bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract B26: MAPK-interacting kinase inhibition sensitizes glioblastoma and glioma stem cells to arsenic trioxide
Authors: Bell Jonathan B. , Eckerdt Frank , Arslan Ahmet Dirim , Iqbal Asneha , Alvarez Angel A. , Cheng Shi-Yuan , Nakano Ichiro , Platanias Leonidas C. 
Published: May 2016

Abstract
Glioblastoma (GBM) is the deadliest primary brain tumor with a median survival of around one year. Arsenic trioxide (ATO) is an emerging therapy for the treatment of GBM and other malignant brain tumors. The cytotoxic effects of ATO are mainly mediated by the production of reactive oxygen species and induction of cell death pathways. However, glioma stem cells in heterogeneous GBM tumors impart resistance by activation of survival pathways, thereby preventing therapeutic responses to cytotoxic agents such as ATO. We have previously shown that ATO responses in leukemia are antagonized by the MAPK-interacting kinases (MNKs), which activate protein translation and survival pathways including the eukaryotic translation initiation factor 4E (eIF4E) in response to ATO treatment. Yet, the role of MNK signaling in GBM and glioma stem cells and the potential of using MNK inhibitors to sensitize GBM to ATO has not been explored. In this study, we sought to determine the mechanisms by which MNK signaling regulates arsenic trioxide responses in GBM and glioma stem cells.
GBM cell lines were treated with ATO in the presence or absence of MNK inhibitors or siRNA against MNK isoforms. Western blots of treated samples were analyzed with antibodies against phosphorylated eIF4E, the key downstream effector of the MNKs. Following treatment with ATO and MNK inhibitors, proliferation rate and apoptosis were determined by WST-1 assay and Annexin V-FITC/PI staining. GBM cell lines were grown under stem cell conditions and subjected to qPCR and flow cytometry to monitor CD44 expression and aldehyde dehydrogenase (ALDH) activity, both markers of stemness. Patient-derived glioma stem cell lines displaying mesenchymal-like phenotype were treated with ATO and MNK inhibitors and analyzed by neurosphere formation assay.
Treatment of GBM cell lines with ATO resulted in MNK activation and induction of eIF4E phosphorylation in a MNK1-depedent manner. Furthermore, MNK inhibition sensitized GBM cells to the anti-proliferative and pro-apoptotic effects of ATO. Knockdown of MNK1 in GBM cell lines grown under stem cell conditions decreased neurosphere formation. Finally, pharmacological MNK inhibition sensitized mesenchymal-like glioma stem cells to ATO. Our results suggest ATO in combination with MNK inhibition might represent a new approach for the treatment of GBM, in particular the therapy-resistant glioma stem cell subpopulation.
Citation Format: Jonathan B. Bell, Frank Eckerdt, Ahmet Dirim Arslan, Asneha Iqbal, Angel A. Alvarez, Shi-Yuan Cheng, Ichiro Nakano, Leonidas C. Platanias. MAPK-interacting kinase inhibition sensitizes glioblastoma and glioma stem cells to arsenic trioxide. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr B26.
Abstract IA09: Imaging to guide genomics and epigenomics of glioma
Authors: Costello Joseph F. 
Published: May 2016

Abstract
Genomic analysis of cancer is typically conducted at a single time point and on a single piece of tumor tissue without knowledge of its original context within the heterogeneous tumor. Glioma tissue biopsies guided by distinct physiologic and metabolic imaging parameters can enrich for tumor regions with elevated levels of cycling cells, differences in blood vessels, and increased presence of hypoxic regions, and an increased probability of malignant transformation. An imaging guided approach to biopsy allows the tumor genomic and transcriptome evolution to be focused on malignant transformation. I will describe the use of novel quantitative imaging methods to guide biopsies to biologically distinct regions of brain tumors for targeted genomic, epigenomic and transcriptome analysis.
The clonal evolution of tumor cell populations can be reconstructed from patterns of genetic alterations. In contrast, tumor epigenetic states are reversible and sensitive to the tumor microenvironment, presumably precluding the use of epigenetics to discover the clonal and sub-clonal evolution of tumors. We recently used mutation patterns to learn how low grade brain tumors evolve over time, and also discovered that temozolomide treatment of LGG is associated with TMZ-induced hypermutation and malignant progression to GBM (BE Johnson et al, Science, 2014). I will present an update to these results, and our follow up analysis of the spatial and temporal dynamics of DNA methylation in this clinically and genetically characterized cohort and in imaging guided biopsies.
Citation Format: Joseph F. Costello. Imaging to guide genomics and epigenomics of glioma. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr IA09.
Abstract IA14: The unique genomic landscape of pediatric high-grade glioma
Authors: Larson Jon D. , Silveira Andre B. , Kasper Lawryn H. , Russell Helen R. , Qu Chunxu , McKinnon Peter J. , Baker Suzanne J. 
Published: May 2016

