bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract PR08: GC skew defines distinct RNA polymerase pause sites in CpG island promoters
Authors: Bell Joshua SK , Kellner Wendy A. , Vertino Paula M. 
Published: May 2016

Abstract
Promoter-proximal pausing of RNA Pol II (Pol II) is a near universal feature of human genes and plays a central role in governing levels of transcription and modulating rapid response to stimuli. Here we show that at CpG island (CGI)- associated promoters, Pol II encounters an additional barrier to elongation distinct from the promoter-proximal pause that occurs at the downstream boundary of the CGI domain. For most CGI associated promoters, Pol II exhibits a dominant pause at either the promoter-proximal or this distal site that correlates, both in position and in intensity, with local regions of high GC skew, a sequence feature known to promote the formation of unique secondary structures. Indeed, we find that distally paused genes manifest longer or more stable R-loops, a structure suggested to protect CGI domains from DNA methylation. Interestingly, the link between GC-skew and Pol II pausing is conserved in Drosophila. Upon signal-induced gene activation, long-range enhancer contacts at the dominant pause site are selectively enhanced, suggesting a new role for enhancers at CGI boundaries. Consistent with this idea, we find a correlation between enrichment of the cohesin complex, important for DNA looping, and the position of the dominant pause site. These findings unearth a novel transcriptional regulatory step at CGI-associated genes that is dictated by the underlying DNA sequenceand linked to the integrity of the CGI domain.
Citation Format: Joshua SK Bell, Wendy A. Kellner, Paula M. Vertino. GC skew defines distinct RNA polymerase pause sites in CpG island promoters. [abstract]. In: Proceedings of the AACR Special Conference on Chromatin and Epigenetics in Cancer; Sep 24-27, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2016;76(2 Suppl):Abstract nr PR08.
Abstract PR12: MED12 methylation by CARM1 sensitizes human breast cancer cells to chemotherapy drugs
Authors: Lu Wang , Zeng Hao , Wang Qiang , Zhao Zibo , Boyer Thomas G. , Bian Xiuwu , Xu Wei 
Published: May 2016

Abstract
Chemotherapy continues to be an important treatment to reduce the risk of metastatic breast cancer recurrence. However, many tumors relapse due to the development of multidrug resistance, the mechanisms of which remain poorly understood. Therefore, there is a pressing need to elucidate mechanisms of resistance and discover a sensitive biomarker that could predict patient response to chemotherapeutic drugs. We discovered that chemosensitivity can be predicted by methylation of a mediator of RNA polymerase II transcription subunit 12 (MED12) by coactivator associated arginine methyltransferase 1 (CARM1). MED12 is frequently mutated in human cancers, and loss of MED12 has been shown to induce drug resistance through activation of TGF-βR signaling. We showed that MED12 is a novel substrate of CARM1. Not only are the expression levels of CARM1 and MED12 positively correlated but their high expression predicts better prognosis in human breast cancers after chemotherapy. MED12 was primarily methylated at R1862 by CARM1, and mutation of this site in cell lines resulted in resistance to chemotherapy drugs (e.g. 5-FU). A change in chemosensitivity by altering the methylation status of a single protein in breast cancer cells is unprecedented. Mechanistically, we showed that the methylation-dependent drug response mechanism is distinct from activation of TGF-βR signaling. Further, we found that methylated MED12 potently suppresses p21/WAF1 transcription. Cells defective in MED12 methylation have up-regulated p21 protein, which correlates with poor prognosis in breast cancer patients treated with chemotherapy. Collectively this study identifies MED12-methylation as a sensor for predicting response to commonly used chemo-drugs in human cancers.
Citation Format: Wang Lu, Hao Zeng, Qiang Wang, Zibo Zhao, Thomas G. Boyer, Xiuwu Bian, Wei Xu. MED12 methylation by CARM1 sensitizes human breast cancer cells to chemotherapy drugs. [abstract]. In: Proceedings of the AACR Special Conference on Chromatin and Epigenetics in Cancer; Sep 24-27, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2016;76(2 Suppl):Abstract nr PR12.
Abstract B1-05: R2: Accessible web-based genomics analysis and visualization platform for biomedical researchers
Authors: Koster Jan , Molenaar Jan J. , Versteeg Rogier 
Published: May 2016

