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Identification of BIRC6 As a Novel Intervention Target For
Lamers et al. BMC Cancer 2012, 12:285 http://www.biomedcentral.com/1471-2407/12/285 RESEARCH ARTICLE Open Access Identification of BIRC6 as a novel intervention target for neuroblastoma therapy Fieke Lamers1, Linda Schild1, Jan Koster1, Frank Speleman2, Ingrid ra3, Ellen M Westerhout1, Peter van Sluis1, Rogier Versteeg1, Huib N Caron4 and Jan J Molenaar1,5* Abstract Background: Neuroblastoma are pediatric tumors of the sympathetic nervous system with a poor prognosis. Apoptosis is often deregulated in cancer cells, but only a few defects in apoptotic routes have been identified in neuroblastoma. Methods: Here we investigated genomic aberrations affecting genes of the intrinsic apoptotic pathway in neuroblastoma. We analyzed DNA profiling data (CGH and SNP arrays) and mRNA expression data of 31 genes of the intrinsic apoptotic pathway in a dataset of 88 neuroblastoma tumors using the R2 bioinformatic platform (http://r2.amc.nl). BIRC6 was selected for further analysis as a tumor driving gene. Knockdown experiments were performed using BIRC6 lentiviral shRNA and phenotype responses were analyzed by Western blot and MTT-assays. In addition, DIABLO levels and interactions were investigated with immunofluorescence and co-immunoprecipitation. Results: We observed frequent gain of the BIRC6 gene on chromosome 2, which resulted in increased mRNA expression. BIRC6 is an inhibitor of apoptosis protein (IAP), that can bind and degrade the cytoplasmic fraction of the pro-apoptotic protein DIABLO. DIABLO mRNA expression was exceptionally high in neuroblastoma but the protein was only detected in the mitochondria. Upon silencing of BIRC6 by shRNA, DIABLO protein levels increased and cells went into apoptosis. Co-immunoprecipitation confirmed direct interaction between DIABLO and BIRC6 in neuroblastoma cell lines. -
Small Cell Ovarian Carcinoma: Genomic Stability and Responsiveness to Therapeutics
Gamwell et al. Orphanet Journal of Rare Diseases 2013, 8:33 http://www.ojrd.com/content/8/1/33 RESEARCH Open Access Small cell ovarian carcinoma: genomic stability and responsiveness to therapeutics Lisa F Gamwell1,2, Karen Gambaro3, Maria Merziotis2, Colleen Crane2, Suzanna L Arcand4, Valerie Bourada1,2, Christopher Davis2, Jeremy A Squire6, David G Huntsman7,8, Patricia N Tonin3,4,5 and Barbara C Vanderhyden1,2* Abstract Background: The biology of small cell ovarian carcinoma of the hypercalcemic type (SCCOHT), which is a rare and aggressive form of ovarian cancer, is poorly understood. Tumourigenicity, in vitro growth characteristics, genetic and genomic anomalies, and sensitivity to standard and novel chemotherapeutic treatments were investigated in the unique SCCOHT cell line, BIN-67, to provide further insight in the biology of this rare type of ovarian cancer. Method: The tumourigenic potential of BIN-67 cells was determined and the tumours formed in a xenograft model was compared to human SCCOHT. DNA sequencing, spectral karyotyping and high density SNP array analysis was performed. The sensitivity of the BIN-67 cells to standard chemotherapeutic agents and to vesicular stomatitis virus (VSV) and the JX-594 vaccinia virus was tested. Results: BIN-67 cells were capable of forming spheroids in hanging drop cultures. When xenografted into immunodeficient mice, BIN-67 cells developed into tumours that reflected the hypercalcemia and histology of human SCCOHT, notably intense expression of WT-1 and vimentin, and lack of expression of inhibin. Somatic mutations in TP53 and the most common activating mutations in KRAS and BRAF were not found in BIN-67 cells by DNA sequencing. -
1 the Neuroprotective Transcription Factor ATF5 Is Decreased And
