Histopathologic, Genetic and Molecular Characterization of Endometrial Cancer Racial Disparity
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Human Periprostatic Adipose Tissue: Secretome from Patients With
CANCER GENOMICS & PROTEOMICS 16 : 29-58 (2019) doi:10.21873/cgp.20110 Human Periprostatic Adipose Tissue: Secretome from Patients With Prostate Cancer or Benign Prostate Hyperplasia PAULA ALEJANDRA SACCA 1, OSVALDO NÉSTOR MAZZA 2, CARLOS SCORTICATI 2, GONZALO VITAGLIANO 3, GABRIEL CASAS 4 and JUAN CARLOS CALVO 1,5 1Institute of Biology and Experimental Medicine (IBYME), CONICET, Buenos Aires, Argentina; 2Department of Urology, School of Medicine, University of Buenos Aires, Clínical Hospital “José de San Martín”, Buenos Aires, Argentina; 3Department of Urology, Deutsches Hospital, Buenos Aires, Argentina; 4Department of Pathology, Deutsches Hospital, Buenos Aires, Argentina; 5Department of Biological Chemistry, School of Exact and Natural Sciences, University of Buenos Aires, Buenos Aires, Argentina Abstract. Background/Aim: Periprostatic adipose tissue Prostate cancer (PCa) is the second most common cancer in (PPAT) directs tumour behaviour. Microenvironment secretome men worldwide. While most men have indolent disease, provides information related to its biology. This study was which can be treated properly, the problem consists in performed to identify secreted proteins by PPAT, from both reliably distinguishing between indolent and aggressive prostate cancer and benign prostate hyperplasia (BPH) disease. Evidence shows that the microenvironment affects patients. Patients and Methods: Liquid chromatography-mass tumour behavior. spectrometry-based proteomic analysis was performed in Adipose tissue microenvironment is now known to direct PPAT-conditioned media (CM) from patients with prostate tumour growth, invasion and metastases (1, 2). Adipose cancer (CMs-T) (stage T3: CM-T3, stage T2: CM-T2) or tissue is adjacent to the prostate gland and the site of benign disease (CM-BPH). Results: The highest number and invasion of PCa. -
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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
PRODUCT SPECIFICATION Prest Antigen C19orf25 Product
PrEST Antigen C19orf25 Product Datasheet PrEST Antigen PRODUCT SPECIFICATION Product Name PrEST Antigen C19orf25 Product Number APrEST85422 Gene Description chromosome 19 open reading frame 25 Alternative Gene FLJ36666 Names Corresponding Anti-C19orf25 (HPA050270) Antibodies Description Recombinant protein fragment of Human C19orf25 Amino Acid Sequence Recombinant Protein Epitope Signature Tag (PrEST) antigen sequence: GEQLYQQSRAYVAANQRLQQAGNVLRQRCELLQRAGEDLEREVAQMKQAA LPAAEAASSG Fusion Tag N-terminal His6ABP (ABP = Albumin Binding Protein derived from Streptococcal Protein G) Expression Host E. coli Purification IMAC purification Predicted MW 24 kDa including tags Usage Suitable as control in WB and preadsorption assays using indicated corresponding antibodies. Purity >80% by SDS-PAGE and Coomassie blue staining Buffer PBS and 1M Urea, pH 7.4. Unit Size 100 µl Concentration Lot dependent Storage Upon delivery store at -20°C. Avoid repeated freeze/thaw cycles. Notes Gently mix before use. Optimal concentrations and conditions for each application should be determined by the user. Product of Sweden. For research use only. Not intended for pharmaceutical development, diagnostic, therapeutic or any in vivo use. No products from Atlas Antibodies may be resold, modified for resale or used to manufacture commercial products without prior written approval from Atlas Antibodies AB. Warranty: The products supplied by Atlas Antibodies are warranted to meet stated product specifications and to conform to label descriptions when used and stored properly. Unless otherwise stated, this warranty is limited to one year from date of sales for products used, handled and stored according to Atlas Antibodies AB's instructions. Atlas Antibodies AB's sole liability is limited to replacement of the product or refund of the purchase price. -
Microrna Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton
cells Review MicroRNA Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton , , Karen Uray * y , Evelin Major and Beata Lontay * y Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary; [email protected] * Correspondence: [email protected] (K.U.); [email protected] (B.L.); Tel.: +36-52-412345 (K.U. & B.L.) The authors contributed equally to the manuscript. y Received: 11 June 2020; Accepted: 7 July 2020; Published: 9 July 2020 Abstract: MicroRNAs (miRNAs) are key modulators of post-transcriptional gene regulation in a plethora of processes, including actin–myosin cytoskeleton dynamics. Recent evidence points to the widespread effects of miRNAs on actin–myosin cytoskeleton dynamics, either directly on the expression of actin and myosin genes or indirectly on the diverse signaling cascades modulating cytoskeletal arrangement. Furthermore, studies from various human models indicate that miRNAs contribute to the development of various human disorders. The potentially huge impact of miRNA-based mechanisms on cytoskeletal elements is just starting to be recognized. In this review, we summarize recent knowledge about the importance of microRNA modulation of the actin–myosin cytoskeleton affecting physiological processes, including cardiovascular function, hematopoiesis, podocyte physiology, and osteogenesis. Keywords: miRNA; actin; myosin; actin–myosin complex; Rho kinase; cancer; smooth muscle; hematopoiesis; stress fiber; gene expression; cardiovascular system; striated muscle; muscle cell differentiation; therapy 1. Introduction Actin–myosin interactions are the primary source of force generation in mammalian cells. Actin forms a cytoskeletal network and the myosin motor proteins pull actin filaments to produce contractile force. All eukaryotic cells contain an actin–myosin network inferring contractile properties to these cells. -
Novel Myosin Mutations for Hereditary Hearing Loss Revealed by Targeted Genomic Capture and Massively Parallel Sequencing
European Journal of Human Genetics (2014) 22, 768–775 & 2014 Macmillan Publishers Limited All rights reserved 1018-4813/14 www.nature.com/ejhg ARTICLE Novel myosin mutations for hereditary hearing loss revealed by targeted genomic capture and massively parallel sequencing Zippora Brownstein1,6, Amal Abu-Rayyan2,6, Daphne Karfunkel-Doron1, Serena Sirigu3, Bella Davidov4, Mordechai Shohat1,4, Moshe Frydman1,5, Anne Houdusse3, Moien Kanaan2 and Karen B Avraham*,1 Hereditary hearing loss is genetically heterogeneous, with a large number of genes and mutations contributing to this sensory, often monogenic, disease. This number, as well as large size, precludes comprehensive genetic diagnosis of all known deafness genes. A combination of targeted genomic capture and massively parallel sequencing (MPS), also referred to as next-generation sequencing, was applied to determine the deafness-causing genes in hearing-impaired individuals from Israeli Jewish and Palestinian Arab families. Among the mutations detected, we identified nine novel mutations in the genes encoding myosin VI, myosin VIIA and myosin XVA, doubling the number of myosin mutations in the Middle East. Myosin VI mutations were identified in this population for the first time. Modeling of the mutations provided predicted mechanisms for the damage they inflict in the molecular motors, leading to impaired function and thus deafness. The myosin mutations span all regions of these molecular motors, leading to a wide range of hearing phenotypes, reinforcing the key role of this family of proteins in auditory function. This study demonstrates that multiple mutations responsible for hearing loss can be identified in a relatively straightforward manner by targeted-gene MPS technology and concludes that this is the optimal genetic diagnostic approach for identification of mutations responsible for hearing loss. -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research. -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
Genome-Wide Identification, Characterization and Expression
