Genome-Wide, Bidirectional CRISPR Screens Identify Mucins As Critical Host Factors Modulating SARS-Cov-2 Infection
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Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
Tnfa-Induced Mucin 4 Expression Elicits Trastuzumab Resistance in HER2-Positive Breast Cancer María F
Published OnlineFirst October 3, 2016; DOI: 10.1158/1078-0432.CCR-16-0970 Cancer Therapy: Clinical Clinical Cancer Research TNFa-Induced Mucin 4 Expression Elicits Trastuzumab Resistance in HER2-Positive Breast Cancer María F. Mercogliano1, Mara De Martino1, Leandro Venturutti1, Martín A. Rivas2, Cecilia J. Proietti1, Gloria Inurrigarro3, Isabel Frahm3, Daniel H. Allemand4, Ernesto Gil Deza5, Sandra Ares5, Felipe G. Gercovich5, Pablo Guzman 6, Juan C. Roa6,7, Patricia V. Elizalde1, and Roxana Schillaci1 Abstract Purpose: Although trastuzumab administration improved the Results: TNFa overexpression turned trastuzumab-sensitive outcome of HER2-positive breast cancer patients, resistance cells and tumors into resistant ones. Histopathologic findings events hamper its clinical benefits. We demonstrated that TNFa revealed mucin foci in TNFa-producing tumors. TNFa induced stimulation in vitro induces trastuzumab resistance in HER2- upregulation of MUC4 that reduced trastuzumab binding to its positive breast cancer cell lines. Here, we explored the mechanism epitope and impaired ADCC. Silencing MUC4 enhanced trastu- of TNFa-induced trastuzumab resistance and the therapeutic zumab binding, increased ADCC, and overcame trastuzumab and strategies to overcome it. trastuzumab-emtansine antiproliferative effects in TNFa-overex- Experimental Design: Trastuzumab-sensitive breast cancer pressing cells. Accordingly, administration of TNFa-blocking cells, genetically engineered to stably overexpress TNFa,and antibodies downregulated MUC4 and sensitized de novo trastu- de novo trastuzumab-resistant tumors, were used to evaluate zumab-resistant breast cancer cells and tumors to trastuzumab. In trastuzumab response and TNFa-blocking antibodies effective- HER2-positive breast cancer samples, MUC4 expression was ness respectively. Immunohistochemistry and antibody-depen- found to be an independent predictor of poor disease-free survival dent cell cytotoxicity (ADCC), together with siRNA strategy, (P ¼ 0.008). -
A Stealth Cloak for Cancer Cells
BMB Rep. 2021; 54(7): 344-355 BMB www.bmbreports.org Reports Invited Mini Review Mucin in cancer: a stealth cloak for cancer cells Dong-Han Wi1, Jong-Ho Cha2,3 & Youn-Sang Jung1,* 1Department of Life Science, Chung-Ang University, Seoul, 06974, 2Department of Biomedical Sciences, College of Medicine, Inha University, Incheon 22212, 3Department of Biomedical Science, Program in Biomedical Science and Engineering, Graduate school, Inha University, Incheon 22212, Korea Mucins are high molecular-weight epithelial glycoproteins and mucinous colorectal carcinoma (MCC) (3). Since tumor growth are implicated in many physiological processes, including epit- sites induce inhospitable conditions for them to survive, helial cell protection, signaling transduction, and tissue home- mucins are suggested as an oncogenic microenvironment that ostasis. Abnormality of mucus expression and structure contri- avoids hypoxia, acidic, and other biological hurdles. The com- butes to biological properties related to human cancer progress- position and structure of mucins enable them to mimic the ion. Tumor growth sites induce inhospitable conditions. Many surface of tumor cells like the surface of normal epithelial cells kinds of research suggest that mucins provide a microenviron- (4). Additionally, the mucus layer captures growth factors or ment to avoid hypoxia, acidic, and other biological conditions cytokines, contributing to cell growth of the tumor. Alter- that promote cancer progression. Given that the mucus layer natively, these properties interfere with the interaction bet- captures growth factors or cytokines, we propose that mucin ween the immune system and tumor cells. Indeed, a high helps to ameliorate inhospitable conditions in tumor-growing concentration of soluble mucins downregulates the motility sites. -