Abstract
In this era of explosive high throughput (HT) genomics data generation, there is a growing need for accessible software solutions that can help unlock biological/clinical characteristics from such data. With the biomedical researcher (with limited or no bioinformatics skills) in mind, we developed a comprehensive web-based system called R2 (http://r2.amc.nl). R2 aids in the analysis and visualization of private/shielded as well as public high throughput data and their associated annotated features.
The R2 platform consists of a database storing both publicly accessible as well as shielded datasets with unified gene annotation, supplemented with a large suite of tools that can be used on these data, and their associated annotation. As such the user experiences the same look & feel throughout the mining process.
In the public section, R2 hosts over 60,000 HT samples. Next to gene expression (microarray and RNA-seq), the platform is also being employed in the integration, analysis and visualization of other data types, such as aCGH, SNP, ChIP, methylation, miRNA, and NGS whole genome sequencing information.
R2 contains an expanding set of interactive analyses which are heavily inter-connected, allowing users to quickly hop from one view (representation of the data) to another. Analyses include, correlation, differential expression, gene sets, gene ontology, transcription factor binding sites, PCA, kmeans, Kaplan Meier scans, signature creation etc. Visualizations include, various gene oriented plots, heatmaps, circos, embedded genome browser, Venn, etc.
Many parts of the R2 platform are publicly accessible through the http://r2.amc.nl portal. The R2 gene expression analysis tools have thus far been used in more than 180 peer-reviewed scientific publications including journals as Nature, Nature Genetics and Cell. R2 also supports restricted / shielded use and is used in many (inter)national collaborative efforts involving unpublished datasets. The webservers have been serving over 900.000 pages over the past 12 months (Nov 2014).
Citation Format: Jan Koster, Jan J. Molenaar, Rogier Versteeg. R2: Accessible web-based genomics analysis and visualization platform for biomedical researchers. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-05.
Abstract B1-20: Gene regulation by transcription factors and microRNAs in ovarian cancer
Authors: Kuijjer Marieke Lydia , Glass Kimberly , Quackenbush John 
Published: May 2016

Abstract
Conventional methods to analyze genomic data do not make use of the connectivity between different data types, such as transcriptional regulation and gene expression, thereby often failing to identify the cellular processes that are unique to cancer and cancer subtypes. An example of this are the four recently characterized high-grade serous ovarian cancer transcriptomic subtypes – differentiated, immunoreactive, mesenchymal, and proliferative ovarian cancer. These subtypes have not been associated with significant differences in survival, and their discovery has not lead to the identification of subtype-specific therapies. Uncovering the regulatory mechanisms mediating differences in expression between these subtypes may identify new therapeutic interventions, and ultimately help cancer patients.
We modeled regulatory networks of the four ovarian cancer subtypes using PANDA, a network inference approach that uses genomic data to search for an optimal network by modeling information flow between regulators and target genes. Because not only transcription factors, but also microRNAs play an important role in gene regulation, we modified the PANDA algorithm to account for the regulatory effects of microRNAs in addition to transcription factors (miR-PANDA, in preparation). We compared the networks defining gene regulation in each subtype using different network comparison metrics. We observed a very striking pattern in out-degree differences that suggests transcription factors and microRNAs play a major role in driving the different subtypes. Using gene set enrichment analysis on in-degree differences of target genes, we identified several cancer-related pathways that are highly targeted in specific subtypes, such as regulation of Notch signaling by microRNAs in the immunoreactive subtype, and regulation of Wnt signaling by transcription factors in the proliferative subtype. These results may point to new therapeutic interventions and advance personalized treatments for ovarian cancer patients.
Citation Format: Marieke Lydia Kuijjer, Kimberly Glass, John Quackenbush. Gene regulation by transcription factors and microRNAs in ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-20.
Abstract B1-33: Network analyses identify hidden regulators of TGFa shedding
Authors: Wilson Jennifer L. , Fraenkel Ernest , Lauffenburger Douglas A. , Herrlich Andreas 
Published: May 2016

Abstract
It is well known that components of the ADAM17/EGFR ligand axis, ADAM17, TGFa, and AR, are upregulated in aggressive, metastatic forms of triple negative breast cancer (TNBC). Furthermore, we know that activation of alternate receptor-tyrosine kinase (RTK) ligands can decrease sensitivity to kinase inhibitor treatments (such as the EGFR-targeting erlotinib) and that locally-shed growth ligands are one source of RTK reactivation1. Unfortunately, directly targeting ADAM17 activity is a poor therapeutic option due to non-specific effects. It is currently unknown what regulators affect ligand shedding, the extent of specificity in this regulation and what connections, if any, exist between ligand shedding regulation and RTK re-activation, cell growth and metastasis in TNBC. We hypothesize that ligand shedding regulation is an important component of altered growth factor pathway signaling and that targets within these pathways contribute to the reactivation of growth factor pathways and chemotherapy resistance in TNBC. Here we use the Prize-Collecting Steiner Forest (PCSF), an interactome-based network construction tool, to identify candidate regulators of ectodomain shedding and leverage TNBC patient data to identify regulators with relevance to TNBC pathology.
Citation Format: Jennifer L. Wilson, Ernest Fraenkel, Douglas A. Lauffenburger, Andreas Herrlich. Network analyses identify hidden regulators of TGFa shedding. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-33.
Abstract B2-04: Time lapse to cancer: Defining the transition from polyp to colorectal cancer based on telomere metrics
Authors: Druliner Brooke R. , Johnson Ruth , Ruan Xiaoyang , Vanderboom Russell , Devine Donna Felmlee , Aletto Jill Washechek , Boardman Lisa A. 
Published: May 2016

