DOCSLIB.ORG

Loss of Epithelial Membrane Protein-2 Expression Confers an Independent Prognosticator in Nasopharyngeal Carcinoma: a Cohort Study

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Loss of Epithelial Membrane Protein-2 Expression Confers an Independent Prognosticator in Nasopharyngeal Carcinoma: a Cohort Study Open Access Research BMJ Open: first published as 10.1136/bmjopen-2012-000900 on 5 April 2012. Downloaded from Loss of epithelial membrane protein-2 expression confers an independent prognosticator in nasopharyngeal carcinoma: a cohort study Yi-Hsien Chen,1 Li-Ching Wu,2 Wen-Ren Wu,3 Hung-Jung Lin,1 Sung-Wei Lee,4 Ching-Yih Lin,5 Shih-Lun Chang,6 Nan-Haw Chow,7,8 Hsuan-Ying Huang,9 Chien-Feng Li,2,3,10,11 Han-Ping Hsu,12 Yow-Ling Shiue3 To cite: Chen Y-H, Wu L-C, ABSTRACT ARTICLE SUMMARY Wu W-R, et al. Loss of Objective: To evaluate the expression of epithelial epithelial membrane membrane protein-2 (EMP2) protein and its Article focus protein-2 expression confers clinicopathological associations in patients with - an independent Recent studies have suggested that EMP2 plays nasopharyngeal carcinoma. prognosticator in a tumour suppressor role in B cell lymphomas. nasopharyngeal carcinoma: Design: Retrospective population-based cohort study. - Immunoexpression of EMP2 was retrospectively a cohort study. BMJ Open Setting: This study was based on a biobank in Chi-Mei assessed in biopsies of 124 consecutive patients 2012;2:e000900. Medical Center (Tainan, Taiwan) from 1993 to 2002. with nasopharyngeal carcinoma. doi:10.1136/ Participants: Biopsies of 124 consecutive bmjopen-2012-000900 nasopharyngeal carcinoma patients without initial Key messages - Loss of EMP2 expression significantly correlates distant metastasis and treated with consistent < Prepublication history for with advanced primary tumour, nodal status and guidelines were assessed. Immunoexpressions of this paper is available online. AJCC stage. To view these files please EMP2 were analysed and the outcomes were correlated - In multivariate analyses, loss of EMP2 expres- visit the journal online (http:// with clinicopathological features and patient survivals. sion emerges as an independent prognosticator dx.doi.org/10.1136/ Primary and secondary outcome bmjopen-2012-000900). for worse disease-specific survival and local http://bmjopen.bmj.com/ measures: Immunoexpressions of EMP2 were recurrence-free survival. analyzed and the outcomes were correlated with Received 21 January 2012 clinicopathological features and patient survivals. Accepted 27 February 2012 Strengths and limitations of this study Results: Loss of EMP2 expression (49.2%) was - Significant correlation between loss of EMP2 This final article is available correlated with advanced primary tumour (p¼0.044), expression and several clinicopathologic vari- for use under the terms of nodal status (p¼0.045) and the 7th American Joint ables supported its potential role in nasopharyn- the Creative Commons Committee on Cancer stage (p¼0.027). In multivariate geal carcinomas. Attribution Non-Commercial analyses, loss of EMP2 expression emerged as an - The molecular mechanisms underlying EMP2 2.0 Licence; see independent prognosticator for worse disease-specific action require to be elucidated. on September 29, 2021 by guest. Protected copyright. http://bmjopen.bmj.com survival (DSS; p¼0.015) and local recurrence-free survival (LRFS; p¼0.030), along with the American non-keratinising carcinoma types, according Joint Committee on Cancer stages IIIeIV (p¼0.034, DSS; p¼0.023, LRFS). to current WHO tumour classification, although genetic and environmental factors Conclusions: Loss of EMP2 expression is common 124 and associated with adverse prognosticators and also play certain roles in pathogenesis. The might confer tumour aggressiveness through advances in diagnostic imaging, radiation hampering its interaction with specific membrane therapy and adjuvant chemotherapy of NPC protein(s) and hence the downstream signal have achieved better locoregional control, transduction pathway(s). while it appears less satisfactory in final treat- ment outcomes.56Even though being an important