non-small-cell lung cancer. Differential gene expression analysis has also produced SCLC signatures with limited application, since they are generally not robust across datasets. Nonetheless, additional genomic approaches are warranted, due to the increasing availability of suitable small-cell lung cancer datasets. Gene co-expression network approaches are a recent and promising avenue, since they have been successful in identifying gene modules that drive phenotypic traits in several biological systems, including other cancer types. RESULTS: We derived an SCLC-specific classifier from weighted gene co-expression network analysis (WGCNA) of a lung cancer dataset. The classifier, termed SCLC-specific hub network (SSHN), robustly separates SCLC from other lung cancer types across multiple datasets and multiple platforms, including RNA-seq and shotgun proteomics. The classifier was also conserved in SCLC cell lines. SSHN is enriched for co-expressed signaling network hubs strongly associated with the SCLC phenotype. Twenty of these hubs are actionable kinases with oncogenic potential, among which spleen tyrosine kinase (SYK) exhibits one of the highest overall statistical associations to SCLC. In patient tissue microarrays and cell lines, SCLC can be separated into SYK-positive and -negative. SYK siRNA decreases proliferation rate and increases cell death of SYK-positive SCLC cell lines, suggesting a role for SYK as an oncogenic driver in a subset of SCLC. CONCLUSIONS: SCLC treatment has thus far been limited to chemotherapy and radiation. Our WGCNA analysis identifies SYK both as a candidate biomarker to stratify SCLC patients and as a potential therapeutic target. In summary, WGCNA represents an alternative strategy to large scale sequencing for the identification of potential oncogenic drivers, based on a systems view of signaling networks. This strategy is especially useful in cancer types where no actionable mutations have emerged.