bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract A33: Integrated analysis of molecular and metabolomic data to identify drug resistance mechanisms in lung cancers
Authors: Merchant Anand S. , Abrams Natalie Fedorova , Stahlberg Eric A. , Weaver Zoe
Published: August 2014

Consistent bioinformatics analysis approaches of chemically perturbed biological systems are needed in order to achieve meaningful integration of results from multiple experiments in support of cancer systems biology research. Our initial efforts have focused on identifying and contrasting molecular mechanisms that reveal biochemical events affecting non-small cell lung cancers in the context of combination drug therapies as a model for defining these approaches. While the link between growth factor receptor mutations, target inhibitor drugs and non-small cell lung cancer is well established, the basis of variable response in different patient cohorts is still poorly understood and is the subject of ongoing investigations. Data for our efforts were provided by the NCI's Center for Advanced Preclinical Research. Mice genetically engineered to develop erlotinib-sensitive lung adenocarcinomas were subjected to drug compounds that are currently in clinical trials, as well as erlotinib, individually and in combination, to study early response and development of late resistance. Metabolite data, gene expression data, and histological data were collected and used in defining the initial analysis approach. While evaluation of analysis approaches continues, preliminary results already indicate these data can be effective in assessing drug efficacy on reducing tumor burden. Further efforts are underway to develop analysis techniques to explore the underlying dynamic processes.

Citation Format: Anand S. Merchant, Natalie Fedorova Abrams, Eric A. Stahlberg, Zoe Weaver. Integrated analysis of molecular and metabolomic data to identify drug resistance mechanisms in lung cancers [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr A33.
Abstract A35: Predicting drugs effect on transcription factor activity by regulatory network analysis of drug perturbed cellular states
Authors: Shen Yao , Alvarez Mariano , Pampou Sergey , Coku Jorida , Califano Andrea
Published: August 2014

Phenotypic changes during pathophysiological processes can be efficiently captured by genome-wide gene expression signatures or molecular phenotypes. Transcription factors (TFs) are the key components of the transcriptional regulatory network that integrates intracellular and extracellular stimuli and generates a response in the form of specific gene expression signatures.

We have shown the existence and dissected the components of this integrative logic layer in several pathologic and physiologic processes.

Moreover, perturbation of key components of this machinery can be efficiently used to induce desired phenotypic changes. However, TFs have been rather elusive targets for pharmacological intervention.

Here, by using a cell-context specific network-based approach, we generated a comprehensive map between small compounds and TF activity. We leveraged the large collection of expression profiles in response to small molecule perturbagens from CMAP to first reverse-engineer transcriptionally regulatory networks in 3 different cellular context (Breast: MCF7, Prostate:PC3 and Myeloma:HL60) by the ARACNe algorithm, and then interrogate these networks with the MARINa algorithm to identify TFs whose activity is affected by the profiled compounds.

We show two different evidences that validate our method. First, we correctly identified ESR1 as the very top TF whose activity is affected by the estrogen antagonists tamoxifen, raloxifen and clomifene. Second, we selected 10 compounds from the 1,400 represented in the MCF7 CMAP dataset that our method predict as STAT3 perturbagens. From these, 4 showed a significant inhibition of STAT3 activity in a cell-based STAT3 reported assay.

Citation Format: Yao Shen, Mariano Alvarez, Sergey Pampou, Jorida Coku, Andrea Califano. Predicting drugs effect on transcription factor activity by regulatory network analysis of drug perturbed cellular states [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr A36.
Abstract A7: Investigating the differential regulation of poly(ADP-ribose) polymerases in cancer
Authors: Krukenberg Kristin , Mitchison Timothy
Published: August 2014

Poly(ADP-ribose) (pADPr) is an important but poorly understood post-translational modification. Poly(ADP-ribose) polymerases (PARPs) catalyze the addition of ADP-ribose onto acceptor proteins using NAD+ as a substrate. The function of pADPr has been best studied in the context of the DNA damage response where PARPs are activated by DNA damage, recruit repair machinery to the site of damage, and modify histones altering chromatin structure. Emerging evidence reveals broader roles for pADPr in other essential cellular pathways including apoptosis, inflammation, and stress responses. The role of PARPs in DNA damage has led to much interest in PARP inhibitors as chemotherapeutics, and multiple inhibitors are currently in clinical trials. The focus so far has been on using PARP inhibitors in combination with DNA damaging agents or in cancers deficient in DNA damage repair pathways (e.g., BRCA1/2 deficient cancers). Recent studies suggest that PARP inhibitors may also have utility in treating some cancers independent of DNA damage, e.g., Ewing's sarcoma. This increases the importance of understanding PARP biology and the role of pADPr in the growth and survival of cancer cells, and opens up the question of why inhibiting PARPs alone is more detrimental to some cancer cells than to others. We have developed a method for quantifying pADPr levels in cell lysates with increased sensitivity compared to previous approaches. Using this method we have found that pADPr levels vary widely between breast cancer cell lines. The differences in pADPr levels appear to be largely attributable to differences in PARP1 activity. PARP1, the most abundant family member, is primarily localized to the nucleus and is overexpressed in some cancers. We are currently investigating the mechanisms behind PARP1 activation and the implications of this finding for both basic biology and chemotherapy. Not only will this provide insight into the biological function of pADPr, but pADPr levels may be useful as an indicator of which patients will respond best to PARP inhibitors or other treatments.