Abstract
Diffuse high-grade gliomas (HGGs) of childhood are a devastating spectrum of disease with no effective cures. The two-year survival for pediatric HGG ranges from 30 percent, for tumors arising in the cerebral cortex, to less than 10 percent for diffuse intrinsic pontine gliomas (DIPGs), which arise in the brainstem. Frequent recurrent somatic mutations in histone H3 distinguish the genetic drivers among pediatric and adult HGG. Mutually exclusive somatic heterozygous H3F3A or HIST1H3B mutations encoding a K27M variant of histone H3.3 or H3.1, respectively, are found in nearly 80 percent of DIPGs and 22 percent of non-brainstem HGG, where they occur predominantly in thalamic and other midline tumors. Strikingly, heterozygous H3F3A mutations encoding histone H3.3 G34R or G34V occur in approximately 14 percent of non-brainstem HGG, and are associated predominantly with cortical tumors arising in older children through young adulthood, suggesting a distinct developmental origin compared to the majority of tumors harboring K27M mutations. Recurrent mutations of the BMP receptor ACVR1/ALK2 have not been reported outside the brainstem, and are further restricted to the youngest DIPG patients, highlighting critical connections between development and gliomagenesis. Experiments to model the connections between oncogenic activity and developmental context will be discussed.
Citation Format: Jon D. Larson, Andre B. Silveira, Lawryn H. Kasper, Helen R. Russell, Chunxu Qu, Peter J. McKinnon, Suzanne J. Baker. The unique genomic landscape of pediatric high-grade glioma. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr IA14.
Abstract IA18: Epigenetic addiction in pediatric high-grade gliomas
Authors: Jabado Nada 
Published: May 2016

Abstract
A remarkably rapidly expanding body of literature points to the epigenome as a new previously unsuspected mechanism of oncogenesis and another “hallmark of cancer.” Indeed, in a large number of cancers, aberrant epigenetic states occur through different mechanisms including altered DNA methylation, covalent histone modification, the reading of these histone modifications by protein regulation modules, histone exchange, chromatin remodelers, or via the effects of non-coding RNAs. Although mutations are also found in canonical signaling pathway genes, we and others identified chromatin-associated proteins to be more commonly altered by somatic alterations than any other class of oncoprotein in several subgroups of childhood high-grade brain tumors. Furthermore, as these childhood malignancies carry fewer non-synonymous somatic mutations per case in contrast to most adult cancers, these mutations are likely drivers in these tumors. Herein, we will use as examples of this novel hallmark of oncogenesis high-grade astrocytomas, including glioblastoma, and a subgroup of embryonal tumors, embryonal tumor with multilayered rosettes (ETMR) to describe the novel molecular defects uncovered in these deadly tumors. We will further discuss evidence for their profound effects on the epigenome and their links to brain development. Importantly, the type, timing and spatial clustering of these molecular alterations provide a better understanding of the pathogenesis of the respective brain tumor they target as well as critical markers for therapy that will help refine pathological grading.The relative genetic simplicity of these tumors promises general insights into how mutations in the chromatin machinery modify downstream epigenetic signatures to drive transformation, and how to target this plastic genetic/epigenetic interface.
Citation Format: Nada Jabado. Epigenetic addiction in pediatric high-grade gliomas. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr IA18.
Abstract PR10: A DNA hypomethylation signature predicts novel antitumor activity of LSD1 inhibition in SCLC
Authors: Mohammad Helai , Kruger Ryan 
Published: May 2016

Abstract
Epigenetic dysregulation has emerged as an important mechanism in cancer. Alterations in epigenetic machinery have become a major focus for new targeted therapies. The current report describes the discovery and biological activity of a cyclopropylamine containing inhibitor of Lysine Demethylase 1 (LSD1), GSK2879552. This small molecule is a potent, selective, orally bioavailable, mechanism-based irreversible inhibitor of LSD1. A proliferation screen of cell lines representing a number of tumor types indicated that small cell lung carcinoma (SCLC) is sensitive to LSD1 inhibition. The subset of SCLC lines that undergo growth inhibition in response to GSK2879552 exhibit DNA hypomethylation of a signature set of probes suggesting this may be used as a predictive biomarker of activity. This targeted mechanism coupled with a novel predictive biomarker make LSD1 inhibition an exciting potential therapy for SCLC, a highly prevalent, rarely cured, tumor type representing approximately 15% of all lung cancers.
Citation Format: Helai Mohammad, Ryan Kruger. A DNA hypomethylation signature predicts novel antitumor activity of LSD1 inhibition in SCLC. [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 PR10.
Abstract B1-38: PARADIGM-SHIFT: Predicts the functional impact of ‘driver modules’ in multiple cancers using pathway impact analysis
Authors: Ng Sam , Benz Christopher , Haussler David , Stuart Joshua M. 
Published: May 2016

