bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 3540: Targeting obesity-related cancer progression with novel leptin receptor antagonists
Authors: Lipsey Crystal C. , Harbuzariu Adriana , Gonzalez-Perez Ruben R. 
Published: July 2017

Abstract
Obesity is a global health issue that has been identified as a risk factor for several types of cancer. High levels of body fat and circulating leptin are typical identifiers of obesity in humans and animals. Leptin is a 16kD protein hormone which is secreted by adipocytes, and maybe secreted from cancer cells, that functions to control satiation via leptin receptor binding. However, obese individuals often develop “leptin resistance”, which is a mechanism that leads to the accumulation of excess leptin. Increased binding of leptin to its receptor (OB-R) due to leptin resistance has been associated with disease progression and poor prognosis in human cancers. Our group has previously shown that leptin-mediated cancer cell proliferation is inhibited by the LPrA2 (leptin peptide receptor antagonist 2). We have prepared novel leptin antagonists and tested their ability to block leptin-induced survival and chemoresistance to Paclitaxel (TAX) and Gemcitabine (GEM) in cancer cells and derived tumorspheres (pancreatic: PANC-1, MiaPaca2 and triple negative breast cancer: MDA-MB231 and MDA-MB468). Western blot protein analyses showed the ability of the antagonists to specifically inhibit leptin-induced phosphorylation of STAT3, and expression of cyclin D, and Notch1 in cancer cells. Additionally, potential toxicity of antagonists was tested using MTT assay with concentrations up to 100X higher than the effective dose in non-malignant breast cells (MCF-10A). Data generated show no toxicity of the novel antagonists in vitro. Leptin-induced proliferation of breast cancer and pancreatic cancer cells (120-160%) was significantly inhibited by the novel antagonists. In addition, leptin-mediated progression of S-phase was also reduced by the antagonists. Leptin increased TAX and GEM chemoresistance in cells and tumorspheres that were efficiently inhibited by the antagonists. These data suggest that the new antagonists could be equally or more effective than LPrA2 for adjuvant treatment of cancer.
Acknowledgements: This work has been supported by Pilot Project Award from MSM/Tuskegee University/UAB Cancer Center partnership grant 5U54CA118638; PC SPORE Grant from UAB to RRGP, and facilities and support services at Morehouse School of Medicine (1G12RR026250-03; NIH RR 03034 and 1C06 RR18386).
Citation Format: Crystal C. Lipsey, Adriana Harbuzariu, Ruben R. Gonzalez-Perez. Targeting obesity-related cancer progression with novel leptin receptor antagonists [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3540. doi:10.1158/1538-7445.AM2017-3540
Abstract 3541: Metabolic signature characterization in prostate cancer mediated by heme-oxygenase 1
Authors: Arciuch Valeria G. Antico , Anselmino Nicolas , Schuster Federico , Paez Alejandra , Cascardo Florencia , Cotignola Javier , Gueron Geraldine , Vazquez Elba 
Published: July 2017