parameter, Tumour, Node, Metas- tasis staging still has space to improve in terms INTRODUCTION of providing the optimal prognostication to 157 For numbered affiliations see Nasopharyngeal carcinoma (NPC) is an the patients. Therefore, to identify end of article. endemic head and neck epithelial malignancy potential biomarkers with better correlation to in Southeastern Asia and Taiwan, strongly tumour growth and/or treatment outcomes in e 1e3 Correspondence to linked to Epstein Barr virus (EBV). The patients with NPC, subsequently, to aid in risk Professor Yow-Ling Shiue; latter association is especially authentic for stratification and perhaps development of [email protected] the differentiated and undifferentiated therapeutic targets, are indispensable. Chen Y-H, Wu L-C, Wu W-R, et al. BMJ Open 2012;2:e000900. doi:10.1136/bmjopen-2012-000900 1 EMP2 low expression in nasopharyngeal carcinoma BMJ Open: first published as 10.1136/bmjopen-2012-000900 on 5 April 2012. Downloaded from Human epithelial membrane protein-2 gene (EMP2), of EMP2 was scored by two pathologists (C-FL and mapped to chromosome 16, is highly conserved across H-YH) using a multiheaded microscope to reach e vertebrates.8 10 The expression pattern of EMP2 partially a consensus for each case without prior knowledge of overlaps to that of the peripheral myelin protein 22 clinical and follow-up information. The percentage of (PMP22, also known as the growth arrest-specific-3, tumour cells with EMP2 immunoexpression was GAS3) transcript. By containing the claudin domain and recorded for each specimen and loss of EMP2 expres- sharing approximately 40% amino acid identity with sion (negative) was defined in cases with staining #5% PMP22/GAS3,11 the EMP2 protein was detected as tumour cells (see the Statistical analysis section). a novel member of this four-transmembrane (tetraspan) superfamily.12 In humans, EMP2 has a discrete cell type Treatment and follow-up and tissue distribution, with high levels observed in the All 124 patients with follow-up for outcome have lung and moderate levels in the eye, heart, thyroid, received complete course of radiotherapy (RT, total dose uterus and intestine.11 13 14 Functionally, the best $7000 cGy) and also cisplatin-based chemotherapy in understood tetraspan proteins are connexins, which those of stage IIeIV diseases, based on the previously form the major structural element of gap junctions. published protocol.16 The method of RT was in general Connexins play important roles in the regulation of cell uniform within this period. All patients were regularly growth and differentiation. Cancer cells usually have monitored after RT until death or their last appointment downregulated levels of gap junctions, and several lines with the mean follow-up duration being 59.6 months of evidence suggest that loss of gap junctional intercel- (range: 4e117). lular communication is an important step in carcino- genesis. Re-expression of connexins in cancer cells causes Statistical analysis normalisation of cell growth control and reduced tumour Statistics were performed using SPSS V.14.0 software 2 growth.15 Accordingly, we aimed to systematically analyse (SPSS Inc). c Test was used to compare the EMP2 EMP2 immunoexpression in patients with NPC and expression status and various clinicopathological identified that loss of EMP2 expression is associated with parameters. The end points analysed were disease- adverse prognosticators, conferring to poor survivals. specific survival (DSS) and local recurrence-free survival (LRFS), calculated from the starting date of RT to the MATERIALS AND METHODS Patients and tumour specimens Table 1 Clinical pathological features of 124 The institutional review board approved the study by nasopharyngeal carcinomas using formalin-fixed tissue of NPC for this study (IRB100-09-003). Available paraffin-embedded tissue Variable n (%) http://bmjopen.bmj.com/ blocks were retrieved from 124 NPC patients who Gender underwent biopsy between January 1993 and December Male 95 (76.6) 2002. These patients were free of distant metastasis at Female 29 (23.4) initial presentation. The histological subtypes were Age (years) reappraised according to the current WHO classification <60 98 (79.0) $ and, the tumour staging was re-evaluated with the 7th 60 26 (21.0) American Joint Committee on Cancer (AJCC) system by Primary tumour (T) T1 30 (24.2) on September 29, 2021 by guest. Protected copyright. two pathologists, independently. T2 50 (40.3) Immunohistochemical staining and assessment of EMP2 T3 21 (16.9) T4 23 (18.5) expression m Nodal status (N) Tissue sections of 3 m thickness were cut onto N0 24 (19.4) precoated slides from paraffin-embedded tissue blocks N1 32 (25.8) and were next routinely deparaffinized with xylene and N2 48 (38.7) rehydrated with ethanol washes. Slides were heated by N3 20 (16.1) the microwave in a 10 mM citrate buffer (pH 6.0) for Stage 7 min to retrieve antigens. Endogenous peroxidase was I 7 (5.6) blocked with 3% H2O2. Slides were next washed by Tris- II 31 (25.0) buffered saline for 15 min and subsequently incubated III 46 (37.1) with a rabbit polyclonal primary antibody targeting IV 40 (32.2) Histological grade EMP2 (Atlas Antibodies, Stockholm, Sweden) at a dilu- Keratinising 5 (4.0) tion of 1:75 for 1 h. Primary antibodies were detected Non-keratinising/differentiated 54 (43.5) using the DAKO ChemMate EnVision Kit (K5001, Non-keratinising/undifferentiated 65 (52.4) Carpinteria, California, USA). The slides were incubated EMP2 expression level and developed with the secondary antibody for 30 min Positive (>5% tumour cells) 63 (50.8) and 3,3-diaminobenzidine for 5 min, followed by coun- Negative (#5% tumour cells) 61 (49.2) terstained using Gill’s haematoxylin. Immunoexpression 2 Chen Y-H, Wu L-C, Wu W-R, et al. BMJ Open 2012;2:e000900. doi:10.1136/bmjopen-2012-000900 EMP2 low expression in nasopharyngeal carcinoma BMJ Open: first published as 10.1136/bmjopen-2012-000900 on 5 April 2012. Downloaded from Figure 1 Immunohistochemically non-tumour respiratory epithelium (A) and those with squamous metaplasia (B) demonstrate diffuse and strong EMP2 immunoexpression, which can also be appreciated in representative non-keratinising carcinoma (C) but not in undifferentiated one (D). date of event developed. Patients lost to follow-up were showed characteristic EMP2 staining (>5% tumour cells; censored on the latest follow-up date.
Load more

Recommended publications
  • Primepcr™Assay Validation Report
    PrimePCR™Assay Validation Report Gene Information Gene Name epithelial membrane protein 2 Gene Symbol Emp2 Organism Rat Gene Summary Description Not Available Gene Aliases Not Available RefSeq Accession No. Not Available UniGene ID Rn.21730 Ensembl Gene ID ENSRNOG00000002664 Entrez Gene ID 360468 Assay Information Unique Assay ID qRnoCIP0024746 Assay Type Probe - Validation information is for the primer pair using SYBR® Green detection Detected Coding Transcript(s) ENSRNOT00000003615 Amplicon Context Sequence CCTGCTGCCTTCGCTGCCCTGTGAACATGTTGGTGATTCTTGCCTTCATCATCGT CTTCCACATCGTGTCTACGGCACTCTTGTTCATTTCAACCATTGACAATGCCTGG TGGGTAGGAGATGGCTTCTCAGCT Amplicon Length (bp) 104 Chromosome Location 10:4276703-4281842 Assay Design Intron-spanning Purification Desalted Validation Results Efficiency (%) 99 R2 0.9989 cDNA Cq 20.98 cDNA Tm (Celsius) 82.5 gDNA Cq Specificity (%) 100 Information to assist with data interpretation is provided at the end of this report. Page 1/4 PrimePCR™Assay Validation Report Emp2, Rat Amplification Plot Amplification of cDNA generated from 25 ng of universal reference RNA Melt Peak Melt curve analysis of above amplification Standard Curve Standard curve generated using 20 million copies of template diluted 10-fold to 20 copies Page 2/4 PrimePCR™Assay Validation Report Products used to generate validation data Real-Time PCR Instrument CFX384 Real-Time PCR Detection System Reverse Transcription Reagent iScript™ Advanced cDNA Synthesis Kit for RT-qPCR Real-Time PCR Supermix SsoAdvanced™ SYBR® Green Supermix Experimental Sample qPCR Reference Total RNA Data Interpretation Unique Assay ID This is a unique identifier that can be used to identify the assay in the literature and online. Detected Coding Transcript(s) This is a list of the Ensembl transcript ID(s) that this assay will detect.