Citation Format: Kristin Krukenberg, Timothy Mitchison. Investigating the differential regulation of poly(ADP-ribose) polymerases in cancer [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr A7.
Abstract A8: Network analysis of retroviral and transposon mutagenesis sites in B cell lymphoma converges on MyD88 pathway
Authors: Lifton Samuel , Olivier Alicia , Dupuy Adam , Dubois Wendy , Wolff Linda , Janz Siegfried
Published: August 2014

Using the murine leukemia virus (MuLV) and the Sleeping Beauty retrotransposon, we have generated several thousand mutagenesis sites associated with development of B cell lymphoma in iMyc mice. We have utilized the gene-centric common insertion site algorithm (gCIS) to determine common events in B cell lymphomagenesis. After gCIS analysis, we have established networks based on filtering with known protein-protein and transcription factor-transcription factor interaction networks. Additionally, gene set enrichment analysis was performed subtracting T cell lymphoma-associated pathways from B cell lymphoma-associated pathways. Several promising networks have been identified through these methods, including one leading to the activation of MyD88. MyD88 mutations are recently identified in several B cell lymphomas. These findings demonstrate the utility of these methods and suggest that common insertion sites during mutagenesis can either affect a single important factor, or converge on its interaction partners.

Citation Format: Samuel Lifton, Alicia Olivier, Adam Dupuy, Wendy Dubois, Linda Wolff, Siegfried Janz. Network analysis of retroviral and transposon mutagenesis sites in B cell lymphoma converges on MyD88 pathway [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr A8.
Abstract IA10: Interrogating gene regulatory networks to explore the boundary between chemistry and biology in cancer
Authors: Califano Andrea
Published: August 2014

In this presentation we will discuss new methods for the computational assembly and experimental validation of gene regulatory network based approaches to study the activity of small-molecules in mouse and human cells. Specifically, we will address the interrogation of context specific models of regulation, inferred from primary data, to elucidate effector genes mediating compound mechanism of action in vitro and in vivo. The analysis can be specifically directed to the identification of biomarkers of drug activity, candidate targets to abrogate resistance, as well as candidate target for combination therapy. Furthermore, we will discuss various mechanisms supporting synergistic compound activity in cancer cells and discuss a systems biology approach that allows the identification of such synergistic combinations on a computational, predictive basis. Specific examples in high-grade glioma and non-small cancer adenocarcinoma will be discussed.

Citation Format: Andrea Califano. Interrogating gene regulatory networks to explore the boundary between chemistry and biology in cancer [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA10.
Abstract IA13: Super-resolution fluorescence microscopy of cells and tissues
Authors: Zhuang Xiaowei
Published: August 2014

Light microscopy is an essential tool in biological research. However, the spatial resolution of light microscopy, classically limited by diffraction to a few hundred nanometers, is substantially larger than typical molecular length scales in cells. Hence many subcellular structures cannot be resolved by conventional light microscopy. We recently developed a new form of super-resolution fluorescence microscopy, stochastic optical reconstruction microscopy (STORM), that breaks the diffraction limit. STORM uses single-molecule imaging and photo-switchable fluorescent probes to temporally separate the spatially overlapping images of individual molecules. This approach allows the localization of fluorescent probes with nanometer precision and the construction of sub-diffraction-limit images. Using this method, we have achieved multicolor and three-dimensional (3-D) imaging of live cells and tissues with nanometer-scale resolution. In this talk, I will discuss the general concept, recent technological advances and biological applications of STORM.

