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During the last decade, more than half of humans infected with highly pathogenic avian influenza (HPAI) H5N1 viruses have died, yet virus-induced host signaling has yet to be clearly elucidated. Airway epithelia are known to produce inflammatory mediators that contribute to HPAI H5N1-mediated pathogenicity, but a comprehensive analysis of the host response in this cell type is lacking. Here, we leveraged a system approach to identify and statistically validate signaling subnetworks that define the dynamic transcriptional response of human bronchial epithelial cells after infection with influenza A/Vietnam/1203/2004 (H5N1, VN1203). Importantly, we validated a subset of transcripts from one subnetwork in both Calu-3 cells and mice. A more detailed examination of two subnetworks involved in the immune response and keratinization processes revealed potential novel mediators of HPAI H5N1 pathogenesis and host response signaling. Finally, we show how these results compare to those for a less virulent strain of influenza virus. Using emergent network properties, we provide fresh insight into the host response to HPAI H5N1 virus infection and identify novel avenues for perturbation studies and potential therapeutic interventions for fatal HPAI H5N1 disease.

Introduction: Recurrent somatic alterations associated with pediatric, childhood, and young adult cancers have not been as intensively studied as those associated with adult cancers. Consequently, whole-exome and transcriptome approaches are still being used to support discovery efforts. However, due to several initiatives aimed at profiling genomic alterations associated with childhood cancers, a set of recurrent somatic alterations has been defined. To accelerate research in this area, we have developed a novel targeted next-generation sequencing (NGS) assay to detect relevant somatic alterations previously reported in these cancer types. Methods: The assay was developed using Ion AmpliSeq targeted sequencing technology to cover the major gene variants associated with childhood cancers, including both solid tumor and hematologic cancer types. Over 200 gene targets were included on the basis of consultation with expert pediatric oncologists, literature review of the recent pediatric cancer genomic publications, as well as inclusion of relevant markers from adult cancers that are also observed in childhood cancers. Variant classes include mutations, copy number variations, gene fusions, and gene expression. Mutations in 130 genes, copy number variants in 28 genes, and over 1,400 distinct fusion isoforms in 88 fusion driver genes are analyzed. Variant calling algorithms for both DNA and RNA were optimized and combined into a single Ion Reporter workflow. Results: The assay generated an average read depth of >3,000 reads per DNA amplicon with high uniformity (>95%), when up to 7 sample DNA-RNA pairs were analyzed with the 540 chip of the Ion S5 sequencing instrument. Minimal allele frequency detected for key hotspots was 5%. Sensitive and reproducible detection of CNV and fusion variants associated with pediatric solid tumors (EWSR1-FL1 and KIAA1549-BRAF fusions, MYC and EGFR amplification) and hematologic cancers (ETV6-RUNX1 and PML-RARA fusions) was demonstrated in orthogonally profiled FFPE, blood, and bone marrow samples. Performance was robust across sample types. Similar results were observed with manual and automated library preparation. Conclusions: A novel NGS assay, designed specifically for pediatric, childhood, and young adult cancers, and capable of detecting relevant DNA and RNA alterations from the same sample, was developed and validated. The assay is useful for characterizing relevant alterations in a wide range of cancers, including childhood leukemias and lymphomas as well as solid tumors including neuroblastoma, rhabdomyosarcoma, retinoblastoma, osteosarcoma, Ewing sarcoma, Wilms tumor, and brain and spinal cord tumors. A review of the analytical studies will be presented. Citation Format: Nickolay A. Khazanov, Chaitali Parikh, Habib Hamidi, Scott P. Myrand, Efren Ballesteros-Villagrana, Jingwei Ni, Paul D. Williams, Karen L. Clyde, Dinesh Cyanam, Armand Bankhead, III, Manimozhi Manivannan, Mark Tomilo, Susan Ewald, Jon K. Sherlock, Janice K. Au-Young, Jaclyn Biegel, Jonathan Buckley, Matthew Hiemenz, Dejerianne Ostrow, Alex Judkins, Xiaowu Gai, Tracy Busse, Alan Wayne, Deepa Bhojwani, Raca Gordana, Matthew Oberley, David Parham, Seth Sadis, Timothy Triche. Development of a next-generation sequencing (NGS) assay for pediatric, childhood, and young adult cancer research with comprehensive DNA and RNA variant detection [abstract]. In: Proceedings of the AACR Special Conference: Pediatric Cancer Research: From Basic Science to the Clinic; 2017 Dec 3-6; Atlanta, Georgia. Philadelphia (PA): AACR; Cancer Res 2018;78(19 Suppl):Abstract nr B45.