    [Show full text]
  • (12) United States Patent (10) Patent No.: US 7.873,482 B2 Stefanon Et Al
    US007873482B2 (12) United States Patent (10) Patent No.: US 7.873,482 B2 Stefanon et al. (45) Date of Patent: Jan. 18, 2011 (54) DIAGNOSTIC SYSTEM FOR SELECTING 6,358,546 B1 3/2002 Bebiak et al. NUTRITION AND PHARMACOLOGICAL 6,493,641 B1 12/2002 Singh et al. PRODUCTS FOR ANIMALS 6,537,213 B2 3/2003 Dodds (76) Inventors: Bruno Stefanon, via Zilli, 51/A/3, Martignacco (IT) 33035: W. Jean Dodds, 938 Stanford St., Santa Monica, (Continued) CA (US) 90403 FOREIGN PATENT DOCUMENTS (*) Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 WO WO99-67642 A2 12/1999 U.S.C. 154(b) by 158 days. (21)21) Appl. NoNo.: 12/316,8249 (Continued) (65) Prior Publication Data Swanson, et al., “Nutritional Genomics: Implication for Companion Animals'. The American Society for Nutritional Sciences, (2003).J. US 2010/O15301.6 A1 Jun. 17, 2010 Nutr. 133:3033-3040 (18 pages). (51) Int. Cl. (Continued) G06F 9/00 (2006.01) (52) U.S. Cl. ........................................................ 702/19 Primary Examiner—Edward Raymond (58) Field of Classification Search ................... 702/19 (74) Attorney, Agent, or Firm Greenberg Traurig, LLP 702/23, 182–185 See application file for complete search history. (57) ABSTRACT (56) References Cited An analysis of the profile of a non-human animal comprises: U.S. PATENT DOCUMENTS a) providing a genotypic database to the species of the non 3,995,019 A 1 1/1976 Jerome human animal Subject or a selected group of the species; b) 5,691,157 A 1 1/1997 Gong et al.
    [Show full text]
  • Supplementary Data
    Supplemental figures Supplemental figure 1: Tumor sample selection. A total of 98 thymic tumor specimens were stored in Memorial Sloan-Kettering Cancer Center tumor banks during the study period. 64 cases corresponded to previously untreated tumors, which were resected upfront after diagnosis. Adjuvant treatment was delivered in 7 patients (radiotherapy in 4 cases, cyclophosphamide- doxorubicin-vincristine (CAV) chemotherapy in 3 cases). 34 tumors were resected after induction treatment, consisting of chemotherapy in 16 patients (cyclophosphamide-doxorubicin- cisplatin (CAP) in 11 cases, cisplatin-etoposide (PE) in 3 cases, cisplatin-etoposide-ifosfamide (VIP) in 1 case, and cisplatin-docetaxel in 1 case), in radiotherapy (45 Gy) in 1 patient, and in sequential chemoradiation (CAP followed by a 45 Gy-radiotherapy) in 1 patient. Among these 34 patients, 6 received adjuvant radiotherapy. 1 Supplemental Figure 2: Amino acid alignments of KIT H697 in the human protein and related orthologs, using (A) the Homologene database (exons 14 and 15), and (B) the UCSC Genome Browser database (exon 14). Residue H697 is highlighted with red boxes. Both alignments indicate that residue H697 is highly conserved. 2 Supplemental Figure 3: Direct comparison of the genomic profiles of thymic squamous cell carcinomas (n=7) and lung primary squamous cell carcinomas (n=6). (A) Unsupervised clustering analysis. Gains are indicated in red, and losses in green, by genomic position along the 22 chromosomes. (B) Genomic profiles and recurrent copy number alterations in thymic carcinomas and lung squamous cell carcinomas. Gains are indicated in red, and losses in blue. 3 Supplemental Methods Mutational profiling The exonic regions of interest (NCBI Human Genome Build 36.1) were broken into amplicons of 500 bp or less, and specific primers were designed using Primer 3 (on the World Wide Web for general users and for biologist programmers (see Supplemental Table 2) [1].