Citation Format: Xiaowei Zhuang. Super-resolution fluorescence microscopy of cells and tissues [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA13.
Abstract IA15: Predicting drug sensitivity from cancer cell lines
Authors: Margolin Adam Arne , Jang In Sock , Friend Stephen
Published: August 2014

High-throughput molecular characterization technologies have enabled detailed genetic and genomic characterization of large panels of cancer cell lines, including profiling of gene expression, copy number variation (CNV), SNP, mutation, and RNA-seq. The same cell lines have also been profiled for sensitivity to potential anti-cancer compounds, allowing development of computational models used to predict genotype-specific drug treatments linked to tumor molecular subtypes.

Inferring such models is challenging because the model inputs contain far more features than observations, known as the p>>n problem, precluding the use of classical statistical models such as least squares (a.k.a. multiple linear regression). Recently, generalized linear models or penalized linear models have been proposed and extended for feature selection and overcoming the p>>n. Bayesian extension of such methods have also been developed, using algorithms such as Metropolis-Hasting and Markov Chain Monte Carlo, and demonstrated to improve prediction accuracy at the expense of increased computing cost.

A comprehensive evaluation of predictive modeling techniques is essential to leverage cell line studies to infer the most accurate genetic predictors of drug sensitivity, which can then be used to inform patient selection strategies in clinical trials and to identify functional genetic determinants of drug sensitivity or resistance. In this study, we evaluate state-of-the-art predictive models which utilize dimension reduction methods (e.g., partial least square, support vector machine, principal component regression), feature selection (e.g., LASSO, RIDGE, and elastic-net), and Bayesian feature selection (e.g., Bayesian LASSO and Bayesian RIDGE). We assess each method based on 1) the accuracy of sensitivity predictions in a cross validation setting and in an independent dataset, and 2) the biological coherence of inferred predictive features by comparison to publicly available pathway databases.

Citation Format: Adam Arne Margolin, In Sock Jang, Stephen Friend. Predicting drug sensitivity from cancer cell lines. [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA15.
Abstract IA16: Chemical inhibition of bromodomains
Authors: Bradner James E.
Published: August 2014

In cancer, epigenetic proteins are among the most promising and intently pursued targets in drug discovery. This relates to the growing appreciation that cancer growth pathways are centrally influenced by proteins which modify chromatin. Already, inhibitors of DNA methyltransferases and histone deacetylases have demonstrated substantial clinical efficacy leading to regulatory approval for use in hematologic malignancies. These events have triggered intense competition to develop inhibitors of chromatin modifying enzymes, or so-called epigenetic “writers” and “erasers.” Perhaps owing to perceptions regarding the feasibility of targeting protein:protein interactions, small-molecule inhibitors of chromatin-binding modules or epigenetic “readers” have not been described. Recently, we reported the first potent, small-molecule inhibitor of human bromodomains, JQ1, which exhibits selectivity for the BET family of bromodomain-containing transcriptional co-activators. Of broad relevance to cancer, we will present research demonstrating that c-Myc expression is critically dependent on BRD4 function and localization to discrete upstream regulatory regions. Exposure of cancer cells to JQ1 prompts immediate downregulation of c-Myc expression leading to suppression of a transcriptional program associated with proliferation, survival and metabolic adaptation. In translational models of Myc-dependent hematologic malignancies, the efficacy of JQ1 treatment establishes a mechanistic rationale for the leveraged clinical development of drug-like JQ1 derivatives. Toward this objective, we have completed chemical optimization of novel, drug-like inhibitors of BET bromodomains as reagents capable of supporting human clinical investigation. This research has established the feasibility of inhibiting epigenetic reader proteins with efficient, cell-permeable, small molecules. In support of an open-innovation model of chemical biology, we have created a chemical probe allowing the broad study of chromatin biology, which has already been provided to more than 250 academic, governmental and industrial laboratories worldwide. Together, we have rapidly identified mechanism-based opportunities for clinical translation in cancer, inflammation, and metabolic diseases.

Citation Format: James E. Bradner. Chemical inhibition of bromodomains [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA16.
Abstract IA17: Developing improved methods to measure human DNA repair capacity
Authors: Samson Leona D.
Published: August 2014

The Samson lab has been developing potentially high-throughput methods for measuring DNA repair capacity (DRC) in human cells. These approaches are modeled on the pioneering work of the late Professor Lawrence Grossman and rely on the transfection of plasmids containing specific types of DNA damage and then monitoring the repair of that damage by the expression of a reporter gene that is poorly expressed in the absence of repair. One of our goals is to simultaneously measure DRC for a variety of DNA repair pathways using a multiplexed approach and a collection of fluorescent proteins of different color. So far we have developed methods for measuring relative levels of nucleotide excision repair, homologous recombination, DNA mismatch repair, and MGMT mediated repair. We are currently extending this approach to encompass other DNA repair pathways. Measuring DNA repair capacity in various human cell types may help predict inter-individual differences in the ability of people to respond upon exposure to environmental agents and thus predict their cancer susceptibility. Moreover, knowing the DNA repair capacity of tumor cells for different types of DNA damage could help in choosing more effective chemotherapy regimens.