Digitalcommons@UNMC Regulation of the Transmembrane Mucin MUC4
University of Nebraska Medical Center DigitalCommons@UNMC Theses & Dissertations Graduate Studies Fall 12-18-2015 Regulation of the transmembrane mucin MUC4 by Wnt/β-catenin in gastrointestinal cancers Priya Pai University of Nebraska Medical Center Follow this and additional works at: https://digitalcommons.unmc.edu/etd Part of the Biochemistry Commons, and the Molecular Biology Commons Recommended Citation Pai, Priya, "Regulation of the transmembrane mucin MUC4 by Wnt/β-catenin in gastrointestinal cancers" (2015). Theses & Dissertations. 58. https://digitalcommons.unmc.edu/etd/58 This Dissertation is brought to you for free and open access by the Graduate Studies at DigitalCommons@UNMC. It has been accepted for inclusion in Theses & Dissertations by an authorized administrator of DigitalCommons@UNMC. For more information, please contact [email protected]. i Regulation of the transmembrane mucin MUC4 by Wnt/β- catenin in gastrointestinal cancers By PRIYA PAI A DISSERTATION Presented to the Faculty of The University of Nebraska Graduate College In Partial Fulfillment of the Requirements For the Degree of Doctor of Philosophy Department of Biochemistry and Molecular Biology Graduate Program Under the Supervision of Professor Surinder K. Batra University of Nebraska Medical Center Omaha, Nebraska November, 2015 ii Regulation of the transmembrane mucin MUC4 by Wnt/β-catenin in gastrointestinal cancers Priya Pai, PhD. University of Nebraska Medical Center, 2015 Supervisor: Surinder K. Batra, PhD. The transmembrane mucin MUC4 is a high molecular weight glycoprotein that is expressed de novo in pancreatic ductal adenocarcinoma (PDAC). MUC4 has been shown to play a tumor-promoting role in malignancies such as PDAC, ovarian cancer and breast cancer. -
And HPV18-Infected Early Stage Cervical Cancers and Normal
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Virology 331 (2005) 269–291 www.elsevier.com/locate/yviro Gene expression profiles of primary HPV16- and HPV18-infected early stage cervical cancers and normal cervical epithelium: identification of novel candidate molecular markers for cervical cancer diagnosis and therapy Alessandro D. Santina,*, Fenghuang Zhanb, Eliana Bignottia, Eric R. Siegelc, Stefania Cane´ a, Stefania Bellonea, Michela Palmieria, Simone Anfossia, Maria Thomasd, Alexander Burnetta, Helen H. Kaye, Juan J. Romana, Timothy J. O’Briena, Erming Tianb, Martin J. Cannonf, John Shaughnessy Jr.b, Sergio Pecorellig aDivision of Gynecologic Oncology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA bMyeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA cDepartment of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA dDepartment of Pathology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA eDepartment of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA fDepartment of Microbiology and Immunology, University of Arkansas, Little Rock, AR 72205, USA gDivision of Gynecologic Oncology, University of Brescia, Brescia, Italy Received 2 July 2004; returned to author for revision 18 August 2004; accepted 9 September 2004 Available online 21 November 2004 Abstract With the goal of identifying genes with a differential pattern of expression between invasive cervical carcinomas (CVX) and normal cervical keratinocytes (NCK), we used oligonucleotide microarrays to interrogate the expression of 14,500 known genes in 11 primary HPV16 and HPV18-infected stage IB–IIA cervical cancers and four primary normal cervical keratinocyte cultures. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Serial Analysis of Gene Expression in Normal P53 Null Mammary Epithelium