    [Show full text]
  • The NIH Catalyst from the Deputy Director for Intramural Research
    — Fostering Communication and Collaboration The nihCatalyst A Publication for NIH Intramural Scientists National Institutes of Health Office of the Director Volume 15 Issue 6 November-Dece.mber i , 2007 Research Festival Research Festival of Age: Getting to the Bottom Coming Tissue Engineering and Regenerative Medicine Of the Beta Cell by Fran Pollner by Julie Wallace or some, the quest is to increase the progenitor pool of pancre- anel chair Rocky F atic beta cells, to derive stem Tuan noted that cells that can be controlled in cul- P this was the NIH ture and serve as replacements for Research Festival’s damaged or lost beta cells; for oth- first dedicated sympo- ers, the quest is for new treatments. sium on tissue engi- neering and regenera- Stem Cell Studies tive medicine, a re- Typically, cul- flection that the field tured human beta is steadily approach- cells do not prolif- ing the threshold of erate well or retain clinical application. the mature pheno- Indeed, applying type, noted Marvin biological and engi- neering principles to Gershengorn, chief Fran Pollner The Re-Generation: (left to right): Pamela Robey, N1DCR; of the Clinical En- Marvin repairing and replac- Cynthia Dunbar, NHLB1; Catherine Kuo, NIAMS; and panel docrinology Branch Gershengorn ing damaged and de- chair Rocky Tuan, NIAMS and scientific director, NIDDK, who stroyed tissues has at- has been exploring the optimization tracted researchers across NIH; scientists adipocytes, and chondrocytes derived of hIPCs (human islet cell-derived from three institutes described their on- from MSCs could indeed be made to precursor cells) for about five years.
    [Show full text]
  • Yale Computational Biology and Bioinformatics Rotation Guide 2020-2021
    Yale Computational Biology and Bioinformatics Rotation Guide 2020-2021 Julien Berro ............................................................................................................................................................3 Cynthia Brandt .......................................................................................................................................................3 Kei-Hoi Cheung .....................................................................................................................................................4 Chris Cotsapas ........................................................................................................................................................4 Richard Flavell .......................................................................................................................................................4 Joel Gelernter .........................................................................................................................................................5 Mark Gerstein .........................................................................................................................................................6 Antonio Giraldez ....................................................................................................................................................7 Jeffrey Gruen ..........................................................................................................................................................8
    [Show full text]
  • Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
    Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ......................................................
    [Show full text]
  • Table S3: Analysis of Genes Induced in BAHD1 Knockdown HEK213 Cells
    Table S3: Analysis of genes induced in BAHD1 knockdown HEK213 cells. Top networks associated to genes induced in BAHD1 KD cells (Ingenuity Pathways Analysis). Associated Network Functions Molecules in Network Score Focus (Molecules in BAHD1-KD transcriptome in upper case) Molecules Cancer, Cell Cycle, Cellular Growth and Proliferation ALCAM, BCL2L11, Caspase, CDKN1C, CLEC11A, CTH, Cyclin 54 27 A, Cyclin E, DACH1, DSP, ERK, GAL, IGF2, Igfbp, IGFBP7, IL6R, KISS1R, LGALS3, Mmp, NEFM, PDGF BB, PHLDA1, Rb, RBL1, RET, RUNX2, SCARA3, SEPP1, SLC6A6, SOX8, SULF1, TAC1, TACSTD1, VCAN, WWP1 Immune Response, Respiratory Disease, Organismal Injury and ADCYAP1R1, ALOX5, Ap1, ATF1, CaMKII, COL13A1, Creb, 39 21 Abnormalities F12, F2R, FSH, hCG, IL1, INDO, ITCH, LDL, MEOX1, NFkB, NID1, NR2F2, P38 MAPK, Pka, Pkc(s), PLA2G7, PLAU, PLC, PLCD3, PRKAR1A, RAP2B, RIPK2, S1PR3, SUMO1, TANK, Tgf beta, TIMP2, Vegf Top Molecular and Cellular Functions associated to genes induced in BAHD1 KD cells (Ingenuity Pathways Analysis). Category Molecules p-value # Molecules Cell Death SAT1, IL6R, PRKAR1A, PHLDA2, RASL10A, PHLDA1, S1PR3, 1,56E-04 - 1,90E-02 43 DSP, IGF2, ADCYAP1R1, ALOX5, QKI, LGALS3, RIPK2, IGFBP7, RUNX2, CDKN1C, PLA2G7, STEAP3, F2R, PLAU, SULF1, KAT2B, RET, BCL2L11, CTH, ATF1, RBL1, DACH1, RTN1, GAL, VCAN, PACS2, TAC1, SUMO1, HLF, EMP2, CLEC11A, TANK, ACSL4, TIMP2, INDO Cellular Growth and Proliferation F12, SAT1, IL6R, PRKAR1A, SEC14L2, PHLDA2, RASL10A, 2,35E-04 - 1,90E-02 46 PHLDA1, DSP, S1PR3, IGF2, CRLF1, ADCYAP1R1, ALOX5, LAMB1, LGALS3, RIPK2, IGFBP7,
    [Show full text]
  • A Network Inference Approach to Understanding Musculoskeletal
    A NETWORK INFERENCE APPROACH TO UNDERSTANDING MUSCULOSKELETAL DISORDERS by NIL TURAN A thesis submitted to The University of Birmingham for the degree of Doctor of Philosophy College of Life and Environmental Sciences School of Biosciences The University of Birmingham June 2013 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Musculoskeletal disorders are among the most important health problem affecting the quality of life and contributing to a high burden on healthcare systems worldwide. Understanding the molecular mechanisms underlying these disorders is crucial for the development of efficient treatments. In this thesis, musculoskeletal disorders including muscle wasting, bone loss and cartilage deformation have been studied using systems biology approaches. Muscle wasting occurring as a systemic effect in COPD patients has been investigated with an integrative network inference approach. This work has lead to a model describing the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. This model has shown for the first time that oxygen dependent changes in the expression of epigenetic modifiers and not chronic inflammation may be causally linked to muscle dysfunction.
