FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2001556983> ?p ?o ?g. }

• W2001556983 endingPage "933" @default.
• W2001556983 startingPage "925" @default.
• W2001556983 abstract "Background & Aims: Barrett’s esophagus is a precursor of esophageal adenocarcinoma. DNA microarrays that enable a genome-wide assessment of gene expression enhance the identification of specific genes as well as gene expression patterns that are expressed by Barrett’s esophagus and adenocarcinoma compared with normal tissues. Barrett’s esophagus length has also been identified as a risk factor for progression to adenocarcinoma, but whether there are intrinsic biological differences between short-segment and long-segment Barrett’s esophagus can be explored with microarrays. Methods: Gene expression profiles for endoscopically obtained biopsy specimens of Barrett’s esophagus or esophageal adenocarcinoma and associated normal esophagus and duodenum were identified for 17 patients using DNA microarrays. Unsupervised and supervised approaches for data analysis defined similarities and differences between the tissues as well as correlations with clinical phenotypes. Results: Each tissue displays a unique expression profile that distinguishes it from others. Barrett’s esophagus and esophageal adenocarcinoma express a unique set of stromal genes that is distinct from normal tissues but similar to other cancers. Adenocarcinoma also showed lower and higher expression for many genes compared with Barrett’s esophagus. No difference in gene expression was found between short-segment and long-segment Barrett’s esophagus. Conclusions: The genome-wide assessment provided by current DNA microarrays reveals many candidate genes and patterns not previously identified. Stromal gene expression in Barrett’s esophagus and adenocarcinoma is similar, indicating that these changes precede malignant transformation. Background & Aims: Barrett’s esophagus is a precursor of esophageal adenocarcinoma. DNA microarrays that enable a genome-wide assessment of gene expression enhance the identification of specific genes as well as gene expression patterns that are expressed by Barrett’s esophagus and adenocarcinoma compared with normal tissues. Barrett’s esophagus length has also been identified as a risk factor for progression to adenocarcinoma, but whether there are intrinsic biological differences between short-segment and long-segment Barrett’s esophagus can be explored with microarrays. Methods: Gene expression profiles for endoscopically obtained biopsy specimens of Barrett’s esophagus or esophageal adenocarcinoma and associated normal esophagus and duodenum were identified for 17 patients using DNA microarrays. Unsupervised and supervised approaches for data analysis defined similarities and differences between the tissues as well as correlations with clinical phenotypes. Results: Each tissue displays a unique expression profile that distinguishes it from others. Barrett’s esophagus and esophageal adenocarcinoma express a unique set of stromal genes that is distinct from normal tissues but similar to other cancers. Adenocarcinoma also showed lower and higher expression for many genes compared with Barrett’s esophagus. No difference in gene expression was found between short-segment and long-segment Barrett’s esophagus. Conclusions: The genome-wide assessment provided by current DNA microarrays reveals many candidate genes and patterns not previously identified. Stromal gene expression in Barrett’s esophagus and adenocarcinoma is similar, indicating that these changes precede malignant transformation. DNA microarrays provide the means to obtain a genome-wide assessment of gene expression. DNA microarrays have been previously used to compare esophageal adenocarcinoma, squamous cell carcinoma, and Barrett’s esophagus and established the presence of unique gene expression profiles capable of discriminating between the tissues.1Selaru F.M. Zou T. Xu Y. Shustova V. Yin J. Mori Y. Sato F. Wang S. Olaru A. Shibata D. Greenwald B.D. Krasna M.J. Abraham J.M. Meltzer S.J. Global gene expression profiling in Barrett’s esophagus and esophageal cancer: a comparative analysis using cDNA microarrays.Oncogene. 2002; 21: 475-478Crossref PubMed Scopus (101) Google Scholar, 2Hansel D.E. Dhara S. Huang R.C. Ashfaq R. Deasel M. Shimada Y. Bernstein H.S. Harmon J. Brock M. Forastiere A. Washington M.K. Maitra A. Montgomery E. CDC2/CDK1 expression in esophageal adenocarcinoma and precursor lesions serves as a diagnostic and cancer progression marker and potential novel drug target.Am J Surg Pathol. 