Abstract
Prostate cancer (PCa) is the second leading cause of cancer-associated death in men, being bone metastases the main cause of mortality. Energetic metabolism alterations have become a new hallmark of cancer, since variations in a single gene can orchestrate changes in metabolic pathways and confer an adaptive advantage. Heme-oxygenase 1 (HO-1) exerts an antitumoral role in PCa inhibiting cell proliferation, migration, tumor growth and angiogenesis. The aim of this work was to assess the role of HO-1 in the metabolic signature of PCa. Through RNA-Seq we found a set of metabolic genes deregulated under pharmacological induction (hemin treatment) or genetic induction of HO-1 in PC3 cells. STAR and ATP5L2 were found upregulated, while HMGCS2, PRODH and ACOT12 were downregulated. These genes encode for steroid hormone metabolism, ATP synthesis, ketogenesis, proline and lipid metabolism. The analysis of the deregulated genes (2-fold) under HO-1 modulation by Gene Ontology revealed alterations in several metabolic pathways such as steroid, tyrosine and lipid metabolism, and ion transport. Bone is the only site of PCa progression, and bone cells are able to produce factors that increase the growth and survival of tumor cells favoring progression. However, the molecular nature of this interaction remains to be elucidated. Our preliminary results performed on co-cultures of PC3 cells (treated or not with hemin) with Raw264.7 (pre-osteoclastic) or MC3T3 (pre-osteoblastic) cells demonstrate that HO-1 is able to direct the metabolic fate of bone precursor cells due to the deregulation of glycolytic genes. HO-1 induction in PC3 cells downregulated the expression of PKM2 and LDHA in co-cultured Raw264.7 and MC3T3 cells (p&lt; 0.05). Based on our results, we propose HO-1 as a key regulator of the metabolic status of PCa cells and a powerful mediator capable of redefining the metabolic signature of bone precursor cells, thus, favoring the establishment of a less aggressive phenotype.
Note: This abstract was not presented at the meeting.
Citation Format: Valeria G. Antico Arciuch, Nicolas Anselmino, Federico Schuster, Alejandra Paez, Florencia Cascardo, Javier Cotignola, Geraldine Gueron, Elba Vazquez. Metabolic signature characterization in prostate cancer mediated by heme-oxygenase 1 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3541. doi:10.1158/1538-7445.AM2017-3541
Abstract 3551: Targeting glutamine addiction of PIK3CA mutant colorectal cancers
Authors: Zhao Yiqing 
Published: July 2017

Abstract
Glutamine addiction is a major metabolic reprogramming event that occurs in cancer cells. Many tumors exhibit oncogene-dependent addiction to glutamine. PIK3CA, which encodes the p110α catalytic subunit of phosphatidylinositol 3-kinase α, is the most frequently mutated oncogene in human cancers. However, whether PIK3CA mutations reprogram cancer metabolism is an important unaddressed question. Here we show that oncogenic PIK3CA mutations render colorectal cancers (CRCs) more dependent on glutamine to growth. As a metabolite, glutamine is first converted to glutamate by glutaminase (GLS) and then to α-ketoglutarate (α-KG) by either a transaminase or a glutamate dehydrogenase. Calithera Biosciences recently developed a potent GLS inhibitor called CB-839, which is currently in phase I clinical trials in cancer patients. Using isogenic colorectal cancer cell lines with either WT or mutant PIK3CA allele knockout, we demonstrated that CRCs with PIK3CA mutations are more sensitive to growth inhibition by CB-839. Remarkably, combination of CB-839 with 5-FU induces regression xenograft tumors in PIK3CA mutant CRC models, suggesting that this combinational therapy may be effective approach to treat CRC patients whose tumors harbor PIK3CA mutations. Mechanistically, mutant p110α up-regulates gene expression of glutamate pyruvate transaminase 2 (GPT2) through an AKT-independent PDK1-RSK2-ATF4 signaling axis, thereby facilitating conversion of glutamate to α-KG. Together, our data establish oncogenic PIK3CA mutations as a cause of glutamine addiction in CRCs and that targeting glutamine metabolism may be effective approach to treat CRCs with PIK3CA mutations.
Citation Format: Yiqing Zhao. Targeting glutamine addiction of PIK3CA mutant colorectal cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3551. doi:10.1158/1538-7445.AM2017-3551
Abstract 3557: miR-155 positively regulates glucose metabolism via PI3K p85&lt;alpha&gt;-FOXO3a-cMYC axis in breast cancer
Authors: Kim Sinae , Lee Eunji , Chang Suhwan 
Published: July 2017