Citation Format: Leona D. Samson. Developing improved methods to measure human DNA repair capacity [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA17.
Abstract IA18: A genomics approach to discover small-molecule perturbagens of cancer cells
Authors: Stegmaier Kimberly
Published: August 2014

Aberrantly activated transcription factors and/or transcriptional programs play a critical role in the development of most cancers. In some cancers, the oncogenic transcription factors have been well characterized and result from either the ectopic activity of native transcription factors or from a chromosomal translocations driving overexpression or producing a mutant transcription factor. In other cases, the direct causative event of the aberrant transcriptional signature is unknown. Given their central role in cancer development, directly targeting transcription factors should be a propitious anti-tumor strategy. However, with the exception of the nuclear hormone receptor family of transcription factors, transcription factor oncoproteins have been largely refractory to conventional drug discovery approaches. While there have been advances in our ability to assess gene expression changes on a global scale, almost all existing approaches (e.g., microarrays, next generation sequencing) cannot be applied to large-scale screening endeavors due to cost and throughput limitations. Alternatively, the use of reporter systems and phenotypic endpoints (e.g., viability) has been challenged by false-positives. Recognizing these shortcomings, we developed an assay approach that allows interrogation of complex gene expression signatures in high-throughput format. Gene Expression-based High-throughput Screening (GE-HTS) allows for the assessment of expression of hundreds of endogenous genes in 384-well format, overcoming some of the challenges that are inherent in conventional target- and phenotype-based screening. We have used GE-HTS in small-molecule library screening endeavors to identify compounds that induce differentiation signatures in different cancer types in the absence of a known target, as well as alter the transcriptional activity of aberrant, oncogenic transcription factors. These compounds have served as leads for clinical trial development as well as tool compounds to further dissect biological mechanisms of disease pathogenesis.

Citation Format: Kimberly Stegmaier. A genomics approach to discover small-molecule perturbagens of cancer cells [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA18.
Abstract IA2: Accelerating natural product discovery with multivariate image-based screening
Authors: Lokey Scott M.
Published: August 2014

Multiparameter phenotypic profiling has emerged as a powerful tool for characterizing small molecules and their effects on complex biological systems. In particular, the union of high-throughput screening technologies with automated microscopy and image processing has enabled the development of multiparameter image-based profiling techniques (also called “cytological profiling”), in which cells are imaged in multiwell plate format using automated fluorescence microscopy and the resulting images are quantified in terms of various descriptors, or “features.” Rather than focusing on a specific phenotype or biological endpoint, CP strategies employ multiple cytological probes that are selected to cover a wide range of biological pathways. Although CP has been used successfully to classify diverse bioactive compounds, its application in the area of natural products (NP) discovery has been limited. Here we describe the use of cytological profiling to discover natural products with novel mechanisms of action (MOAs). The goal of this project is to invert the NP discovery process from the traditional approach, where compound identification and function are the final steps in the discovery process, to a new paradigm where identities and functions of active constituents are determined directly from primary screening data and lead compounds are selected based on chemical and biological novelty prior to isolation and full structural characterization. Futhermore, the integration of CP fingerprints with metabolomics data allows us to rapidly associate compounds with phenotypes and prioritize unique chemistries for follow up.

Citation Format: Scott M. Lokey. Accelerating natural product discovery with multivariate image-based screening [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA2.
Abstract IA4: Designing biological systems to report on disease
Authors: Silver Pamela A.
Published: August 2014

Biology presents us with an array of design principles. From studies of both simple and more complex systems, we understand some of the fundamentals of how nature works and what goes wrong in the disease state. We are interested in using the foundations of biology to engineer cells in a logical and predictable way to perform certain functions with relevance to therapeutics and diagnostics. By necessity, the predictable engineering of biology requires knowledge of quantitative behavior of individual cells and communities and the ability to construct reliable models. By building and analyzing synthetic systems, we learn more about the fundamentals of biological design as well as engineer useful living devices with myriad applications. For example, we are interested in building cells that can perform specific tasks, such as remembering past events and thus acting as a biological computer. In particular, we have built genetic circuits whereby cells can ‘remember’ stimuli for many generations including DNA damage and hypoxia. By characterizing these ‘memory’ cells, we can identify key genes that may act as therapeutic targets and explanations for persistence of a subset of cells in tumors.