    [Show full text]
  • BGGN 213 Pathway Analysis and the Interpretation of Gene Lists
    BGGN 213 Pathway Analysis and the Interpretation of Gene Lists Barry Grant http://thegrantlab.org/bggn213 My high-throughput experiment generated a long list of genes/proteins… What do I do now? Pathway analysis! (a.k.a. geneset enrichment) Use bioinformatics methods to help extract biological meaning from such lists… Pathway analysis (a.k.a. geneset enrichment) Principle DEGs Pathway Differentially Pathway Expressed (geneset) Genes (DEGs) Enriched Not enriched • Variations of the math: overlap, ranking, networks... ➢ Not critical, different algorithms show similar performances • DEGs come from your experiment ➢ Critical, needs to be as clean as possible • Pathway genes (“geneset”) come from annotations ➢ Important, but typically not a competitive advantage Pathway analysis (a.k.a. geneset enrichment) Limitations • Post-transcriptional regulation is neglected • Directionality is hard to capture sensibly • e.g. IκBα/NF-κB • Tissue-specific variations of pathways are not annotated • e.g. NF-κB regulates metabolism, not inflammation, in adipocytes • Size bias: stats are influenced by the size of the pathway • Geneset annotation bias: can only discover what is already known • Non-model organisms: no high-quality genesets available • Many pathways/receptors converge to few regulators • e.g. tens of innate immune receptors activate 4 TFs: NF-kB, AP-1, IRF3/7, NFAT Starting point for pathway analysis: Your gene list • You have a list of genes/proteins of interest • You have quantitative data for each gene/protein • Fold change 228018_at F26A1.8NP_000192
    [Show full text]
  • A Mechanogenetic Model of Exercise-Induced Pulmonary Haemorrhage in the Thoroughbred Horse
    G C A T T A C G G C A T genes Article A Mechanogenetic Model of Exercise-Induced Pulmonary Haemorrhage in the Thoroughbred Horse Sarah Blott 1,* , Hannah Cunningham 1, Laurène Malkowski 1 , Alexandra Brown 2 and Cyril Rauch 1,* 1 School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington LE12 5RD, UK; [email protected] (H.C.); [email protected] (L.M.) 2 Animal Health Trust, Lanwades Park, Kentford, Newmarket, Suffolk CB8 7UU, UK; [email protected] * Correspondence: [email protected] (S.B.); [email protected] (C.R.) Received: 30 September 2019; Accepted: 30 October 2019; Published: 1 November 2019 Abstract: Exercise-induced pulmonary haemorrhage (EIPH) occurs in horses performing high-intensity athletic activity. The application of physics principles to derive a ‘physical model’, which is coherent with existing physiology and cell biology data, shows that critical parameters for capillary rupture are cell–cell adhesion and cell stiffness (cytoskeleton organisation). Specifically, length of fracture in the capillary is a ratio between the energy involved in cell–cell adhesion and the stiffness of cells suggesting that if the adhesion diminishes and/or that the stiffness of cells increases EIPH is more likely to occur. To identify genes associated with relevant cellular or physiological phenotypes, the physical model was used in a post-genome-wide association study (GWAS) to define gene sets associated with the model parameters. The primary study was a GWAS of EIPH where the phenotype was based on weekly tracheal wash samples collected over a two-year period from 72 horses in a flat race training yard.