Abstract
Breast cancer is the most common cancer for women worldwide. Although the oncogenic roles of miR-155 in cancer have been reported, the metabolic function of miR-155 in breast cancer has not been fully elucidated. In this study, we have investigated how the energy metabolic shift occurs after a genetic inactivation or knockdown of miR-155. To this end, we performed metabolic profiling of the miR-155ko/ko or miR-155+/ko primary cancer cells, obtained from mouse breast cancer model. We found, in the absence of miR-155, less glucose uptake and glycolysis in tumor cells. Mechanistically, we revealed PIK3R1(Phosphoinositide-3-Kinase, Regulatory Subunit1, p85&lt;alpha&gt;) and FOXO3a (Forkhead transcription factor of the O class 3a) are major targets that trigger the metabolic shift. Furthermore, we showed cMYC level was consequently decreased in the absence of miR-155 that results in the down-regulation of proteins playing in glucose uptake and Glycolysis. This finding is further confirmed in mouse allograft model. Finally, we show the miR-155 expression is positively correlates with either energy metabolite levels or standardized uptake values (SUV) of fluoro-deoxy glucose (FDG)-PET Images in triple negative breast tumors. Taken together, our study demonstrates a novel mechanism by which the miR-155 controls energy metabolism in breast cancer, through PI3K p85&lt;alpha&gt;-FOXO3a-cMYC axis.
Citation Format: Sinae Kim, Eunji Lee, Suhwan Chang. miR-155 positively regulates glucose metabolism via PI3K p85&lt;alpha&gt;-FOXO3a-cMYC axis in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3557. doi:10.1158/1538-7445.AM2017-3557
Abstract 3561: UCP2’s tumor-promoting role via regulating lipid signaling and PLCγ -1 activity
Authors: Sreedhar Annapoorna , Zhao Yunfeng 
Published: July 2017

Abstract
Mitochondrial abnormalities are long suspected to play important roles in tumor cell differentiation, proliferation and metabolism. Dysfunction of mitochondrial-dependent processes appear to be key features of cancerous cells. Among many such abnormal features of cancerous cells, a mitochondrial uncoupling protein 2 (UCP2) is shown to be up-regulated in various aggressive human cancers. Uncoupling proteins are a family of mitochondrial proteins present in the inner mitochondrial membrane whose physiological role is to decrease membrane potential and reactive oxygen species (ROS) production.
UCP2 over-expression recently been proposed as a novel survival mechanism for cancer cells. However, till date, the exact role of UCP2 in cancer remains inconclusive.
We recently reported that UCP2 appears to be a key regulator of cell proliferation, cell cycle and cell death during skin tumorigenesis. Using JB6P+ cells that overexpress UCP2, we showed that UCP2 expression correlated closely with cell proliferation and cell transformation. Moreover, inhibition of UCP2, decreased colony formation and 3D culture growth. Since UCP2 is the crucial player in the regulation of reactive oxygen species, and mitochondrial bioenergetics, we wanted to dissect out the role of UCP2 in redox regulation and tumor promotion.
Our data demonstrated that UCP2 differentially regulated ROS. UCP2 upregulation, decreased superoxide production, whereas increased hydrogen peroxide production with a concomitant increase in manganese superoxide dismutase (MnSOD) expression and activity. Furthermore, hydrogen peroxide was responsible for induction of lipid peroxidation and PLCγ-1 activation in UCP2 overexpressed cells. Moreover, PLCγ-1 activation enhanced tumorigenecity. Strikingly, pharmacological and siRNA mediated inhibition of PLCγ-1 markedly reduced colony formation and 3D growth in vitro. Lastly, restricting hydrogen peroxide production with hydrogen peroxide scavenger catalase, suppressed lipid peroxidation and dampened PLCγ-1 activity.
Taken together, our data suggest that hydrogen peroxide might be the mediator of UCP2’s tumor promoting role, and pharmacological disruption of PLCγ-1, and/or hydrogen peroxide may have clinical utility for UCP2-overexpressed cancers.
This research was funded by NCI and Feist-Wellier Cancer Center of LSUHSC-S
Citation Format: Annapoorna Sreedhar, Yunfeng Zhao. UCP2’s tumor-promoting role via regulating lipid signaling and PLCγ -1 activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3561. doi:10.1158/1538-7445.AM2017-3561
Abstract 3571: Precise somatic mutation prediction in the absence of matching normal DNA
Authors: Kalatskaya Irina , Trinh Quang , Spears Melanie , Bartlett John , Stein Lincoln 
Published: July 2017