Citation Format: Pamela A. Silver. Designing biological systems to report on disease [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA4.
Abstract IA7: Functional genomics to identify cancer targets and resistance
Authors: Hahn William C.
Published: August 2014

Recent advances in genomics now make it possible to consider enumerating all of the genetic lesions in specific cancers. While these approaches will yield critical information regarding the identify, number, and types of alterations found in human tumors, a complementary approach to decipher the molecular basis of malignant transformation depends upon the application of genome scale tools to annotate the function of genes involved in cancer initiation and progression. Over the past several years, we have developed genome scale RNAi libraries and open reading frame expression libraries that permit a systematic evaluation of genes involved in cancer initiation and maintenance. Using these libraries, we have now performed screens in a panel of human cancer cell lines to systematically identify cancer vulnerabilities. By combining these functional approaches with information derived from mapping the structural abnormalities present in cancer genomes, we have identified several new oncogenes that contribute to cancer development. In pilot studies, we have identified several genes that act as synthetic lethal partners to known oncogenes or mediate resistance to targeted therapies. In recent work, we have expanded the scale of these experiments to genome scale in more than 100 cell lines, which has permitted greatly expanded and deeper investigation into genes that program the malignant state. Together, these studies suggest that combining forward and reverse genetic approaches with information derived from the cancer genome characterization projects will yield a comprehensive list of cancer vulnerabilities and establish a general approach for the rational identification of oncogenic and co-dependent pathways in cancer.

Citation Format: William C. Hahn. Functional genomics to identify cancer targets and resistance [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA7.
Abstract IA8: Genetic approaches to cancer
Authors: Solimini Nicole L. , Bredemeyer Andrea L. , Li Mamie Z. , Beroukhim Rameen , Meyerson Matthew , Elledge Stephen J. , Pavlova Natalya N. , Xu Qikai , Mermel Craig H. , Liang Anthony C. , Schlabach Michael R. , Luo Ji , Burrows Anna E. , Anselmo Anthony N.
Published: August 2014

Breast cancer is a collection of diseases with distinct clinical behaviors and underlying genetic causes. We have searched genetically for genes that have cancer relevant phenotypes including genes that alter cellular proliferation, cellular transformation, cell survival, cellular senescence, and genes that are essential for the proliferation of cancer cells. We have approached this by the generation of libraries of shRNAs for loss of function experiments and libraries of ORFs for gain of function experiments. We will discuss these technologies and how they can be applied to the functional dissection of genes important for breast cancer.

Citation Format: Nicole L. Solimini, Andrea L. Bredemeyer, Mamie Z. Li, Rameen Beroukhim, Matthew Meyerson, Stephen J. Elledge, Natalya N. Pavlova, Qikai Xu, Craig H. Mermel, Anthony C. Liang, Michael R. Schlabach, Ji Luo, Anna E. Burrows, Anthony N. Anselmo. Genetic approaches to cancer [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA8.
Abstract PR2: A systems biology approach to elucidating the consequences of complex ternary interactions of heparin, FGF ligands, and FGF receptor on downstream signaling in NSCLC cells
Authors: Chai Diana H. , Kim Jaeyeon , Vollmer Jannik , Radivojevic Andrijana , Kanodia Jitendra , Muda Marco , Schoeberl Birgit
Published: August 2014

Autocrine/paracrine FGF signaling has been implicated in non-small cell lung cancer (NSCLC) development and progression. In multiple NSCLC cell lines, a switch from FGFR2-IIIb expressed in lung epithelial cells to FGFR1-IIIc and FGFR2-IIIc, results in autocrine response to FGF2 and FGF9 ligands also expressed by these cell lines. FGF2 and FGFR1 expression have also been detected in patient samples and shown to correlate with short survival times. The FGF signaling complex involves a ternary interaction of FGF ligand, receptor, and heparin sulfate glycosaminoglycans (HSGAGs). HSGAGs bind directly to both ligand and receptor, and can serve both to stabilize the receptor-ligand complex and to sequester autocrine/paracrine ligands, increasing local concentrations. A systems approach combining experiment and modeling was used to understand the complex interplay of these components and their implications on cell signaling and behavior.