    [Show full text]
  • BGGN 213 Pathway Analysis and the Interpretation of Gene Lists Lecture 15
    BGGN 213 Pathway Analysis and the Interpretation of Gene Lists Lecture 15 Barry Grant http://thegrantlab.org/bggn213 Inputs Steps Reads R1 Reads R2 [optional] Control FastQ FastQ 1. Quality Reads R1 Reads R2 Control [optional] FastQC FastQ FastQ Treatment 2. Reference Alignment Genome (Mapping) UCSC Fasta TopHat2 Count Last day’s step Table 4. 3. data.frame Annotation Read Differential Counting expression UCSC GTF Count analysis! CuffLinks Table DESeq2 data.frame Volcano Plot Fold change vs P-value Significant (P < 0.01 & log2 > 2) My high-throughput experiment generated a long list of genes/proteins… What do I do now? Pathway analysis! (a.k.a. geneset enrichment) Use bioinformatics methods to help extract biological meaning from such lists… Inputs Steps Reads R1 Reads R2 [optional] Control FastQ FastQ 1. Quality Reads R1 Reads R2 Control [optional] FastQC 5. Gene set FastQ FastQ enrichment Treatment analysis 2. nalysis! Reference KEGG, GO, … Alignment Genome (Mapping) UCSC Fasta TopHat2 Count Table 4. 3. data.frame Annotation Read Differential Counting expression UCSC GTF Count analysis! CuffLinks Table DESeq2 data.frame Basic idea Differentially Expressed Genes (DEGs) Gene-sets (Pathways, annotations, etc...) Annotate... Basic idea Differentially Expressed Genes (DEGs) Gene-sets (Pathways, annotations, etc...) Annotate... Differentially Pathways Expressed Overlap... Genes (DEGs) Pathway analysis (geneset enrichment) Pathway analysis (a.k.a. geneset enrichment) Principle DEGs Pathway Differentially Pathway Expressed (geneset) Genes (DEGs) Enriched Not enriched • DEGs come from your experiment ➢ Critical, needs to be as clean as possible • Pathway genes (“geneset”) come from annotations ➢ Important, but typically not a competitive advantage • Variations of the math: overlap, ranking, networks..
    [Show full text]
  • A Systems Approach to Mapping Transcriptional Networks Controlling
    Xu et al. BMC Genomics 2010, 11:451 http://www.biomedcentral.com/1471-2164/11/451 RESEARCH ARTICLE Open Access A systems approach to mapping transcriptional networks controlling surfactant homeostasis Yan Xu1,2*, Minlu Zhang2,3, Yanhua Wang1, Pooja Kadambi4, Vrushank Dave1, Long J Lu2,3, Jeffrey A Whitsett1 Abstract Background: Pulmonary surfactant is required for lung function at birth and throughout life. Lung lipid and surfactant homeostasis requires regulation among multi-tiered processes, coordinating the synthesis of surfactant proteins and lipids, their assembly, trafficking, and storage in type II cells of the lung. The mechanisms regulating these interrelated processes are largely unknown. Results: We integrated mRNA microarray data with array independent knowledge using Gene Ontology (GO) similarity analysis, promoter motif searching, protein interaction and literature mining to elucidate genetic networks regulating lipid related biological processes in lung. A Transcription factor (TF) - target gene (TG) similarity matrix was generated by integrating data from different analytic methods. A scoring function was built to rank the likely TF-TG pairs. Using this strategy, we identified and verified critical components of a transcriptional network directing lipogenesis, lipid trafficking and surfactant homeostasis in the mouse lung. Conclusions: Within the transcriptional network, SREBP, CEBPA, FOXA2, ETSF, GATA6 and IRF1 were identified as regulatory hubs displaying high connectivity. SREBP, FOXA2 and CEBPA together form a common core regulatory module that controls surfactant lipid homeostasis. The core module cooperates with other factors to regulate lipid metabolism and transport, cell growth and development, cell death and cell mediated immune response. Coordinated interactions of the TFs influence surfactant homeostasis and regulate lung function at birth.
    [Show full text]