Abstract
Accurate identification of somatic mutations is an essential first step for many cancer studies. It is usually done by comparing the genome of the tumour to the reference genome sequence derived from a normal tissue taken from the same donor. However, there are a number of possible scenarios in which matched normal tissues might be not available for comparisons. It is most commonly encountered when performing analysis on retrospective studies with human tissues from clinical trials or pathology archives when normal samples were not collected in the first place or patient consent precludes examination of normal tissue or germline variants. Another common scenario is the use of a cancer cell line as an experimental model, many of which have no information on the donor’s normal genome. In this work, we describe an algorithm to identify somatic single nucleotide variants (SNVs) in Next Generation Sequencing (NGS) data in the absence of normal samples using a machine learning approach. Our algorithm was evaluated using a family of supervised learning classifications across six different cancer types and ~1,600 samples, including cell lines, fresh frozen tissues, and formalin-fixed paraffin-embedded (FFPE) tissues. In addition, our algorithm was tested with both deep targeted sequencing and whole exome sequencing strategies. The algorithm correctly classified between 95% and 98% of somatic mutations with F1-measure ranges from 75.9% to 98.6% depending on the tumour type. We have released the algorithm as a software package called ISOWN (Identification of SOmatic mutations Without matching Normal tissues), which is available as Open Source under Apache License 2.0 from https://github.com/ikalatskaya/ISOWN.
Citation Format: Irina Kalatskaya, Quang Trinh, Melanie Spears, John Bartlett, Lincoln Stein. Precise somatic mutation prediction in the absence of matching normal DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3571. doi:10.1158/1538-7445.AM2017-3571
Abstract 3578: Methyl2Acetyl: predicting epigenetic and transcriptomic activity from DNA methylation
Authors: Chen Xiang 
Published: July 2017

Abstract
DNA methylation and histone modifications are interconnected and interdependent epigenetic mechanisms that regulate chromatin accessibility in cells. They establish cell’s developmental identity and modulate individual response to endogenous developmental stimuli and environmental changes. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a popular assay to study genomewide histone modification profiles. However, ChIP-seq assays require relatively large amounts of starting materials (ranging from ~105 cells using a low cell number protocol to 107 cells in a standard protocol), which remains as a major obstacle for precious biological samples including primary tumor specimens. On the other hand, tagmentation-based whole genome bisulfite sequencing (TWGBS) protocol enables unbiased assessment of the genomewide methylation pattern using ~3,000 cells. Therefore, a quantitative relationship between DNA methylation and epigenetic/transcriptomic activity is in great demand.
In the current study, we developed Methyl2Acetyl, a machine learning framework to infer promoter epigenetic activities (e.g. H3K27Ac enrichment) using TWGBS data as input. The proposed model utilizes random forest learners, which allow automatic extraction of complex interactions among DNA methylation features surrounding transcription start sites. We applied Methyl2Acetyl to a set of pediatric solid tumor samples with high quality H3K27Ac ChIPseq data to evaluate its performance. The model accurately predicted promoter H3K27Ac enrichment in independent test samples (Pearson correlation against measured enrichment: 0.81 ± 0.02). To further test the robustness of our model, we trained a Methyl2Acetyl model on solid tumors and applied it to a set of 10 pediatric leukemia samples. Despite dramatic global methylome differences between solid tumors and leukemia, Methyl2Acetyl predicted promoter H3K27Ac enrichment showed strong concordance with target gene expression level in the same sample (Pearson correlation: 0.75 ± 0.02, classification AUC: 0.89 ± 0.01). Collectively, our data suggested that DNA methylation is predictive of promoter active histone modification enrichment and gene expression activity. Epigenetically active promoters can be imputed from TWGBS data in samples with limiting starting materials.
Citation Format: Xiang Chen. Methyl2Acetyl: predicting epigenetic and transcriptomic activity from DNA methylation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3578. doi:10.1158/1538-7445.AM2017-3578
Abstract 359: C1GALT1 activates multiple RTKs and promotes malignant behaviors in pancreatic adenocarcinoma cells
Authors: Kuo Ting-Chun , Juan Hsueh-Fen , Tien Yu-Wen , Huang Min-Chuan 
Published: July 2017