Oncogene (2002) 21, 6366 – 6376 ª 2002 Nature Publishing Group All rights reserved 0950 – 9232/02 $25.00 www.nature.com/onc Serial analysis of gene expression in normal p53 null mammary epithelium C Marcelo Aldaz*,1, Yuhui Hu1, Rachael Daniel1, Sally Gaddis1, Frances Kittrell2 and Daniel Medina2 1The University of Texas M.D. Anderson Cancer Center, Department of Carcinogenesis, Smithville, Texas, TX 78957, USA; 2Baylor College of Medicine Department of Molecular and Cellular Biology, Houston, Texas, TX 77030, USA Much evidence has accumulated implicating the p53 gene function although activating mutations were also as of importance in breast carcinogenesis. However, observed. Usually p53 abnormalities associate with much still remains to be uncovered on the specific poorer clinical outcome. This, likely, is the consequence downstream pathways influenced by this important of the known critical roles of p53 in regulating the cell activator/repressor of transcription. This study investi- cycle, apoptosis, DNA repair and maintaining genome gated the effects of a p53 null genotype on the stability (Levine, 1997). The loss of wild type p53 transcriptome of ‘normal’ mouse mammary epithelium function is clearly an important event in breast using a unique in vivo model of preneoplastic transforma- tumorigenesis as documented both in human and murine tion. We used SAGE for the comparative analysis of p53 systems (Donehower et al., 1995; Elledge and Allred, wild type (wt) and null mammary epithelium unexposed 1994). However, the exact mechanisms by which such and exposed to hormonal stimulation. Analysis of the lack of normal gene function leads to cancer formation hormone exposed samples provided a comprehensive view and progression are only beginning to be understood. -
Proteomic Analysis of Cancer and Mesothelial Cells Reveals an Increase in Mucin 5AC During Ovarian Cancer and Peritoneal Interaction
JOURNAL OF PROTEOMICS 103 (2014) 204– 215 Available online at www.sciencedirect.com ScienceDirect www.elsevier.com/locate/jprot Proteomic analysis of cancer and mesothelial cells reveals an increase in Mucin 5AC during ovarian cancer and peritoneal interaction Natasha Musrapa,b, George S. Karagiannisa,b, Punit Saraona,b, Ihor Batruchb, Chris Smithc, Eleftherios P. Diamandisa,b,c,⁎ aDepartment of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada bDepartment of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada cDepartment of Clinical Biochemistry, University Health Network, Toronto, Ontario, Canada ARTICLE INFO ABSTRACT Article history: Ovarian cancer is a highly metastatic disease that is often characterized by widespread Received 4 December 2013 abdominal dissemination. A hallmark of ovarian cancer progression is the attachment of Accepted 27 March 2014 malignant cells to the mesothelium and the formation of invasive peritoneal implants. Available online 12 April 2014 Therefore, delineating factors involved in cancer-peritoneal cell interaction is critical to improving patient survival, as it may lead to the discovery of novel therapeutic targets. As Keywords: such, we aimed to identify proteins that participate in this interaction by comparing the Ovarian cancer secreted proteome of a co-culture model containing ovarian cancer (OVCAR-5) and mesothelial Proteomics cells (LP-9), to their respective monoculture secretomes. In total, 49 proteins were differentially Co-culture secreted during cancer and mesothelial cell contact. Relative mRNA expression of candidates Peritoneum was performed, which revealed a significant increase in MUC5AC gene expression in cancer Metastasis cells cultured in three different co-culture models (OVCAR-5 and LP-9; BG-1 and LP-9; OV-90 and Mucin 5AC LP-9). -
Proteoglycan-Based Diversification of Disease Outcome in Head and Neck