Abstract
The major mechanism by which cancer arises is through genomic alterations. These alterations can lead to changes in gene regulation, protein structure, and function. Individual tumors can contain hundreds to thousands of alterations. It is critical to distinguish alterations that have an important role defining the cancer – drivers – from alterations that are unimportant to the tumor – passengers. Driver genes can lead to significant changes in their pathways; however, alterations in a single gene may not be sufficient to explain all the pathway perturbations across patients. Additional alterations could range from DNA copy number changes, gene-fusions, or even lesser understood non-coding mutations. Identifying these ‘driver modules’ is essential for understanding cancer disease mechanisms, which can help guide treatment decisions as well as identify novel targets for treatment.
We have developed a functional impact prediction method called PARADIGM-SHIFT based on integrated pathway analysis to discriminate loss-of-function, neutral, and gain-of-function alterations. Utilizing the set of regulatory interactions annotated for a given gene, we can detect a shift in the downstream effects of an altered gene compared to what is expected from its upstream influences. Additionally, since these shifts in pathway signal can be detected for all samples, PARADIGM-SHIFT can be used to identify additional genomic alterations that lead to similar changes to the altered pathway to form ‘driver modules.’ Application of our method to the TCGA Pan-Cancer cohort identifies many genes with significant alterations that lead to loss- and gain- of function. PARADIGM-SHIFT then identifies several additional genomic alterations, including non-coding mutations variants, which are significantly implicated in these pathway changes. This analysis offers insight into the mechanism of non-coding mutations orthogonal to sequence-based methods by interpreting the pathway consequences of these variants.
Citation Format: Sam Ng, Christopher Benz, David Haussler, Joshua M. Stuart. PARADIGM-SHIFT: Predicts the functional impact of ‘driver modules’ in multiple cancers using pathway impact analysis. [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 B1-38.
Abstract B1-43: Cancer drug response networks built for comparative cancer pharmacogenomics identifies combination therapies for repositioning
Authors: Brubaker Douglas , Svenson Elena , Kai Smith , Monroe Maya , Ryu Christopher , Narla Goutham , Chance Mark R. , Bebek Gurkan 
Published: May 2016

Abstract
We present an integrative framework for classifying drug response: CAncer Drug Response nEtworks (CADREs). We built CADREs for drugs with differential sensitivity profiles in cancer cell lines by integrating baseline copy number, gene expression, and drug sensitivity data for the cell lines. The nodes in the network are drugs and the edges are weighted according to the number of shared copy number variations, differentially expressed genes, and dysregulated pathways present in sensitive cell lines at baseline. These baseline features were mapped into pathways to generate a Pathway CADRE, and were also integrated into a differential gene expression and copy number Feature CADRE. CADREs were built for breast, ovarian, and endometrial cancers individually and combined to assess shared and unique features of drug sensitivity. Analyzing CADRE clusters associated multiple gene features and pathways with sensitivity to frontline therapies used in combination in these cancers. We identified four clusters of breast cancer drugs whose effectiveness is driven by a shared core of pathways. Compounds that were used in combination in clinical trials tended to not share an edge or are completely disconnected in networks. Specifically, ten such drug pairs in our breast CADREs have been found to work in combination in breast cancer and an additional five have been used in combination in other cancers, representing opportunities for repositioning these combinations in breast cancer. Examining highly interconnected CADRE nodes gave us an understanding for compounds that might work best together.
Citation Format: Douglas Brubaker, Elena Svenson, Smith Kai, Maya Monroe, Christopher Ryu, Goutham Narla, Mark R. Chance, Gurkan Bebek. Cancer drug response networks built for comparative cancer pharmacogenomics identifies combination therapies for repositioning. [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 B1-43.
Abstract B2-01: Integrated omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact
Authors: Moran Michael F. , Kislinger Thomas , Li Lei , Ignatchenko Vladimir , Wei Yuhong , To Christine , Taylor Paul , Tong Jiefei , Pham Nhu An , Pintilie Melania , Muthuswamy Lakshmi , Shepherd Frances A. , Tsao Ming Sound 
Published: May 2016