Abstract
Despite advances in prevention and early detection strategies, colorectal cancer (CRC) remains the second leading cause of cancer death in the United States. The majority of CRC arises from adenomatous polyps. However, only 5% of all people who receive a colonoscopy will have a lesion determined to be at high risk for malignant transformation. Adenomas are primarily classified based on histology, size, degree of dysplasia and limited genetic mutation information. Further characterization of what contributes to or underlies the malignant transformation of polyps is currently lacking, but is essential to further understand the transition from polyp to cancer and factors that lead only a small portion of polyps to progress onto cancer.
Although telomere length is a recognized biomarker in multiple cancers, few studies have addressed the comprehensive role of telomeres in CRC progression. Telomere shortening is a fundamental feature of dividing cells related to the age of the cell and is implicated in carcinogenesis. Telomere length is not solely determined by attrition resulting from cell division, but also through telomere maintenance mechanisms (TMM), which are often exploited in malignant cells. In this study, we will measure the telomere profile (consisting of telomere length and TMM) in normal colon epithelium, polyps and the adjacent tumor trios and normal colon epithelium and cancer-free polyp pairs. Our aim is to determine which telomere features distinguish cancer adjacent polyps from cancer free polyps. This is an innovative approach for identifying the definable telomere-related properties that distinguish polyps with malignant potential that remain benign from those that transform to cancer and progress to invasive lesions. Further characterization of the molecular profile of polyps undergoing the transition to cancer that differentiate cancer free polyps has the potential to be utilized in designing optimal treatment options for patients with polyps that carry the risk of CRC.
Citation Format: Brooke R. Druliner, Ruth Johnson, Xiaoyang Ruan, Russell Vanderboom, Donna Felmlee Devine, Jill Washechek Aletto, Lisa A. Boardman. Time lapse to cancer: Defining the transition from polyp to colorectal cancer based on telomere metrics. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-04.
Abstract B2-34: Model guided understanding of synergistic combination therapies in the DNA damage response pathway
Authors: Raue Andreas , Alkan Ozan , Drummond Daryl , Schoeberl Birgit 
Published: May 2016

Abstract
Most commonly used anti-cancer therapies involve the systemic administration of anti-proliferative and DNA damaging agents. Deregulation of DNA damage response (DDR) pathways can cause resistance to DNA damaging therapies. Synergistic combination strategies of novel DDR pathway modulators promise to re-sensitize to and amplify currently used standard-of-care therapies.
Our goal is to gain mechanistic understanding of the DDR pathway by developing a predictive computational model using single cell microscopy phenotypic data and signaling data from a panel of cancer cell lines. We focus on synergistic and potentiating effects of drug combinations using standard-of-care drugs such as doxorubicin, gemcitabine and irinotecan, and DDR pathway modulators. Our computational model explains the mechanisms of synergistic or additive phenotype that are observed for various modulators and was validated using DDR signaling data.
The presented computational model rationalizes the design of novel combination therapies targeting the DDR pathway, includes heterogeneity of different cell lines and is an important step towards the design of a biomarker strategy.
Citation Format: Andreas Raue, Ozan Alkan, Daryl Drummond, Birgit Schoeberl. Model guided understanding of synergistic combination therapies in the DNA damage response pathway. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-34.
Abstract B2-35: Efficient exploration of multi-cancer networks by generalized covariance selection and interactive web content
Authors: Kling Teresia , Johansson Patrik , Sanchez Jose , Marinescu Voichita D. , Jornsten Rebecka , Nelander Sven 
Published: May 2016

Abstract
Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools for network construction and interpretation are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as the Cancer Genome Atlas (TCGA). Here, we describe a novel strategy to construct and analyze integrative network models heterogeneous data from multiple cancers. First, we introduce a generalization of sparse inverse covariance selection (SICS) designed to integrate genetic, epigenetic and transcriptional data from multiple cancers into a comparative network. The algorithm is shown to be statistically robust, effective at detecting direct pathway links in data from The Cancer Genome Atlas (TCGA), and uses a new strategy involving non-informative priors to balance different cancers and data types. Second, we propose to rationalize the interpretation of the derived networks by a new and publicly accessible tool (cancerlandscapes.org), in which derived models are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model of genetic, epigenetic and transcriptional data for eight TCGA cancers, using data from 3900 patients. The derived model rediscovered known mechanisms and contained interesting predictions. Possible applications include the prediction of regulatory relationships between genes in particular cancers, comparison of network modules in across multiple forms of cancer, and identification of drug targets in relation to network structure.
Citation Format: Teresia Kling, Patrik Johansson, Jose Sanchez, Voichita D. Marinescu, Rebecka Jornsten, Sven Nelander. Efficient exploration of multi-cancer networks by generalized covariance selection and interactive web content. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-35.
Abstract IA03: Towards the next clinical option: Experience from a precision cancer medicine trial
Authors: Rubin Mark A. 
Published: May 2016