We focused on the signaling behavior of NSCLC cell line NCI-H1703, which predominantly expressed FGFR1. We interrogated pathway dynamics with both FGF2 and FGF9 ligands and found varying Erk1/2 activation kinetics. Using a model encompassing the ternary complex formation in the cellular membrane, ligand-mediated receptor dimerization and phosphorylation, and subsequent kinase cascade to activate Erk1/2, we were able to identify potential mechanisms driving these differences. Additional perturbations of extracellular interactions and intracellular signaling were able to support these hypotheses. These results highlight the role of the extracellular interactions between ligand, receptor, and HSGAGs in controlling downstream behavior.

This proffered talk is also presented as Poster A5.

Citation Format: Diana H. Chai, Jaeyeon Kim, Jannik Vollmer, Andrijana Radivojevic, Jitendra Kanodia, Marco Muda, Birgit Schoeberl. A systems biology approach to elucidating the consequences of complex ternary interactions of heparin, FGF ligands, and FGF receptor on downstream signaling in NSCLC cells [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR2.
Abstract PR5: The receptor tyrosine kinase layer of breast cancer cell lines is predictive of the response to therapeutic drugs
Authors: Niepel Mario , Hafner Marc , Pace Emily , Schoeberl Birgit , Sorger Peter K.
Published: August 2014

Currently, clinicians use the levels of the hormone receptors for estrogen (ER) and progesterone (PR) and amplifications of the ErbB2 receptor tyrosine kinase (RTK) to distinguish three groups of breast cancers and guide the choice of therapeutic treatments. In this work we show that a limited number of measurements characterizing breast cancer cell lines at the level of RTKs can be used to predict cell line sensitivity to therapeutic inhibitors.

We chose a panel of approximately 40 breast cancer cell lines, treated them with 22 different growth factors and cytokines at a saturating and subsaturating dose for 10, 30, and 90 min and measured the phosphorylation of key kinases downstream of the receptors. In addition, we measured the expression and phosphorylation levels of approximately 20 RTKs under serum starvation conditions. We used the measurements to predict the GI50 values of the cell lines in response to over 70 therapeutic inhibitors by partial least square regression. We found that our measurements are sufficient to predict the response to about half of the drugs studied. The majority of drugs we are able to predict target RTKs directly or kinases immediately downstream of the receptors. In some cases we are able to predict the response to drugs that target processes seemingly unrelated to our measurements. We are currently exploring the data to uncover what drives sensitivity and resistance to drugs, gain mechanistic insight in the action of cancer therapeutics, and find predictors of drug response that may be useful in a clinical setting.

Our results suggest that a carefully selected set of measurements might be sufficient to classify responsiveness of breast cancers to a number of cancer drugs currently used in the clinic. This is particularly relevant in the case of cancers like triple-negative breast cancers for which choosing effective treatment has proven difficult.

This proffered talk is also presented as Poster A17.This proffered talk is also presented as Poster A17.

Citation Format: Mario Niepel, Marc Hafner, Emily Pace, Birgit Schoeberl, Peter K. Sorger. The receptor tyrosine kinase layer of breast cancer cell lines is predictive of the response to therapeutic drugs [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR5.
Abstract PR6: A cooperative molecular response to combined mTOR/HDAC inhibition revealed by transcriptional co-expression analysis
Authors: Simmons John Kyle , Mock Beverly A. , Michalowski Aleksandra , Patel Jyoti , Wei Bih-Rong , Simpson R. Mark , Kuehl W. Michael , Zhang Shuling , Zhang Ke , Landgren Ola
Published: August 2014

Identification of biologically relevant molecular targets responding cooperatively to drug combinations is challenging, yet potentially useful in predicting clinical outcomes. We found that combining sirolimus (rapamycin), an inhibitor of mechanistic target of rapamycin (mTOR), with entinostat (MS-275), a selective class I histone deacytlase (HDAC) inhibitor, was synergistic in controlling 90% of tested cell lines derived from B cell malignancies, including multiple myeloma, mantle cell lymphoma, and murine plasmacytoma, in vitro, and effective in limiting xenograft growth in vivo. To understand the transcriptional underpinnings of the drug synergy, weighted gene co-expression analysis (WGCNA) was adapted to analyze gene expression profile data from cells treated with sirolimus and entinostat individually and in combination. WGCNA delineated the contribution of each inhibitor to the overall gene expression change of the combination by considering not only measures of fold-change and significance testing, but also the degree of gene expression interconnectedness. A co-expression network consisting of five gene modules was defined, where each module represents a unique transcriptional effect of the drug combination. In the next phase of analysis, each gene module was individually tested for functional and clinical enrichment. The module containing genes cooperatively affected by both compounds was highly enriched (p<0.001) for genes involved in cell cycle, immune recognition, and DNA damage/repair, which we have validated. Gene set enrichment analysis of each drug-induced gene expression module demonstrated that genes of all five modules were significantly enriched when healthy donors were compared to MM patients. Finally, interrogation of the cooperative drug signature in patient GEP datasets with survival annotation found it predictive of increased survival (p<0.01), thus linking the drug combination-induced transcriptional changes to predictions for enhanced survival. Thus, systems-level genomic approaches identified markers and a gene signature associated with drug combination activity, disease specificity, and clinical potential.