Background: Medical castration that interferes with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, clinical progression is universal, and tumors with AR-independent resistance mechanisms appear to be increasing in frequency. Consequently, there is an urgent need to develop new treatments targeting molecular pathways enriched in lethal prostate cancer. Lysine specific demethylase 1 (LSD1) is a histone demethylase and important regulator of gene expression. Here we describe a distinct role of LSD1 as a driver of proliferation and survival of castration-resistant prostate cancer (CRPC) cells independently of its demethylase function and of the AR. Methods: We used loss of function studies to determine the importance of LSD1 for survival of prostate cancer cells. To identify transcriptional networks that contribute to cell survival, we suppressed LSD1 with RNAi and performed gene expression profiling. To determine the importance of LSD1's demethylase function in regulation of target genes, we measured LSD1's canonical histone substrates (H3K4me2 and H3K9me2) using genome-wide chromatin immunoprecipitation-sequencing and measured the effect of ectopically expressed wild type or catalytically deficient LSD1 on cell survival and target gene expression. We used mass spectrometry (MS) to identify important LSD1 protein complex members. Finally, we used multiple biochemical and cellular assays and an in vivo study to confirm the mechanism of action of a small molecule inhibitor that targets critical, non-canonical functions of LSD1 in CRPC cells. Results: Cell viability assays demonstrated that LSD1 is important for proliferation and survival of CRPC cells independently of the AR. Gene expression profiles demonstrated that LSD1 activates androgen-independent genes that are enriched in lethal human tumors. Importantly, our global epigenomic studies and biochemical experiments demonstrated that LSD1's demethylase function was dispensable for these effects, while our MS studies identified cooperating LSD1 binding proteins. Finally, we identified a reversible small molecule inhibitor of LSD1 that blocked critical, demethylase-independent functions in vitro and in vivo. Conclusions: Our results demonstrate that LSD1 promotes survival of prostate cancer cells, including those that are castration-resistant, independently of its demethylase function and of the AR. Importantly, this effect is explained in part by activation of a lethal prostate cancer gene network in collaboration with specific binding proteins. Finally, that a reversible small molecule LSD1 inhibitor blocks important demethylase-independent functions and suppresses CRPC cell viability demonstrates the potential of LSD1 inhibition in this disease. Citation Format: Archana Sehrawat, Dae-Hwan Kim, Lina Gao, Yuliang Wang, Armand Bankhead, Shannon McWeeney, Carly J. King, Jacob Schwartzman, Junior Tayou, Joshua Urrutia, William H. Bisson, Daniel J. Coleman, Sunil K. Joshi, David A. Sampson, Sheila Weinmann, Bhaskar VS Kallakury, Deborah L. Berry, Reina Haque, Stephen K. Van Den Eeden, Sunil Sharma, Jared Bearss, Tomasz M. Beer, George V. Thomas, Laura M. Heiser, Joshi J. Alumkal. LSD1 activates a lethal prostate cancer gene network independently of its demethylase function [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-240.

