A Novel Gene-By-Environment Quantitative Trait Locus on Mouse Chromosome 15 Underlies
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Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Mutational Landscape Differences Between Young-Onset and Older-Onset Breast Cancer Patients Nicole E
Mealey et al. BMC Cancer (2020) 20:212 https://doi.org/10.1186/s12885-020-6684-z RESEARCH ARTICLE Open Access Mutational landscape differences between young-onset and older-onset breast cancer patients Nicole E. Mealey1 , Dylan E. O’Sullivan2 , Joy Pader3 , Yibing Ruan3 , Edwin Wang4 , May Lynn Quan1,5,6 and Darren R. Brenner1,3,5* Abstract Background: The incidence of breast cancer among young women (aged ≤40 years) has increased in North America and Europe. Fewer than 10% of cases among young women are attributable to inherited BRCA1 or BRCA2 mutations, suggesting an important role for somatic mutations. This study investigated genomic differences between young- and older-onset breast tumours. Methods: In this study we characterized the mutational landscape of 89 young-onset breast tumours (≤40 years) and examined differences with 949 older-onset tumours (> 40 years) using data from The Cancer Genome Atlas. We examined mutated genes, mutational load, and types of mutations. We used complementary R packages “deconstructSigs” and “SomaticSignatures” to extract mutational signatures. A recursively partitioned mixture model was used to identify whether combinations of mutational signatures were related to age of onset. Results: Older patients had a higher proportion of mutations in PIK3CA, CDH1, and MAP3K1 genes, while young- onset patients had a higher proportion of mutations in GATA3 and CTNNB1. Mutational load was lower for young- onset tumours, and a higher proportion of these mutations were C > A mutations, but a lower proportion were C > T mutations compared to older-onset tumours. The most common mutational signatures identified in both age groups were signatures 1 and 3 from the COSMIC database. -
Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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. Abstract The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes. -
Role of Amylase in Ovarian Cancer Mai Mohamed University of South Florida, [email protected]
University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School July 2017 Role of Amylase in Ovarian Cancer Mai Mohamed University of South Florida, [email protected] Follow this and additional works at: http://scholarcommons.usf.edu/etd Part of the Pathology Commons Scholar Commons Citation Mohamed, Mai, "Role of Amylase in Ovarian Cancer" (2017). Graduate Theses and Dissertations. http://scholarcommons.usf.edu/etd/6907 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Role of Amylase in Ovarian Cancer by Mai Mohamed A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Pathology and Cell Biology Morsani College of Medicine University of South Florida Major Professor: Patricia Kruk, Ph.D. Paula C. Bickford, Ph.D. Meera Nanjundan, Ph.D. Marzenna Wiranowska, Ph.D. Lauri Wright, Ph.D. Date of Approval: June 29, 2017 Keywords: ovarian cancer, amylase, computational analyses, glycocalyx, cellular invasion Copyright © 2017, Mai Mohamed Dedication This dissertation is dedicated to my parents, Ahmed and Fatma, who have always stressed the importance of education, and, throughout my education, have been my strongest source of encouragement and support. They always believed in me and I am eternally grateful to them. I would also like to thank my brothers, Mohamed and Hussien, and my sister, Mariam. I would also like to thank my husband, Ahmed. -
Ncomms3787.Pdf
ARTICLE Received 6 Aug 2013 | Accepted 17 Oct 2013 | Published 14 Nov 2013 DOI: 10.1038/ncomms3787 OPEN Structural and molecular basis of ZNRF3/RNF43 transmembrane ubiquitin ligase inhibition by the Wnt agonist R-spondin Matthias Zebisch1, Yang Xu2,3, Christos Krastev1, Bryan T. MacDonald2, Maorong Chen2, Robert J.C. Gilbert1,XiHe2 & E. Yvonne Jones1 The four R-spondin (Rspo) proteins are secreted agonists of Wnt signalling in vertebrates, functioning in embryogenesis and adult stem cell biology. Through ubiquitination and degradation of Wnt receptors, the transmembrane E3 ubiquitin ligase ZNRF3 and related RNF43 antagonize Wnt signalling. Rspo ligands have been reported to inhibit the ligase activity through direct interaction with ZNRF3 and RNF43. Here we report multiple crystal structures of the ZNRF3 ectodomain (ZNRF3ecto), a signalling-competent Furin1–Furin2 (Fu1–Fu2) fragment of Rspo2 (Rspo2Fu1–Fu2), and Rspo2Fu1–Fu2 in complex with ZNRF3ecto,or RNF43ecto. A prominent loop in Fu1 clamps into equivalent grooves in the ZNRF3ecto and RNF43ecto surface. Rspo binding enhances dimerization of ZNRF3ecto but not of RNF43ecto. Comparison of the four Rspo proteins, mutants and chimeras in biophysical and cellular assays shows that their signalling potency depends on their ability to recruit ZNRF3 or RNF43 via Fu1 into a complex with LGR receptors, which interact with Rspo via Fu2. 1 Division of Structural Biology, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK. 2 F.M. Kirby Neurobiology Center, Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA. 3 Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, College of Life Science, Jilin University, Changchun 130012, China. -