Abstract
Pancreatic adenocarcinoma (PDAC), stands up to the 4th in all cancer mortalities and remains the most in progress in America. Curative resection remains the most and only potential strategy but only 15~20% of patients are candidates. Even though, many of them have dismal prognosis. Aberrant glycosylation illustrates an attribution of cancer, especially fot promoting malignant behaviors in adenocarcinomas. Altered expression of glycans, such as GalNAcα1-O-S/T (Tn antigen) and Galβ1,3-GalNAc-S/T (T antigen), is hallmark of cancers. Core 1 β1,3-galactosyltransferase (C1GALT1) catalyzes the transfer of Gal to Tn antigen to form T antigen. C1GALT1 is reported to contribute to clinicopathological features and malignant phenotypes in various cancers. However, the expression and function of C1GALT1 in PDAC remain unrevealed. Our data showed that C1GALT1 was overexpressed in PDAC tissues and correlated with poor prognosis. C1GALT1 knockdown inhibited viability, migration, and invasion analyzed by MTT, transwell migration, and Matrigel invasion assays, respectively, in PDAC cells, associated with increased Tn antigen but decreased T antigen expression. Conversely, C1GALT1 overexpression promoted these malignant behaviors. C1GALT1 knockdown inhibited AKT and ERK activities in PDAC cells. Consistently, phospho-receptor tyrosine kinase (p-RTK) array showed decreased phosphorylation of several RTKs including EGFR, IGF1R, and FLT3. Additionally, flow cytometry of C1GALT1 knockdown cells showed enhanced apoptosis, which was associated with decreased catalase, Bcl-x, and death receptor DR5 revealed by apoptosis array. We also found that C1GALT1 knockdown arrested G1 progression in PDAC cells. Furthermore, gene set enrichment analysis of cDNA microarray indicated that C1GALT1 regulated cell cycle, cytoskeleton, and chromatin structure in PDAC cells. These findings indicate that higher C1GALT1 expression predicts worse survival of PDAC and enhances malignant characters in PDAC cells, highlighting a fundamental role of C1GALT1 in PDAC development.
Note: This abstract was not presented at the meeting.
Citation Format: Ting-Chun Kuo, Hsueh-Fen Juan, Yu-Wen Tien, Min-Chuan Huang. C1GALT1 activates multiple RTKs and promotes malignant behaviors in pancreatic adenocarcinoma cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 359. doi:10.1158/1538-7445.AM2017-359
Abstract 3590: Somatic variation discovery with GATK4
Authors: Auwera Geraldine A. Van der 
Published: July 2017

Abstract
The Genome Analysis Toolkit or GATK, developed at the Broad Institute, is currently one of the most widely used software toolkits for germline short variant discovery and genotyping in whole genome and exome data. GATK4 is the next generation of GATK; it runs faster and covers more ground, adding somatic SNVs, Indels and CNVs to its variant discovery portfolio.
Given the breathtaking increase in the amount of genomic data produced in recent years, GATK development has come to tackle multiple challenges: a) reflect the cutting-edge of science in terms of depth as well as breadth of analyses offered, b) scale to petabytes of data and c) provide a way to navigate the tradeoff between turn-around-time and cost of analyses. GATK4 addresses all of these challenges through a complete redesign and reimplementation of the original GATK software.
This new version greatly expands the toolkit's scope of action within the variant discovery space by improving somatic mutation calling and adding copy number, structural variant and tumor-heterogeneity analysis tools. For the established tools and algorithms composing the GATK Best Practices pipelines for short variant discovery (including MuTect2, the next generation of the DREAM challenge-winning somatic SNV caller MuTect, developed originally in the Cancer Genome Analysis group at the Broad Institute), GATK4 is a substantial upgrade that streamlines the tools' operation, providing functionally equivalent results in a much faster timeframe through greatly increased efficiency and leaner engineering.
Designed with cloud infrastructure in mind (although it still runs on local infrastructure), GATK4 is implemented with support for Apache Spark, makes key operations hundreds of times faster than previous generations of GATK and comes with end-to-end pipeline implementations that run out of the box on select cloud platforms.
Citation Format: Geraldine A. Van der Auwera. Somatic variation discovery with GATK4 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3590. doi:10.1158/1538-7445.AM2017-3590