Background: Androgen deprivation therapy (ADT) or interference with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, progression is universal, and therapies following the emergence of castration resistance do not offer durable control of the disease. Lysine specific demethylase 1 (LSD1) is a histone demethylase and a key regulator of gene expression in cancer. Prior work demonstrates that LSD1 may act as a cofactor of the AR in androgen-dependent prostate cancer cells. In this report, we describe a distinct role of LSD1 as a driver of proliferation and survival of castration-resistant prostate cancer (CRPC) cells independently of the AR and independently of histone demethylation. Methods: We used gain and loss of function studies to determine the importance of LSD1 for survival of prostate cancer cells. To identify transcriptional networks that contribute to cell survival, we suppressed LSD1 with RNAi and measured gene expression changes with microarrays. To determine the importance of histone demethylation in regulation of these gene networks, we suppressed LSD1 and measured levels of LSD1 canonical histone substrates (H3K4me2 and H3K9me2) genome-wide with chromatin immunoprecipitation-sequencing. Results: Cell viability assays demonstrated that LSD1 is important for proliferation and survival of CRPC cells independently of the AR. Microarray studies demonstrated that LSD1 activates androgen-independent genes that comprise cell cycle and embryonic stem cell maintenance gene sets that are enriched in lethal human tumors. Importantly, our global epigenomic studies after LSD1 suppression demonstrated that LSD1 activates these gene sets independently of demethylation of its canonical histone substrates. Conclusions: Our results demonstrate that LSD1 promotes CRPC cell survival independently of the AR and suggest that LSD1 regulates key pathways in CRPC through demethylation of non-histone substrates or via a scaffold function―mechanisms we are currently investigating. In summary, LSD1 contributes to CRPC cell survival through non-canonical mechanisms and represents an attractive therapeutic target in lethal prostate cancer. Citation Format: Archana Sehrawat, Lina Gao, Junior Tayou, Armand Bankhead, Laura M. Heiser, Carly J. King, Yuliang Wang, Jacob Schwartzman, Joshua Urrutia, Daniel J. Coleman, Sheila Weinmann, Bhaskar V. Kallakury, Deborah L. Berry, Reina Haque, Stephen K. Van Den Eeden, Tomasz M. Beer, George V. Thomas, Shannon McWeeney, Joshi J. Alumkal. LSD1 promotes castration-resistant prostate cancer cell survival independently of the androgen receptor and of histone demethylation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2406. doi:10.1158/1538-7445.AM2017-2406

Developmental transcription programs are epigenetically regulated by multi-protein complexes including the MLL-containing trithorax (TrxG) complexes, which methylate H3K4 to promote gene transcription. We recently reported that the TrxG protein MLL1 and its binding partner menin are overexpressed by and function as oncogenes in Ewing sarcoma. Moreover, small molecule inhibition of the menin-MLL1 protein-protein interaction leads to loss of menin and MLL1 protein expression and to inhibition of growth and tumorigenicity. For the current study we investigated the mechanistic basis of menin-MLL1 mediated oncogenic activity in Ewing sarcoma. Bru-seq analysis was performed to identify changes in nascent gene transcription in Ewing sarcoma cells following exposure to the menin-MLL interaction inhibitor MI-503. Identified targets were validated by qRT-PCR, western blot, immunocytochemistry and by interrogation of published databases. Loss of function was achieved by lentiviral shRNAs and by inhibitor treatment. Exposure of three independent Ewing sarcoma cell lines to MI-503 resulted in significant and reproducible modulation of nearly 100 genes. Bioinformatics analysis of MI-503-regulated genes revealed that the serine synthesis pathway (SSP) was the most significantly impacted pathway downstream of MI-503 treatment. The SSP has recently emerged as a major mediator of tumorigenicity in multiple human cancers. qRT-PCR confirmed reduced expression of SSP enzyme-encoding genes PHGDH, PSAT1 and PSPH in MI-503 treated cells. To determine if the SSP contributes to Ewing sarcoma pathogenesis we evaluated expression of SSP genes and proteins in tumors and cell lines. Our findings showed that Ewing sarcomas express high levels of PHGDH, PSAT1, and PSPH and interrogation of the Cancer Cell Line Encyclopedia revealed that PHGDH expression is higher in Ewing sarcoma than in any other cancer in the database. Studies of Ewing sarcoma cells in serine and glycine free media showed that cells retain viability but that exposure to the PHGDH inhibitor, CBR-5884, inhibits survival in both standard and serine/glycine-free conditions, confirming the importance of the pathway to tumor pathogenesis. To determine how menin-MLL1 promote SSP activation we performed loss of function studies and discovered that knockdown of menin, but not of MLL1, leads to a significant reduction in SSP gene expression, implicating menin as the primary mediator of SSP gene activation. Transcriptional up regulation the SSP pathway has been linked to ATF4 in non-small cell lung cancer. Significantly, ATF4 protein expression is high in Ewing sarcoma cells and ATF4 transcript and protein expression are down regulated following MI-503 treatment and menin knockdown. Together these data demonstrate that the SSP is highly active in Ewing sarcoma and that its activation is induced, at least in part, by a novel menin-ATF4 transcriptional axis. Citation Format: Laurie Kathleen Svoboda, Selina Shiqing Teh, Sudha Sud, Armand Bankhead, Brian Magnuson, Mats Ljungman, Costas Lyssiotis, Tomasz Cierpicki, Jolanta Grembecka, Elizabeth R. Lawlor. Oncogenic activation of the serine synthesis pathway by the scaffolding protein menin [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5835. doi:10.1158/1538-7445.AM2017-5835