G C A T T A C G G C A T genes Article Genome-Wide Identification, Characterization and Expression Profiling of myosin Family Genes in Sebastes schlegelii Chaofan Jin 1, Mengya Wang 1,2, Weihao Song 1 , Xiangfu Kong 1, Fengyan Zhang 1, Quanqi Zhang 1,2,3 and Yan He 1,2,* 1 MOE Key Laboratory of Molecular Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China; [email protected] (C.J.); [email protected] (M.W.); [email protected] (W.S.); [email protected] (X.K.); [email protected] (F.Z.); [email protected] (Q.Z.) 2 Laboratory of Tropical Marine Germplasm Resources and Breeding Engineering, Sanya Oceanographic Institution, Ocean University of China, Sanya 572000, China 3 Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266003, China * Correspondence: [email protected]; Tel.: +86-0532-82031986 Abstract: Myosins are important eukaryotic motor proteins that bind actin and utilize the energy of ATP hydrolysis to perform a broad range of functions such as muscle contraction, cell migration, cytokinesis, and intracellular trafficking. However, the characterization and function of myosin is poorly studied in teleost fish. In this study, we identified 60 myosin family genes in a marine teleost, black rockfish (Sebastes schlegelii), and further characterized their expression patterns. myosin showed divergent expression patterns in adult tissues, indicating they are involved in different types and Citation: Jin, C.; Wang, M.; Song, W.; compositions of muscle fibers. Among 12 subfamilies, S. schlegelii myo2 subfamily was significantly Kong, X.; Zhang, F.; Zhang, Q.; He, Y. -
WO 2012/174282 A2 20 December 2012 (20.12.2012) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2012/174282 A2 20 December 2012 (20.12.2012) P O P C T (51) International Patent Classification: David [US/US]; 13539 N . 95th Way, Scottsdale, AZ C12Q 1/68 (2006.01) 85260 (US). (21) International Application Number: (74) Agent: AKHAVAN, Ramin; Caris Science, Inc., 6655 N . PCT/US20 12/0425 19 Macarthur Blvd., Irving, TX 75039 (US). (22) International Filing Date: (81) Designated States (unless otherwise indicated, for every 14 June 2012 (14.06.2012) kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, English (25) Filing Language: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, Publication Language: English DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR, (30) Priority Data: KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, 61/497,895 16 June 201 1 (16.06.201 1) US MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, 61/499,138 20 June 201 1 (20.06.201 1) US OM, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SC, SD, 61/501,680 27 June 201 1 (27.06.201 1) u s SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, 61/506,019 8 July 201 1(08.07.201 1) u s TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. -
Coordinated Changes in Gene Expression, H1 Variant Distribution and Genome 3D Conformation in Response to H1 Depletion
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.12.429879; this version posted April 24, 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. Coordinated changes in gene expression, H1 variant distribution and genome 3D conformation in response to H1 depletion Núria Serna-Pujol1,#, Mónica Salinas-Pena1,#, Francesca Mugianesi2,#, François Le Dily3, Marc A. Marti-Renom2,3,4,5, Albert Jordan1,* 1Molecular Biology Institute oF Barcelona (IBMB-CSIC), Barcelona, 08028, Spain 2CNAG-CRG, Centre For Genomic Regulation, The Barcelona Institute oF Science and Technology, Baldiri Reixac 4, Barcelona, 08028, Spain 3Centre For Genomic Regulation, The Barcelona Institute For Science and Technology, Carrer del Doctor Aiguader 88, Barcelona, 08003, Spain 4Pompeu Fabra University, Doctor Aiguader 88, Barcelona, 08003, Spain 5ICREA, Pg. Lluís Companys 23, 08010 Barcelona, Spain # These authors contributed equally to this work. *To whom correspondence should be addressed. Tel: +34 93 402 0487; Fax: +34 93 403 4979; Email: [email protected] Running title: Consequences of H1 depletion on genome architecture 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.02.12.429879; this version posted April 24, 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. Abstract Up to seven members oF the histone H1 Family may contribute to chromatin compaction and its regulation in human somatic cells. In breast cancer cells, knock-down of multiple H1 variants deregulates many genes, promotes the appearance oF genome-wide accessibility sites and triggers an interFeron response via activation oF heterochromatic repeats.