The neuroprotective transcription factor ATF5 is decreased and sequestered into polyglutamine inclusions in Huntington’s disease Ivó H. Hernández1,2,3, Jesús Torres-Peraza1,2,5, María Santos-Galindo1,2, Eloísa Ramos-Morón4, María R. Fernández-Fernández1,2, María J. Pérez-Álvarez1,2,3, Antonio Miranda-Vizuete4 and José J. Lucas1,2* 1 Centro de Biología Molecular Severo Ochoa (CBM”SO”) CSIC/UAM, Madrid, Spain. 2 Instituto de Salud Carlos III, Networking Research Center on Neurodegenerative Diseases (CIBERNED), Spain. 3 Departamento de Biología, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain. 4 Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain 5 Present Address: Gerència d’Atenció Primària del Servei de Salut de les Illes Balears (IB-SALUT), Palma, Spain *Corresponding author: José J. Lucas [email protected] http://www.cbm.uam.es/lineas/lucasgroup.htm provided by Digital.CSIC View metadata, citation and similar papers at core.ac.uk CORE brought to you by 1 Abstract Activating transcription factor-5 (ATF5) is a stress-response transcription factor induced upon different cell stressors like fasting, amino-acid limitation, cadmium or arsenite. ATF5 is also induced, and promotes transcription of anti-apoptotic target genes like MCL1, during the unfolded protein response (UPR) triggered by endoplasmic reticulum stress. In the brain, high ATF5 levels are found in gliomas and also in neural progenitor cells, which need to decrease their ATF5 levels for differentiation into mature neurons or glia. This initially led to believe that ATF5 is not expressed in adult neurons. More recently, we reported basal neuronal ATF5 expression in adult mouse brain and its neuroprotective induction during UPR in a mouse model of status epilepticus. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Two Locus Inheritance of Non-Syndromic Midline Craniosynostosis Via Rare SMAD6 and 4 Common BMP2 Alleles 5 6 Andrew T
1 2 3 Two locus inheritance of non-syndromic midline craniosynostosis via rare SMAD6 and 4 common BMP2 alleles 5 6 Andrew T. Timberlake1-3, Jungmin Choi1,2, Samir Zaidi1,2, Qiongshi Lu4, Carol Nelson- 7 Williams1,2, Eric D. Brooks3, Kaya Bilguvar1,5, Irina Tikhonova5, Shrikant Mane1,5, Jenny F. 8 Yang3, Rajendra Sawh-Martinez3, Sarah Persing3, Elizabeth G. Zellner3, Erin Loring1,2,5, Carolyn 9 Chuang3, Amy Galm6, Peter W. Hashim3, Derek M. Steinbacher3, Michael L. DiLuna7, Charles 10 C. Duncan7, Kevin A. Pelphrey8, Hongyu Zhao4, John A. Persing3, Richard P. Lifton1,2,5,9 11 12 1Department of Genetics, Yale University School of Medicine, New Haven, CT, USA 13 2Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, CT, USA 14 3Section of Plastic and Reconstructive Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA 15 4Department of Biostatistics, Yale University School of Medicine, New Haven, CT, USA 16 5Yale Center for Genome Analysis, New Haven, CT, USA 17 6Craniosynostosis and Positional Plagiocephaly Support, New York, NY, USA 18 7Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA 19 8Child Study Center, Yale University School of Medicine, New Haven, CT, USA 20 9The Rockefeller University, New York, NY, USA 21 22 ABSTRACT 23 Premature fusion of the cranial sutures (craniosynostosis), affecting 1 in 2,000 24 newborns, is treated surgically in infancy to prevent adverse neurologic outcomes. To 25 identify mutations contributing to common non-syndromic midline (sagittal and metopic) 26 craniosynostosis, we performed exome sequencing of 132 parent-offspring trios and 59 27 additional probands. -
Mouse Cdc27 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Cdc27 Knockout Project (CRISPR/Cas9) Objective: To create a Cdc27 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Cdc27 gene (NCBI Reference Sequence: NM_145436 ; Ensembl: ENSMUSG00000020687 ) is located on Mouse chromosome 11. 19 exons are identified, with the ATG start codon in exon 1 and the TAA stop codon in exon 19 (Transcript: ENSMUST00000093923). Exon 2~7 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 2 starts from about 1.13% of the coding region. Exon 2~7 covers 32.93% of the coding region. The size of effective KO region: ~8408 bp. The KO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 3 4 5 6 7 19 Legends Exon of mouse Cdc27 Knockout region Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of Exon 2 is aligned with itself to determine if there are tandem repeats. Tandem repeats are found in the dot plot matrix. The gRNA site is selected outside of these tandem repeats. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 1285 bp section downstream of Exon 7 is aligned with itself to determine if there are tandem repeats. -
Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Exploring the Metastatic Role of the Inhibitor of Apoptosis BIRC6 in Breast Cancer
bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438518; this version posted April 10, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Exploring the metastatic role of the inhibitor of apoptosis BIRC6 in Breast 2 Cancer 3 Corresponding author: Matias Luis Pidre, Pringles 3010, Lanús, Buenos Aires, Argentina, CP 1824 4 [email protected], mobile: +54 9 221 364 6836 5 AUTHORS 6 Santiago M. Gómez Bergna1; Abril Marchesini1; Leslie C. Amorós Morales1; Paula N. Arrías1; Hernán 7 G. Farina2; Víctor Romanowski1; M. Florencia Gottardo2*; Matias L. Pidre1*. 8 *Both authors equally contributed to this work. 9 AUTHOR AFFILIATIONS 10 1Instituto de Biotecnología y biología molecular (IBBM-CONICET-UNLP) 11 2Center of Molecular & Translational Oncology, Department of Science and Technology, 12 National University of Quilmes, Buenos Aires, Argentina. 13 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438518; this version posted April 10, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 14 Abstract 15 Breast cancer is the most common cancer as well as the first cause of death by cancer in 16 women worldwide. BIRC6 (baculoviral IAP repeat-containing protein 6) is a member of the 17 inhibitors of apoptosis protein family thought to play an important role in the progression or 18 chemoresistance of many cancers. The aim of the present work was to investigate the role of 19 apoptosis inhibitor BIRC6 in breast cancer, focusing particularly on its involvement in the 20 metastatic cascade. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
Genomic Amplification of Chromosome 20Q13.33 Is the Early Biomarker For
Bui et al. BMC Medical Genomics 2020, 13(Suppl 10):149 https://doi.org/10.1186/s12920-020-00776-z RESEARCH Open Access Genomic amplification of chromosome 20q13.33 is the early biomarker for the development of sporadic colorectal carcinoma Vo-Minh-Hoang Bui1,2, Clément Mettling3, Jonathan Jou4 and H. Sunny Sun1,5* From The 18th Asia Pacific Bioinformatics Conference Seoul, Korea. 18-20 August 2020 Abstract Background: Colorectal carcinoma (CRC) is the third most common cancer in the world and also the third leading cause of cancer-related mortality in Taiwan. CRC tumorigenesis is a multistep process, starting from mutations causing loss of function of tumor suppressor genes, canonically demonstrated in adenomatous polyposis coli pathogenesis. Although many genes or chromosomal alterations have been shown to be involved in this process, there are still unrecognized molecular events within CRC tumorigenesis. Elucidating these mechanisms may help improve the management and treatment. Methods: In this study, we aimed to identify copy number alteration of the smallest chromosomal regions that is significantly associated with sporadic CRC tumorigenesis using high-resolution array-based Comparative Genomic Hybridization (aCGH) and quantitative Polymerase chain reaction (qPCR). In addition, microsatellite instability assay and sequencing-based mutation assay were performed to illustrate the initiation event of CRC tumorigenesis. Results: A total of 571 CRC patients were recruited and 377 paired CRC tissues from sporadic CRC cases were used to define the smallest regions with chromosome copy number changes. In addition, 198 colorectal polyps from 160 patients were also used to study the role of 20q13.33 gain in CRC tumorigenesis. -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia.