bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract A15: High-Content screen for inhibitors of cell migration in cancer metastasis using adenoviral knock-down
Authors: de Pril Remko , Lekkerkerker Annemarie , van Steenhoven Desire , Maghrani Ilhem , Perera Tim , Arts Janine , Fischer David , Janssen Richard 
Published: August 2014

Abstract
Enhanced cell migration is a hallmark of metastatic cancer cells. The propensity of cancer cells to close an open wound in a cell monolayer is thought to predict this ability. Using our adenoviral shRNA knockdown library we have established a high-throughput wound healing assay to identify novel genes involved in cell migration. A 96-pin tool was designed to apply a constant mechanical scratch-wound in the cellular monolayer. We used transmitted light imaging for segmentation and quantification of the scratch wound that remained open.
Genes whose knockdown inhibit cell migration can be identified by their effect on the open wound. We demonstrated that two knockdown constructs targeting a known player in motility, CXCR4, inhibit wound healing, thereby validating our approach. Using this wound healing assay we have identified a number of novel genes associated with cancer cell motility. These targets have consecutively been validated for their role in 3-D invasion using Boyden chambers. As our adenoviral knockdown libraries focus on druggable targets, these validated targets can quickly be employed to generate small-molecule compounds or antibody therapeutics targeting cancer metastasis.
Citation Format: Remko de Pril, Annemarie Lekkerkerker, Desire van Steenhoven, Ilhem Maghrani, Tim Perera, Janine Arts, David Fischer, Richard Janssen. High-Content screen for inhibitors of cell migration in cancer metastasis using adenoviral knock-down [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 A15.
Abstract A20: Molecular Detection of Prostate-Specific Membrane Antigen in Canine Prostate Carcinoma Cells
Authors: Wu Lisa Y. , Liu Tiancheng , Vanwie Bernard , Davis William C. , Berkman Clifford E. 
Published: August 2014

Abstract
Apart from the man, the dog develops prostate cancer spontaneously. Although the diseases in both species have several clinical aspects in common, not much is known about the expression of markers in the canine prostate cancer due to the lack of study in canine prostate cancer research. Therefore, the vast majority of canine prostate cancers at the time of diagnosis are end-staged. Numerous prostate cancer cell lines have been developed, but few cell lines develop bone metastases and no cell lines have been reported to cause brain metastases except the Ace-1 and the Leo canine prostate cancer cell lines. Prostate-specific membrane antigen (PSMA), which is known as a prostate cancer biomarker in humans, its usefulness in canine specimens has not been examined fully in these cell lines. Although there has been a considerable effort toward the development of PSMA-targeted diagnostic and therapeutic technologies for dogs, methods for detecting circulating and invasive prostate tumor cells currently remain limited. Previously, we developed a prostate circulating tumor cell (PCTC) detection method by a fluorescent PSMA inhibitor. The focus of the study is to evaluate PSMA expression on the Ace-1 and Leo cell lines by fluorescent conjugated PSMA inhibitor in flow cytometry. It is expected that the results will enable the development of detecting PSMA expressing canine cells in circulation for prognosis and diagnosis of canine prostate cancer.
Citation Format: Lisa Y. Wu, Tiancheng Liu, Bernard Vanwie, William C. Davis, Clifford E. Berkman. Molecular Detection of Prostate-Specific Membrane Antigen in Canine Prostate Carcinoma 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 A20.
Abstract A21: High-throughput small molecule screening of genetically diverse glioblastoma stem cells
Authors: Strohbehn Garth W. , Zhou Jiangbing , Fu Michael , Patel Toral R. , Piepmeier Joseph M. , Saltzman W. Mark 
Published: August 2014

Abstract
Survival statistics for glioblastoma multiforme (GBM) have remained static despite years of research. Mounting evidence suggests that glioblastoma stem cells (GSCs) are a primary cause of GBM growth, spread, vascularity, and chemotherapeutic resistance. Increasing survival, therefore, demands a therapeutic strategy with efficacy against GSCs. To address this, we have conducted a high-throughput screen of over 3,000 small molecule compounds for activity against three independently derived GSC lines that vary in their expression of TCGA subtype-related genes. Our fluorescence-based assay is sensitive, reliable, and largely free of row- and column-based systematic errors. We identify novel compounds that impair the viability of all three of these genetically diverse GSC lines but have comparably limited toxicity against a normal human glial cell line. Many of these compounds are small and lipophilic, as well, making them ideal candidates for follow-up in vivo evaluation either through intravenous delivery or through encapsulation in polymeric nanoparticles.
Citation Format: Garth W. Strohbehn, Jiangbing Zhou, Michael Fu, Toral R. Patel, Joseph M. Piepmeier, W. Mark Saltzman. High-throughput small molecule screening of genetically diverse glioblastoma stem 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 A21.
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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&gt;&gt;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&gt;&gt;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

Abstract
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.