Abstract
Cancer results from processes prone to selective pressure and dysregulation acting along the sequence-to-phenotype continuum DNA→RNA→Protein→Disease. An Omics Array integrating DNA gene copy number, mRNA transcriptome, and quantified proteome was assembled into a genetic map representing non-small cell lung carcinoma (NSCLC). Data were collected from patient-matched normal lung, primary tumors, and patient tumor-derived xenograft (PDX) tumors. Dysregulated proteins not previously implicated as cancer drivers were found encoded throughout the genome including but not limited to regions of recurrent DNA amplification/deletion in NSCLC. Unsupervised clustering revealed signatures comprising metabolism proteins particularly highly recapitulated between matched primary and PDX tumors, and which distinguished between the major NSCLC histological subtypes adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Interrogation of The Cancer Genome Atlas (TCGA) revealed sizeable cohorts of NSCLC patients with DNA alterations in genes encoding the metabolism proteome signatures, and accompanied by differences in survival. Similar to the proteome signatures from which they were extrapolated, the gene mutation signatures with prognostic impact discriminated between the lung ADC and SCC subtypes. Serine hydroxymethyltransferase 2 (SHMT2), a key enzyme in serine/glycine and folate-dependent one-carbon metabolism, is upregulated in the proteomes of NSCLC primary and PDX tumours, and is implicated as a driver of recurrent chromosome 12q14.1 amplification in NSCLC. SHMT2, along with other enzymes implicated as anti-folate targets, is also part of a metabolism signature associated with poor outcome in lung ADC. The interrogation of cancer genomes and proteomes for alterations that are related products of selective pressures driving the cancer phenotype may be a general approach to uncover and group together cryptic, polygenic cancer drivers, which might represent new anti-cancer therapeutic targets.
Note: This abstract was not presented at the conference.
Citation Format: Michael F. Moran, Thomas Kislinger, Lei Li, Vladimir Ignatchenko, Yuhong Wei, Christine To, Paul Taylor, Jiefei Tong, Nhu An Pham, Melania Pintilie, Lakshmi Muthuswamy, Frances A. Shepherd, Ming Sound Tsao. Integrated omic analysis of lung cancer reveals metabolism proteome signatures with prognostic impact. [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 B2-01.
Abstract B2-18: Mechanisms of GBM progression on bevacizumab: Model predictions
Authors: Scribner Elizabeth , Saut Olivier , Colin Thierry , Fathallah-Shaykh Hassan M. 
Published: May 2016

Abstract
Glioblastoma multiforme (GBM) causes significant neurological morbidity and short survival times. Brain invasion by GBM is associated with poor prognosis. Recent clinical trials of bevacizumab in newly-diagnosed GBM found no beneficial effects on overall survival times. We have reported a mathematical model of GBM growth and invasion, built at the scale of clinical magnetic resonance imaging. Here, we replicate the patterns of progression of GBM patients treated with bevacizumab. The model is interrogated to derive a mechanistic explanation for each type of recurrence.
Citation Format: Elizabeth Scribner, Olivier Saut, Thierry Colin, Hassan M. Fathallah-Shaykh. Mechanisms of GBM progression on bevacizumab: Model predictions. [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 B2-18.
Abstract B2-21: Identification of somatic RNA splicing alterations in human cancers
Authors: Brooks Angela N. , Ge Yawei , Chau Kevin , Freeman Samuel S. , Saksena Gordon , Pedamallu Chandra Sekhar , Meyerson Matthew 
Published: May 2016

Abstract
Recent whole-exome sequencing studies have found that somatic mutations frequently occur in splicing factors across multiple cancer types, supporting the need to systematically and globally characterize splicing alterations across human cancers. Somatic alterations that affect RNA processing of cancer genes may be caused by multiple mechanisms, including mutations in splicing factors, mutations in cis-acting splice sites and other regulatory sequences, alterations in methylation, or alterations in chromatin structure. For a global look at somatic RNA splicing alterations, we are applying the Cancer Outlier Profile Analysis (COPA) approach on ~7,000 cancer transcriptomes from 12 tumor types in The Cancer Genome Atlas (TCGA) and investigating the underlying somatic mutations that cause these splicing alterations using matched whole-exome, whole-genome, and methylation data from these samples.
To identify and quantify alternative splicing in RNA-Seq data, including unannotated splicing events, we have further developed a computational pipeline called JuncBASE. To distinguish between cancer-specific splicing alterations and normal transcriptome variation, we are utilizing ~700 RNA-Seq libraries from healthy individuals from the Genotype-Tissue Expression (GTEx) project.
COPA analysis of outlier splicing events in lung adenocarcinomas and glioblastomas successfully identified known altered splicing events in MET and EGFR, respectively, that are caused by DNA level somatic mutations. The genomic mechanisms for novel somatic splicing events in known cancer genes such as FGFR3, as well as genes previously uncharacterized in cancer genomes, are currently being investigated.
To identify splicing events that may be novel somatic driver alterations, these events have been profiled using RNA-Seq data from the Cancer Cell Line Encyclopedia and are being used as biomarkers to identify genetic vulnerabilities in high-throughput shRNA screens. This work will have a significant impact on the identification of somatic splicing events that contribute to cancer pathogenesis.
Citation Format: Angela N. Brooks, Yawei Ge, Kevin Chau, Samuel S. Freeman, Gordon Saksena, Chandra Sekhar Pedamallu, Matthew Meyerson. Identification of somatic RNA splicing alterations in human cancers. [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 B2-21.