This proffered talk is also presented as Poster A16.

Citation Format: John Kyle Simmons, Beverly A. Mock, Aleksandra Michalowski, Jyoti Patel, Bih-Rong Wei, R. Mark Simpson, W. Michael Kuehl, Shuling Zhang, Ke Zhang, Ola Landgren. Sorger. A cooperative molecular response to combined mTOR/HDAC inhibition revealed by transcriptional co-expression analysis [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR6.
Abstract PR7: Visualizing the dynamic and heterogeneous responses of single cells to inhibitors of the growth factor signaling network
Authors: Albeck John , Hung Yin P. , Leya Gregory , Yellen Gary , Mills Gordon , Brugge Joan
Published: August 2014

The growth factor signaling network, including the Akt, ERK, mTOR and other pathways, is deregulated in many diseases and is a prominent target for therapeutic inhibitors. The effectiveness of these inhibitors is limited by the existence of homeostatic feedback loops that act to restore signaling and attenuate the effects of inhibition. To obtain the single-cell data necessary to fully characterize these rapid and heterogeneous responses, we developed a library of mammary epithelial cells stably expressing over 90 fluorescent protein-based reporters. This library comprises reporters for: cellular processes including cell death, cell cycle, protein translation, and metabolism; kinases including ERK, Akt and AMPK; and microRNAs involved in the regulation of cellular differentiation and stress response. Using high-throughput live-cell microscopy and computational image analysis, we monitored the responses of these pathways to inhibitors of EGFR, ErbB2, PI3K, mTOR, MEK, Raf, and Bcl-2. This analysis revealed unexpectedly dynamic fluctuations in key pathways including ERK, Akt, and glycolysis. In one example, inhibition of EGFR transformed constitutive ERK activity into intermittent bursts of activity ranging in duration from 20-90 minutes with high cell-to-cell variability. Characterization of ERK activity pulses revealed that their frequency depended on the level of EGF receptor activity and that their duration was essential for controlling the commitment to cell proliferation. In sharp contrast, inhibition of MEK altered the amplitude, rather than the frequency, of ERK activity. Using these live-cell measurements in combination with high content immunofluorescence, we constructed a computational model of feedback loops controlling ERK activity pulses. Quantitative mapping of ERK output to proliferation rate revealed a distinct and exquisitely sensitive threshold of ERK output required for proliferation. Potential strategies for reducing ERK output below this threshold and effectively blocking proliferation include dual inhibition of upstream regulators or intermittent high-dose inhibition. Single-cell quantitative analysis of inhibitor responses is now being extended to other pathways to identify signaling dynamics and information transfer properties that enable effective therapeutic targeting of the network.

This proffered talk is also presented as Poster A19.

Citation Format: John Albeck, Yin P. Hung, Gregory Leya, Gary Yellen, Gordon Mills, Joan Brugge. Visualizing the dynamic and heterogeneous responses of single cells to inhibitors of the growth factor signaling network [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR7.
Abstract A01: Long noncoding RNA H19 regulates growth factor signaling in breast cancer cells
Authors: Vennin Constance , Dhamani Fatima , Spruyt Nathalie , Adriaenssens Eric
Published: August 2014

H19 is one of the earliest identified, and the most studied, long noncoding RNAs. H19 gene is submitted to genomic imprinting and expressed only from the maternal allele and has no protein associated to its transcription. It has been proposed that H19 RNA function as a riboregulator. H19 is essential for development regulation but is also associated with carcinogenesis in many organs. However, biological functions and regulatory mechanisms of this conserved non coding RNA remain largely undecipher. Previously, we have shown that H19 is overexpressed in 70% of human breast cancers. In addition, its over-expression promotes cells invasion and angiogenesis. H19, positively regulated by E2F1, promotes cell cycle progression and G1/S transition. Altogether, these data support oncogenic function in breast tumor genesis of H19.

Recently, H19 has been showed to be a microRNA precursor of miR-675-5p and miR-675-3p. MicroRNAs are small non-coding RNA that regulate expression of up to 60% of genes. However, miR-675 targets have not yet been identified in breast cancer cells.