Atlas Journal
Atlas of Genetics and Cytogenetics in Oncology and Haematology Home Genes Leukemias Solid Tumours Cancer-Prone Deep Insight Portal Teaching X Y 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 NA Atlas Journal Atlas Journal versus Atlas Database: the accumulation of the issues of the Journal constitutes the body of the Database/Text-Book. TABLE OF CONTENTS Volume 12, Number 6, Nov-Dec 2008 Previous Issue / Next Issue Genes BCL8 (B-cell CLL/lymphoma 8) (15q11). Silvia Rasi, Gianluca Gaidano. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 781-784. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/BCL8ID781ch15q11.html CDC25A (Cell division cycle 25A) (3p21). Dipankar Ray, Hiroaki Kiyokawa. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 785-791. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/CDC25AID40004ch3p21.html CDC73 (cell division cycle 73, Paf1/RNA polymerase II complex component, homolog (S. cerevisiae)) (1q31.2). Leslie Farber, Bin Tean Teh. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 792-797. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/CDC73D181ch1q31.html EIF3C (eukaryotic translation initiation factor 3, subunit C) (16p11.2). Daniel R Scoles. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 798-802. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/EIF3CID44187ch16p11.html ELAC2 (elaC homolog 2 (E. coli)) (17p11.2). Yang Chen, Sean Tavtigian, Donna Shattuck. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 803-806. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/ELAC2ID40437ch17p11.html FOXM1 (forkhead box M1) (12p13). Jamila Laoukili, Monica Alvarez Fernandez, René H Medema. -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts. -
RSPO4 Is the Major Gene in Autosomal-Recessive Anonychia
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector ORIGINAL ARTICLE RSPO4 Is the Major Gene in Autosomal-Recessive Anonychia and Mutations Cluster in the Furin-Like Cysteine-Rich Domains of the Wnt Signaling Ligand R-spondin 4 Nadina Ortiz Bru¨chle1, Jorge Frank2,3, Valeska Frank1, Jan Senderek1, Ahmet Akar4, Erol Koc4, Dimitris Rigopoulos5, Maurice van Steensel2,3, Klaus Zerres1 and Carsten Bergmann1 Congenital anonychia is a rare autosomal-recessive disorder characterized by the absence of finger- and toenails. Recently, we and others identified the secreted Wnt signaling ligand R-spondin 4 (RSPO4) as the first gene known to be responsible for inherited anonychia. R-spondins are secreted proteins that activate the Wnt/ b-catenin signaling pathway. This puts anonychia on the growing list of congenital malformation syndromes caused by Wnt signaling pathway defects. Here, we expand the RSPO4 mutational spectrum by identification of the previously unknown mutations c.190C4T (p.Arg64Cys) in exon 2 and c.301C4T (p.Gln101X) in exon 3, thereby corroborating R-spondin 4 as the major protein in autosomal-recessive anonychia. Almost all RSPO4 mutations detected so far affect the highly conserved exons 2 and 3. Thus, we postulate that RSPO4 mutations preferentially cluster in the furin-like cysteine-rich domains of R-spondin 4, which is in line with experimental data proposing that for b-catenin stabilization, a shortened protein comprising just these two regions is sufficient. Journal of Investigative Dermatology (2008) 128, 791–796; doi:10.1038/sj.jid.5701088; published online 4 October 2007 INTRODUCTION even within a given family. -
Multi Gene Mutation Signatures in Colorectal Cancer