Farnedi et al. BMC Cancer (2015) 15:352 DOI 10.1186/s12885-015-1336-4 RESEARCH ARTICLE Open Access Proteoglycan-based diversification of disease outcome in head and neck cancer patients identifies NG2/CSPG4 and syndecan-2 as unique relapse and overall survival predicting factors Anna Farnedi1†, Silvia Rossi2†, Nicoletta Bertani2, Mariolina Gulli3, Enrico Maria Silini2,4, Maria Teresa Mucignat5, Tito Poli6, Enrico Sesenna6, Davide Lanfranco6, Lucio Montebugnoli7, Elisa Leonardi1, Claudio Marchetti8, Renato Cocchi9,10, Andrea Ambrosini-Spaltro1, Maria Pia Foschini1 and Roberto Perris2,5* Abstract Background: Tumour relapse is recognized to be the prime fatal burden in patients affected by head and neck squamous cell carcinoma (HNSCC), but no discrete molecular trait has yet been identified to make reliable early predictions of tumour recurrence. Expression of cell surface proteoglycans (PGs) is frequently altered in carcinomas and several of them are gradually emerging as key prognostic factors. Methods: A PG expression analysis at both mRNA and protein level, was pursued on primary lesions derived from 173 HNSCC patients from whom full clinical history and 2 years post-surgical follow-up was accessible. Gene and protein expression data were correlated with clinical traits and previously proposed tumour relapse markers to stratify high-risk patient subgroups. Results: HNSCC lesions were indeed found to exhibit a widely aberrant PG expression pattern characterized by a variable expression of all PGs and a characteristic de novo transcription/translation of GPC2, GPC5 and NG2/ CSPG4 respectively in 36%, 72% and 71% on 119 cases. Importantly, expression of NG2/CSPG4, on neoplastic cells and in the intralesional stroma(HazardRatio[HR],6.76,p = 0.017) was strongly associated with loco-regional relapse, whereas stromal enrichment of SDC2 (HR, 7.652, p = 0.007) was independently tied to lymphnodal infiltration and disease-related death. -
Figure S1. Reverse Transcription‑Quantitative PCR Analysis of ETV5 Mrna Expression Levels in Parental and ETV5 Stable Transfectants
Figure S1. Reverse transcription‑quantitative PCR analysis of ETV5 mRNA expression levels in parental and ETV5 stable transfectants. (A) Hec1a and Hec1a‑ETV5 EC cell lines; (B) Ishikawa and Ishikawa‑ETV5 EC cell lines. **P<0.005, unpaired Student's t‑test. EC, endometrial cancer; ETV5, ETS variant transcription factor 5. Figure S2. Survival analysis of sample clusters 1‑4. Kaplan Meier graphs for (A) recurrence‑free and (B) overall survival. Survival curves were constructed using the Kaplan‑Meier method, and differences between sample cluster curves were analyzed by log‑rank test. Figure S3. ROC analysis of hub genes. For each gene, ROC curve (left) and mRNA expression levels (right) in control (n=35) and tumor (n=545) samples from The Cancer Genome Atlas Uterine Corpus Endometrioid Cancer cohort are shown. mRNA levels are expressed as Log2(x+1), where ‘x’ is the RSEM normalized expression value. ROC, receiver operating characteristic. Table SI. Clinicopathological characteristics of the GSE17025 dataset. Characteristic n % Atrophic endometrium 12 (postmenopausal) (Control group) Tumor stage I 91 100 Histology Endometrioid adenocarcinoma 79 86.81 Papillary serous 12 13.19 Histological grade Grade 1 30 32.97 Grade 2 36 39.56 Grade 3 25 27.47 Myometrial invasiona Superficial (<50%) 67 74.44 Deep (>50%) 23 25.56 aMyometrial invasion information was available for 90 of 91 tumor samples. Table SII. Clinicopathological characteristics of The Cancer Genome Atlas Uterine Corpus Endometrioid Cancer dataset. Characteristic n % Solid tissue normal 16 Tumor samples Stagea I 226 68.278 II 19 5.740 III 70 21.148 IV 16 4.834 Histology Endometrioid 271 81.381 Mixed 10 3.003 Serous 52 15.616 Histological grade Grade 1 78 23.423 Grade 2 91 27.327 Grade 3 164 49.249 Molecular subtypeb POLE 17 7.328 MSI 65 28.017 CN Low 90 38.793 CN High 60 25.862 CN, copy number; MSI, microsatellite instability; POLE, DNA polymerase ε. -