The Systems Biology for Infectious Diseases Research program was established by the U.S. National Institute of Allergy and Infectious Diseases to investigate host-pathogen interactions at a systems level. This program generated 47 transcriptomic and proteomic datasets from 30 studies that investigate in vivo and in vitro host responses to viral infections. Human pathogens in the Orthomyxoviridae and Coronaviridae families, especially pandemic H1N1 and avian H5N1 influenza A viruses and severe acute respiratory syndrome coronavirus (SARS-CoV), were investigated. Study validation was demonstrated via experimental quality control measures and meta-analysis of independent experiments performed under similar conditions. Primary assay results are archived at the GEO and PeptideAtlas public repositories, while processed statistical results together with standardized metadata are publically available at the Influenza Research Database (www.fludb.org) and the Virus Pathogen Resource (www.viprbrc.org). By comparing data from mutant versus wild-type virus and host strains, RNA versus protein differential expression, and infection with genetically similar strains, these data can be used to further investigate genetic and physiological determinants of host responses to viral infection.

Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV., IMPORTANCE Severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI.

Virus infection is a complex biological phenomenon for which in vitro experiments provide a uniquely concise view where data is often obtained from a single population of cells, under controlled environmental conditions. Nonetheless, data interpretation and real understanding of viral dynamics is still hampered by the sheer complexity of the various intertwined spatio-temporal processes. In this paper we present a tool to address these issues: a cellular automata model describing critical aspects of in vitro viral infections taking into account spatial characteristics of virus spreading within a culture well. The aim of the model is to understand the key mechanisms of SARS-CoV infection dynamics during the first 24 hours post infection. Using a simulated annealing algorithm we tune free parameters with data from SARS-CoV infection of cultured lung epithelial cells. We also interrogate the model using a Latin Hypercube sensitivity analysis to identify which mechanisms are critical to the observed infection of host cells and the release of measured virus particles.

Kinases are dysregulated in most cancers, but the frequency of specific kinase mutations is low, indicating a complex etiology in kinase dysregulation. Here, we report a strategy to rapidly identify functionally important kinase targets, irrespective of the etiology of kinase pathway dysregulation, ultimately enabling a correlation of patient genetic profiles to clinically effective kinase inhibitors. Our methodology assessed the sensitivity of primary leukemia patient samples to a panel of 66 small-molecule kinase inhibitors over 3 days. Screening of 151 leukemia patient samples revealed a wide diversity of drug sensitivities, with 70% of the clinical specimens exhibiting hypersensitivity to one or more drugs. From this data set, we developed an algorithm to predict kinase pathway dependence based on analysis of inhibitor sensitivity patterns. Applying this algorithm correctly identified pathway dependence in proof-of-principle specimens with known oncogenes, including a rare FLT3 mutation outside regions covered by standard molecular diagnostic tests. Interrogation of all 151 patient specimens with this algorithm identified a diversity of kinase targets and signaling pathways that could aid prioritization of deep sequencing data sets, permitting a cumulative analysis to understand kinase pathway dependence within leukemia subsets. In a proof-of-principle case, we showed that in vitro drug sensitivity could predict both a clinical response and the development of drug resistance. Taken together, our results suggested that drug target scores derived from a comprehensive kinase inhibitor panel could predict pathway dependence in cancer cells while simultaneously identifying potential therapeutic options. Cancer Res; 73(1); 285–96. ©2012 AACR.

e23224Background: Development of scalable and cost-effective NGS solutions to accurately assess relevant genomic alterations is necessary to support translational research and a future precision on...