H19 gene expression is positively regulated by several growth factors, in peculiar hepatocyte growth factor / scatter factor (HGF/SF). HGF/SF stimulates proliferation of epithelial cells and increases both their motility and morphogenesis.

In the present study, in order to explain these phenotypes, we have searched for miR-675 targets in breast cancer cells. We demonstrate that H19, through its microRNA miR-675-5p, regulates negatively the expression of ubiquitin ligase E3 proteins: c-Cbl and Cbl-b. Both these proteins are involved in tyrosine kinase receptor degradation. In all breast cancer cells tested, c-Cbl and Cbl-b expression was significantly decreased after H19 or miR-675 over-expression. This downregulation promotes stability of growth factor receptors (EGFR, c-Met) that sustains and amplifies activation of downstream signaling pathways (Akt, MAP-kinase). Furthermore, we have shown that H19 overexpression increases breast cancer cells migration and invasion. Our data demonstrate that H19 gene overexpression increases HGF/SF receptor signaling as well as associated phenotypes. Our work propose a mechanism of action of H19 in breast cancer in increasing cell invasion and metastasis in this organ. H19 could also be involved in the mechanism of tumor resistance to treatment by increasing paracrine phenomena.

Citation Format: Constance Vennin, Fatima Dhamani, Nathalie Spruyt, Eric Adriaenssens. Long noncoding RNA H19 regulates growth factor signaling in breast cancer cells. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr A01.
Abstract A34: A regulatory role of beta-PIX in epidermal growth factor-induced cancer cell migration
Authors: Kuo Jean-Cheng
Published: August 2014

Expression of epidermal growth factor receptor (EGFR) in non–small cell lung cancer (NSCLC) tumors correlates with poor prognosis. EGFR signaling is Src dependent. Activation of EGFR leads to cycles of membrane protrusion, cell adhesion, contraction, and retraction, therefore promoting cell migration. Here, we show a novel role of beta-PIX (Pak-interactive exchange factor) in EGFR-mediated NSCLC cell migration. EGFR signals through Src, which phosphorylates beta-PIX sequentially at two specific tyrosine residues, 442 and 595. Phosphorylation of beta-PIX at tyrosine 442 leads to activation of small GTPase Rac1, which promotes membrane protrusion and cell adhesion assembly around 5 min after EGF stimulation. After another 20 minutes, tyrosine 442 is dephosphorylated, while tyrosine 595 of beta-PIX is phosphorylated. Phosphorylation of tyrosine 595 results in activation of small GTPase RhoA, contraction generation, adhesion disassembly, and cell retraction. These data suggest that the phosphorylation-dephosphorylation cycle of beta-PIX at tyrosine 442 and 595 serves as a regulatory signal downstream of EGFR to control migration and invasion of NSCLC cells.

Note: This abstract was not presented at the conference.

Citation Format: Jean-Cheng Kuo. A regulatory role of beta-PIX in epidermal growth factor-induced cancer cell migration. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr A34.
Abstract A41: Inhibition of Lkb1 in cultured embryonic pancreas destabilizes tissue architecture to generate precancerous-like lesions
Authors: Lo Bryan , Viotti Manuel , Strasser Geraldine , Mellman Ira
Published: August 2014

The tumor suppressor Lkb1 is a regulator of cellular energy, proliferation, and polarity, yet the mechanism by which it controls tissue morphogenesis or cancer remains poorly defined. By culturing embryonic tissues from mice harboring a mutant Lkb1 that can be rapidly inhibited, we have previously shown that acute loss of Lkb1 results in destabilized tissue architecture and the formation of highly dynamic pancreatic cysts (Lo et al, JCB 2012). Remarkably, the pancreatic cysts evolve within a few days into precancerous-like lesions that we now demonstrate to have a transcriptional profile that is strikingly similar to those reported for mouse and human PanINs (Pancreatic Intraepithelial Neoplasias). Utilizing fluorescence activated cell sorting, we have begun to track gene expression signatures associated with canonical signaling pathways in both single cells and subsets of cells from the embryonic explants. Since our experimental system offers precise temporal control and accessibility to manipulation within a tissue context, we are able to gain unprecedented insight into the earliest events in pancreatic oncogenesis.

Citation Format: Bryan Lo, Manuel Viotti, Geraldine Strasser, Ira Mellman. Inhibition of Lkb1 in cultured embryonic pancreas destabilizes tissue architecture to generate precancerous-like lesions. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr A41.