Protein Profile and Simulated Digestive Behavior of Breast Milk
foods Article Protein Profile and Simulated Digestive Behavior of Breast Milk from Overweight and Normal Weight Mothers Silvia Sánchez-Hernández 1, Laëtitia Théron 2, Pablo Jiménez-Barrios 3 , Manuel Olalla-Herrera 1,4 , Isidra Recio 3 and Beatriz Miralles 3,* 1 Departamento de Nutrición y Bromatología, University of Granada, 18071 Granada, Spain; [email protected] (S.S.-H.); [email protected] (M.O.-H.) 2 Institut National de Recherche Pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), UR370 Qualité des Produits Animaux, F-63122 Saint Genès-Champanelle, France; [email protected] 3 Instituto de Investigación en Ciencias de la Alimentación, CIAL, (CSIC-UAM), Nicolás Cabrera 9, 28049 Madrid, Spain; [email protected] (P.J.-B.); [email protected] (I.R.) 4 Instituto de Investigación Biosanitaria ibs. GRANADA, University of Granada, 18071 Granada, Spain * Correspondence: [email protected]; Tel.: +34-910017932 Abstract: Human milk proteins have shown to vary in concentration and distribution through lactation. However, while some regulatory components, such as hormones, have shown associations with regard to the mothers’ body mass index, there is limited information on the possible influence of this condition on the whole protein distribution. The objective of this study was to evaluate the protein profile of human milk from normal weight and overweight or obese mothers to identify differences in protein expression in colostrum, transitional and mature milk. The mass spectrometry analysis showed the ability to class with a high degree of confidence the lactation state and the milk profile according to the mother’s condition. Individual milk samples were subjected to a digestion Citation: Sánchez-Hernández, S.; in vitro model that takes into account the specificities of the gastrointestinal conditions of full-term Théron, L.; Jiménez-Barrios, P.; newborn infants. -
Supplemental Information For
Supplemental Information for: CLASSIFICATION OF PEDIATRIC ACUTE LYMPHOBLASTIC LEUKEMIA BY GENE EXPRESSION PROFILING Mary E. Ross1, Xiaodong Zhou2, Guangchun Song2, Sheila A. Shurtleff2, Kevin Girtman2, W. Kent Williams2, Hsi-Che Liu2, Rami Mahfouz2, Susana C. Raimondi2, Noel Lenny2, Anami Patel2, & James R. Downing2,* 1 Table of Contents Section I: Patient Dataset Diagnostic ALL samples used for class prediction Subgroup distribution of ALL cases Section II: Methods Hybridization of microarrays Statistical methods Section III: Genetic Subtype Discriminating Genes Top 100 chi-square probe sets selected for BCR-ABL decision tree format Top 100 chi-square probe sets selected for E2A-PBX1 decision tree format Top 100 chi-square probe sets selected for Hyperdiploid >50 decision tree format Top 100 chi-square probe sets selected for MLL decision tree format Top 100 chi-square probe sets selected for T-ALL decision tree format Top 100 chi-square probe sets selected for TEL-AML1 decision tree format Top 100 chi-square probe sets selected for BCR-ABL parallel format Top 100 chi-square probe sets selected for E2A-PBX1 parallel format Top 100 chi-square probe sets selected for Hyperdiploid >50 parallel format Top 100 chi-square probe sets selected for MLL parallel format Top 100 chi-square probe sets selected for T-ALL parallel format Top 100 chi-square probe sets selected for TEL-AML1 parallel format Section IV: Diagnostic Accuracy Training and test set results Cross comparison of supervised learning algorithms Section V: Comparison of Expression Profiles and Real-time PCR (Taqman) Section VI: References 2 I: Patient Dataset 132 cases of pediatric ALL were selected from the original 327 diagnostic bone marrow aspirates1 to reanalyze on the higher density U133A and B microarrays.