Abstract
Understanding molecular mechanisms of response and resistance to anticancer therapies requires prospective patient follow-up and clinical and functional validation of both common and low frequency mutations. We describe an evidence-based precision medicine program designed to bring whole exome sequencing (WES) into clinical practice and illustrate how this can be utilized to identify novel predictive biomarkers associated with exceptional systemic response.
Metastatic and treatment-resistant cancer patients are prospectively enrolled for paired metastatic tumor and normal WES. Using a comprehensive computational pipeline, point mutations, indels and copy number alterations are detected. Mutations are categorized as Category I-III based on actionability and a report is generated and discussed in tumor board. Patients are followed prospectively for correlation of molecular information with clinical response and patient outcomes. A rapid response functional team follows on key findings to expand actionability based on the WES results.
In the first year, 154 tumor-normal pairs from 97 patients were sequenced, with an average coverage of 95X of over 21,000 genes and 16 somatic alterations detected on average per patient. In total, 16 mutations were Category I, 98 were Category II, and 1474 were Category III. Tumor purity ranged from 14 to near 100%. Among unexpected findings, a prostate cancer exceptional responder was identified that harbored a somatic hemizygous deletion of the DNA repair gene FANCA and likely loss of function of the second allele through germline missense variant. Follow-up experiments established that loss of FANCA function was associated with platinum hypersensitivity both in vitro and in patient-derived xenografts, thus providing biologic rationale and functional evidence for his extreme clinical response.
The establishment of a clinical program for whole exome sequencing of metastatic tumors with prospective follow-up of patients can help identify candidate predictive biomarkers of response.
Citation Format: Mark A. Rubin. Towards the next clinical option: Experience from a precision cancer medicine trial. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr IA03.
Abstract IA14: Genomic alterations dysregulate cancer genes by modulating microRNA activity
Authors: Chiu Hua-Sheng , Yang Xuerui , Califano Andrea , Sumazin Pavel 
Published: May 2016

Abstract
microRNAs play key roles in cancer etiology, and recent evidence suggests that targets of the same microRNA programs are stoichiometrically coupled via a competitive endogenous RNA (ceRNA) mechanism. Consequently, aberrant expression of multiple targets of the same microRNA program dysregulate coupled ceRNA- oncogenes and tumor suppressors.
We computationally inferred and experimentally validated that coordinated copy number and methylation alterations contribute to physiologically significant in-trans dysregulation of hundreds of coupled oncogenes and tumor suppressors in multiple tumor contexts. Both high-throughput perturbation assays and low-throughput mutational assays confirmed significant ceRNA-mediated regulation of cancer genes in eight tumor contexts, including ESR1 and APC in breast and colon cancer, respectively.
Our analysis infers roles for previously uncharacterized genomic alterations and it suggests that ceRNA-mediated interactions account for a substantial fraction of cancer's missing genomic variability.
Citation Format: Hua-Sheng Chiu, Xuerui Yang, Andrea Califano, Pavel Sumazin. Genomic alterations dysregulate cancer genes by modulating microRNA activity. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr IA14.
Abstract IA20: Post-transcriptional regulation of metastatic progression
Authors: Tavazoie Sohail F. 
Published: May 2016

Abstract
Post-transcriptional regulation represents an increasingly studied layer of gene expression control. In recent years, it has become increasingly evident that deregulation in post-transcriptional control mechanisms represents an important feature of the aggressive malignant phenotype. We have found that distinct cancers arising from various tissues such as the breast, skin, and the colon modulate unique tissue-specific sets of small non-coding RNAs (microRNAs) as they acquire a highly metastatic phenotype. We have used these microRNAs as molecule probes to better understand the molecular and cellular biology underlying metastatic progression. These studies have revealed surprising pathways and mechanisms utilized by cancer cells to colonize metastatic microenvironments. We find that while distinct tissues such as breast and melanoma might modulate distinct miRNAs and downstream target genes, the cellular phenotypes impacted by these pathways en route to metastatic colonization can be similar. Importantly, clinical association studies using human specimens support the roles for these miRNAs and their downstream effectors in metastatic progression. These basic studies into the molecular and cellular biology of metastatic progression have revealed key target genes whose pharmacological modulation in proof-of-concept pre-clinical studies have revealed robust therapeutic effects.
Citation Format: Sohail F. Tavazoie. Post-transcriptional regulation of metastatic progression. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr IA20.