Zhuang et al. BMC Cancer (2021) 21:380 https://doi.org/10.1186/s12885-021-08108-9 RESEARCH ARTICLE Open Access Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis Yan Zhuang1†, Hailong Wang2†, Da Jiang3, Ying Li3, Lixia Feng4, Caijuan Tian5, Mingyu Pu5, Xiaowei Wang6, Jiangyan Zhang6, Yuanjing Hu7* and Pengfei Liu2* Abstract Background: Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. Currently, however, there is still few effective biomarkers for early diagnosis and prognostic judgment in CRC patients. The purpose was to identify novel mutation signatures for the diagnosis and prognosis of CRC. Methods: Clinical information of 531 CRC patients and their sequencing data were downloaded from TCGA database (training group), and 53 clinical patients were collected and sequenced with targeted next generation sequencing (NGS) technology (validation group). The relationship between the mutation genes and the diagnosis, pathological type, stage and prognosis of CRC were compared to construct signatures for CRC, and then analyzed their relationship with RNA expression, immunocyte infiltration and tumor microenvironment (TME). (Continued on next page) * Correspondence: [email protected]; [email protected] †Yan Zhuang and Hailong Wang contributed equally to this work. 7Department of Gynecological Oncology, Tianjin Central Hospital of Obstetrics & Gynecology, No. 156 Nankai Third Road, Nankai District, Tianjin 300100, China 2Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, No.354 Beima Road, Hongqiao District, Tianjin 300120, China Full list of author information is available at the end of the article © The Author(s). -
Regulation of Cancer Stemness in Breast Ductal Carcinoma in Situ by Vitamin D Compounds
Author Manuscript Published OnlineFirst on May 28, 2020; DOI: 10.1158/1940-6207.CAPR-19-0566 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Analysis of the Transcriptome: Regulation of Cancer Stemness in Breast Ductal Carcinoma In Situ by Vitamin D Compounds Naing Lin Shan1, Audrey Minden1,5, Philip Furmanski1,5, Min Ji Bak1, Li Cai2,5, Roman Wernyj1, Davit Sargsyan3, David Cheng3, Renyi Wu3, Hsiao-Chen D. Kuo3, Shanyi N. Li3, Mingzhu Fang4, Hubert Maehr1, Ah-Ng Kong3,5, Nanjoo Suh1,5 1Department of Chemical Biology, Ernest Mario School of Pharmacy; 2Department of Biomedical Engineering, School of Engineering; 3Department of Pharmaceutics, Ernest Mario School of Pharmacy; 4Environmental and Occupational Health Sciences Institute and School of Public Health, 5Rutgers Cancer Institute of New Jersey, New Brunswick; Rutgers, The State University of New Jersey, NJ, USA Running title: Regulation of cancer stemness by vitamin D compounds Key words: Breast cancer, cancer stemness, gene expression, DCIS, vitamin D compounds Financial Support: This research was supported by the National Institutes of Health grant R01 AT007036, R01 AT009152, ES005022, Charles and Johanna Busch Memorial Fund at Rutgers University and the New Jersey Health Foundation. Corresponding author: Dr. Nanjoo Suh, Department of Chemical Biology, Ernest Mario School of Pharmacy, Rutgers, The State University of New Jersey, 164 Frelinghuysen Road, Piscataway, New Jersey 08854. Tel: 848-445-8030, Fax: 732-445-0687; e-mail: [email protected] Disclosure of Conflict of Interest: “The authors declare no potential conflicts of interest” 1 Downloaded from cancerpreventionresearch.aacrjournals.org on October 1, 2021. -
Altered Gene Expression in Circulating Immune Cells Following a 24-Hour Passive Dehydration
University of Connecticut OpenCommons@UConn Master's Theses University of Connecticut Graduate School 5-10-2020 Altered Gene Expression in Circulating Immune Cells Following a 24-Hour Passive Dehydration Aidan Fiol [email protected] Follow this and additional works at: https://opencommons.uconn.edu/gs_theses Recommended Citation Fiol, Aidan, "Altered Gene Expression in Circulating Immune Cells Following a 24-Hour Passive Dehydration" (2020). Master's Theses. 1480. https://opencommons.uconn.edu/gs_theses/1480 This work is brought to you for free and open access by the University of Connecticut Graduate School at OpenCommons@UConn. It has been accepted for inclusion in Master's Theses by an authorized administrator of OpenCommons@UConn. For more information, please contact [email protected]. Altered Gene Expression in Circulating Immune Cells Following a 24- Hour Passive Dehydration Aidan Fiol B.S., University of Connecticut, 2018 A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science At the University of Connecticut 2020 i copyright by Aidan Fiol 2020 ii APPROVAL PAGE Master of Science Thesis Altered Gene Expression in Circulating Immune Cells Following a 24- Hour Passive Dehydration Presented by Aidan Fiol, B.S. Major Advisor__________________________________________________________________ Elaine Choung-Hee Lee, Ph.D. Associate Advisor_______________________________________________________________ Douglas J. Casa, Ph.D. Associate Advisor_______________________________________________________________ Robert A. Huggins, Ph.D. University of Connecticut 2020 iii ACKNOWLEDGEMENTS I’d like to thank my committee members. Dr. Lee, you have been an amazing advisor, mentor and friend to me these past few years. Your advice, whether it was how to be a better writer or scientist, or just general life advice given on our way to get coffee, has helped me grow as a researcher and as a person.