Background A systems biology interpretation of genome-scale RNA interference (RNAi) experiments is complicated by scope, experimental variability and network signaling robustness. Over representation approaches (ORA), such as the Hypergeometric or z-score, are an established statistical framework used to associate RNA interference effectors to biologically annotated gene sets or pathways. These methods, however, do not directly take advantage of our growing understanding of the interactome. Furthermore, these methods can miss partial pathway activation and may be biased by protein complexes. Here we present a novel ORA, protein interaction permutation analysis (PIPA), that takes advantage of canonical pathways and established protein interactions to identify pathways enriched for protein interactions connecting RNAi hits. Results We use PIPA to analyze genome-scale siRNA cell growth screens performed in HeLa and TOV cell lines. First we show that interacting gene pair siRNA hits are more reproducible than single gene hits. Using protein interactions, PIPA identifies enriched pathways not found using the standard Hypergeometric analysis including the FAK cytoskeletal remodeling pathway. Different branches of the FAK pathway are distinctly essential in HeLa versus TOV cell lines while other portions are uneffected by siRNA perturbations. Enriched hits belong to protein interactions associated with cell cycle regulation, anti-apoptosis, and signal transduction. Conclusion PIPA provides an analytical framework to interpret siRNA screen data by merging biologically annotated gene sets with the human interactome. As a result we identify pathways and signaling hypotheses that are statistically enriched to effect cell growth in human cell lines. This method provides a complementary approach to standard gene set enrichment that utilizes the additional knowledge of specific interactions within biological gene sets.

A computer simulation is used to model ductal carcinoma in situ, a form of non-invasive breast cancer. The simulation uses known histological morphology, cell types, and stochastic cell proliferation to evolve tumorous growth within a duct. The ductal simulation is based on a hybrid cellular automaton design using genetic rules to determine each cell's behavior. The genetic rules are a mutable abstraction that demonstrate genetic heterogeneity in a population. Our goal was to examine the role (if any) that recently discovered mammary stem cell hierarchies play in genetic heterogeneity, DCIS initiation and aggressiveness. Results show that simpler progenitor hierarchies result in greater genetic heterogeneity and evolve DCIS significantly faster. However, the more complex progenitor hierarchy structure was able to sustain the rapid reproduction of a cancer cell population for longer periods of time.

A G2/M genetic network simulation is trained with tumor incidence data from knockout experiments. The genetic network is implemented using a neural network; knockout genotypes are simulated by removing nodes in the neural network. Two analyses are used to interpret the resulting network weights. We use a novel approach of fixing the network topology that allows knockout TSG (tumor suppressor gene) data from multiple studies to overlap and indirectly inform one another. The trained simulation is validated by reproducing qualitative mammary cancer susceptibilities of ATM, BRCA1, and p53 TSGs. The work described is valuable because it allows TSG mammary cancer susceptibility to be quantified using genetic network topology and in vivo knockout data.

Late stage drug attrition rates in oncology remain higher than other therapeutic areas. To reduce attrition, it is critical to identify appropriate drug targets and pre-clinical models. Next-generation sequencing (NGS) is poised to accelerate the discovery of new drug targets through identification of genomic markers of response and identification of models to characterize candidate drivers. To maximize the value of NGS, it is imperative to develop data analysis/interpretation solutions that accurately assess genomic aberrations, delineate driver alterations from passengers, annotate alterations for clinical relevance and integrate alterations by gene and pathway. Here, we present our framework for the systematic analysis of thousands of clinical NGS samples as well as expertly curated oncology data for the purpose of identifying candidate drug targets. Our methodology was developed through a systematic interrogation of genomic aberrations in a training set of gold standard oncogenes such as EGFR and PIK3CA, and tumor suppressors such as TP53 and PTEN. The resulting platform was used to rank genes through an assessment of driver genomic aberrations, associations with patient survival, and potential clinical actionability. Using this framework, we found supporting evidence implicating NFE2L2 as an oncogene. Recurrent NFE2L2 mutations were found in multiple cancer types and associated with poor outcome in head and neck squamous cell carcinoma. Recurrent mutations were identified in: 14.0% of squamous cell lung carcinoma, 12.5% of hepatocellular carcinoma, 11.1% of infiltrating bladder urothelial carcinoma, 7.7% of cervical squamous carcinoma, and 4% of head and neck squamous cell carcinoma. We also investigated KEAP1, a repressor of NFE2L2 activity. Mutations in KEAP1 tended to localize within the NFE2L2 binding domains and displayed evidence of mutual exclusivity with NFE2L2 recurrent mutations. KEAP1 mutations were identified in 14% of lung adenocarcinoma, 13.5% of squamous cell lung carcinoma, 7.4% of infiltrating bladder urothelial carcinoma, and 4% of hepatocellular carcinoma. Genes up-regulated in patients with mutations in either NFE2L2 or KEAP1 in squamous cell lung carcinoma included many direct NFE2L2 target genes (e.g. GCLC, GCLM, NQO1). Genes up-regulated in NFE2L2 or KEAP1 mutant patients significantly associated with genes up-regulated in cell lines resistant to chemotherapy. Using Oncomine™ database curated data and cell line exome data we were able to identify cell lines that were representative of clinical populations containing these mutations. We have provided proof of concept identification of a potentially clinically relevant candidate driver gene using a novel systematic analysis of cancer genomic data. Citation Format: Sean Eddy, Mary Ellen Urick, Mark Tomilo, Armand Bankhead, Dan Rhodes, Emma T. Bowden. Rapid drug target ranking system developed from a systematic analysis of cancer genomic data from the Oncomine™ knowledgebase identifies an oncogenic role for the NFE2L2 pathway in multiple cancer types. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2779. doi:10.1158/1538-7445.AM2014-2779

Patients with chromosomal rearrangements resulting in fusion proteins are amongst the most responsive to targeted therapy. For example, targeting of the BCR-ABL fusion in chronic myelogenous leukemia (CML) with imatinib and the EML4-ALK fusion in non-small cell lung cancer (NSCLC) with crizotinib has led to dramatic patient responses in these diseases. While crizotinib is approved for use in EML4-ALK positive NSCLC through its inhibition of ALK, the drug also inhibits ROS1, MST1R (RON), MET, and more recently has been shown to inhibit the ALK homolog, LTK. To gain a more comprehensive understanding of the full therapeutic potential of crizotinib, we undertook a genomic survey of ALK, LTK, ROS1, MET and MST1R across thousands of patients subjected to full exome sequencing including patients from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), as well as tens thousands of patients from Oncomine® databases. We confirmed the presence of EML4-ALK fusions in both lung and colorectal cancer (CRC), identified a PRKAR1A-ALK fusion in CRC, and found evidence of novel recurrent ALK fusions in kidney papillary renal cell carcinoma and thyroid gland carcinoma. ALK hotspot mutations and focal amplifications were confined to neuroblastoma, as previously described. We also report the first instance of an LTK fusion, identified in thyroid gland carcinoma. LTK amplifications were also observed in 1.4% of gastric cancers and rarely in medulloblastoma and breast cancer. LTK was prominently over-expressed in leukemia, and in an analysis of over 4,000 PML-RARA fusion positive leukemia patients, LTK was amongst the most significantly over-expressed genes. In addition to confirming previously published ROS1 fusions, our survey of ROS1 identified rare novel fusions in NSCLC and glioblastoma. High-level MET amplifications were observed in 1-5% of papillary renal cell carcinoma, the intestinal subtype of gastric adenocarcinoma, oligodendroglioma, glioblastoma and lung adenocarcinoma. Hotspot mutations in MET were frequently observed in head and neck squamous cell carcinoma (HNSCC) (11%), and observed in a third of metastatic HNSCC samples. Additional hotspot mutations were also observed in lung adenocarcinoma (2%) and small cell lung cancer (2%). Aberrations in MST1R were rare. These results leverage all available genomic profiling data to provide a broadened scope of therapeutic opportunity for inhibitors like crizotinib. With the growing availability of next-generation sequencing data and analyses, such surveys can support hypothesis-driven development of targeted therapies and help expand opportunities for clinical stage therapies. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C256. Citation Format: Sean Eddy, Mark Tomilo, Mary Ellen Urick, Nickolay A. Khazanov, Paul Williams, Armand Bankhead, Dinesh Cyanam, Supra Gajjala, Peter Wyngaard, Emma Bowden, Dan R. Rhodes. Expanded clinical opportunities for crizotinib from an analysis of over 5,000 cancer patient exomes. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C256.

11017 Background: Cancer driver events occur as a result of chromosomal rearrangements. There are several examples where targeted inhibition of the resulting fusion produces dramatic clinical response. For example, the EML4-ALK fusion in non-small cell lung cancer (NSCLC). Other ALK fusions have been described in NSCLC and other diseases including the NPM-ALK fusion in anaplastic large cell lymphoma (ALCL). The efficacy of crizotinib and other ALK inhibitors are being investigated in these diseases. ALK is also subject to activation via mutation and sensitivity to crizotinib is reported in ALK mutation positive neuroblastoma. Finally, crizotinib has activity not only against ALK, but also against ROS1, MST1R and MET. ROS1 fusions have been found in NSCLC and glioblastoma, and MET amplification events in gastric adenocarcinoma identify additional settings that may benefit from crizotinib treatment. Methods: To further understand the full therapeutic potential of Crizotinib, we undertook a genomic survey of ALK, ROS1, MET and MST1R across 1,000’s of patients from the The Cancer Genome Atlas (TCGA) and Oncomine. Results: We confirmed the presence of EML4-ALK fusions in both lung and colorectal cancer (CRC), and also identified a novel ALK fusion in CRC. ALK hotspot mutations and focal amplifications were confined to neuroblastoma, as previously described. Our survey of ROS1 identified rare novel fusions in NSCLC and glioblastoma, and high-level amplifications in liposarcoma (2%) and rarely in breast cancer (0.2%). No fusions were identified for MET, however high-level amplifications were observed in 1-5% of papillary renal cell carcinoma, the intestinal subtype of gastric adenocarcinoma, oliogodendroglioma, glioblastoma and lung adenocarcinoma. Hotspot mutations were frequently observed in squamous head and neck (11%), and more rarely in hepatocellular carcinoma, small cell lung and ovarian cancers. Conclusions: These results leverage all available genomic profiling data to provide a broadened scope of therapeutic opportunity for inhibitors like crizotinib. With the growing availability of next-generation sequencing, such surveys can support hypothesis-driven development of targeted therapies.

Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV.IMPORTANCESevere acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI.

Background The complex interplay between viral replication and host immune response during infection remains poorly understood. While many viruses are known to employ anti-immune strategies to facilitate their replication, highly pathogenic virus infections can also cause an excessive immune response that exacerbates, rather than reduces pathogenicity. To investigate this dichotomy in severe acute respiratory syndrome coronavirus (SARS-CoV), we developed a transcriptional network model of SARS-CoV infection in mice and used the model to prioritize candidate regulatory targets for further investigation. Results We validated our predictions in 18 different knockout (KO) mouse strains, showing that network topology provides significant predictive power to identify genes that are important for viral infection. We identified a novel player in the immune response to virus infection, Kepi, an inhibitory subunit of the protein phosphatase 1 (PP1) complex, which protects against SARS-CoV pathogenesis. We also found that receptors for the proinflammatory cytokine tumor necrosis factor alpha (TNFα) promote pathogenesis, presumably through excessive inflammation. Conclusions The current study provides validation of network modeling approaches for identifying important players in virus infection pathogenesis, and a step forward in understanding the host response to an important infectious disease. The results presented here suggest the role of Kepi in the host response to SARS-CoV, as well as inflammatory activity driving pathogenesis through TNFα signaling in SARS-CoV infections. Though we have reported the utility of this approach in bacterial and cell culture studies previously, this is the first comprehensive study to confirm that network topology can be used to predict phenotypes in mice with experimental validation. Electronic supplementary material The online version of this article (doi:10.1186/s12918-016-0336-6) contains supplementary material, which is available to authorized users.