2005; 29: 390-399Crossref PubMed Scopus (49) Google Scholar, 3Gomes L.I. Esteves G.H. Carvalho A.F. Cristo E.B. Hirata Jr, R. Martins W.K. Marques S.M. Camargo L.P. Brentani H. Pelosof A. Zitron C. Sallum R.A. Montagnini A. Soares F.A. Neves E.J. Reis L.F. Expression profile of malignant and nonmalignant lesions of esophagus and stomach: differential activity of functional modules related to inflammation and lipid metabolism.Cancer Res. 2005; 65: 7127-7136Crossref PubMed Scopus (30) Google Scholar, 4Dahlberg P.S. Ferrin L.F. Grindle S.M. Nelson C.M. Hoang C.D. Jacobson B. Gene expression profiles in esophageal adenocarcinoma.Ann Thorac Surg. 2004; 77: 1008-1015Abstract Full Text Full Text PDF PubMed Scopus (35) Google Scholar In contrast to previous studies, which were limited by the diversity of genes and tissues examined, the present work provides a genome-wide determination of gene expression for Barrett’s esophagus, esophageal adenocarcinoma, normal esophagus, and duodenum. The duodenum serves as a control for the intestinal metaplasia characteristic of Barrett’s esophagus. Whether the higher cancer risk associated with long-segment Barrett’s esophagus is secondary to intrinsic differences in biology or the extent of tissue involved is unknown.5Hirota W.K. Loughney T.M. Lazas D.J. Maydonovitch C.L. Rholl V. Wong R.K. Specialized intestinal metaplasia, dysplasia, and cancer of the esophagus and esophagogastric junction: prevalence and clinical data.Gastroenterology. 1999; 116: 277-285Abstract Full Text Full Text PDF PubMed Scopus (458) Google Scholar Because differences in cell phenotype and physiology are associated with concomitant differences in gene expression, DNA microarrays are well suited to evaluate whether differences exist between short-segment and long-segment Barrett’s epithelium. Unselected patients scheduled for endoscopic evaluation for Barrett’s esophagus or esophageal adenocarcinoma were enrolled to participate in the study. Biopsy specimens were obtained according to the Seattle protocol using a standard esophagogastroduodenoscope (Olympus GIF-XV10; Center Valley, PA) and biopsy forceps (Radial Jaw 3; Boston Scientific Corp, Natick, MA). Four biopsy specimens each were obtained from normal-appearing esophagus (proximal to Barrett’s esophagus), salmon-colored Barrett’s esophagus, adenocarcinoma (if present), and duodenum. Twin biopsy specimens were also obtained for each sample of Barrett’s esophagus and sent for pathologic analysis. Adenocarcinoma samples were also confirmed by pathologic analysis. Duplicate microarrays were performed for one patient (sample 677 normal). All procedures were performed with patient consent and under approved human subjects protocols from Stanford University and the Palo Alto Veterans Affairs Health Care System. Cell lines were derived from human esophageal adenocarcinomas associated with Barrett’s metaplasia (Seg-1 and OE33), a poorly differentiated adenocarcinoma (TE7), and a squamous cell carcinoma (OE21). Seg-16Soldes O.S. Kuick R.D. Thompson II, I.A. Hughes S.J. Orringer M.B. Iannettoni M.D. Hanash S.M. Beer D.G. Differential expression of Hsp27 in normal oesophagus, Barrett’s metaplasia and oesophageal adenocarcinomas.Br J Cancer. 1999; 79: 595-603Crossref PubMed Scopus (106) Google Scholar cells (from Dr David Beer, University of Michigan, Ann Arbor, MI) were grown at 5% CO2 in Dulbecco’s modified Eagle medium with 4.5 g/L glucose and L-glutamine (Cellgro; Mediatech, Inc, Herndon, VA), penicillin (100 U/mL), streptomycin (100 U/mL), and 10% fetal bovine serum. The OE21 and OE337Rockett J.C. Larkin K. Darnton S.J. Morris A.G. Matthews H.R. Five newly established oesophageal carcinoma cell lines: phenotypic and immunological characterization.Br J Cancer. 1997; 75: 258-263Crossref PubMed Scopus (101) Google Scholar cell lines (European Collection of Cell Cultures, Wiltshire, England) and TE78Nishihira T. Hashimoto Y. Katayama M. Mori S. Kuroki T. Molecular and cellular features of esophageal cancer cells.J Cancer Res Clin Oncol. 1993; 119: 441-449Crossref PubMed Scopus (213) Google Scholar cells (Dr T. Nishihira, Second Department of Surgery, Tohoku University School of Medicine, Sendai, Japan) were grown in RPMI 1640 with 25 mmol/L HEPES, 10% fetal bovine serum, and penicillin and streptomycin (100 U/mL). Total RNA (20–120 μg) was obtained using TRIzol (Invitrogen, Carlsbad, CA) and amplified one round as antisense RNA (Message Amp II; Ambion, Inc, Austin, TX). Amplified commercial human reference RNA served as an internal standard (Universal Human Reference RNA; Stratagene Corp, La Jolla, CA). DNA microarrays were produced at the Stanford Functional Genomics Facility (http://www.microarray.org), where protocols for the production of microarrays, array postprocessing, and hybridization can be found.9Alizadeh A.A. Eisen M.B. Davis R.E. Lossos I.S. Rosenwald A. Boldrick J.C. Sabet H. Tran T. Yu X. Powell J.I. Yang L. Marti G.E. Moore T. Hudson Jr, J. Lu L. Lewis D.B. Tibshiranl R. Sherlock G. Chan W.C. Greiner T.C. Weisenburger D.D. Armitage J.O. Warnke R. Levy R. Wilson W. Grever M.R. Byrd J.C. Botstein D. Brown P.O. Staudt L.M. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.Nature. 2000; 403: 503-511Crossref PubMed Scopus (7948) Google Scholar, 10Perou C.M. Sorlie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Rees C.A. Pollack J.R. Ross D.T. Johnsen H. Akslen L.A. Fluge O. Pergamenschikov A. Williams C. Zhu S.X. Lonning P.E. Borresen-Dale A.L. Brown P.O. Botstein D. Molecular portraits of human breast tumours.Nature. 2000; 406: 747-752Crossref PubMed Scopus (11569) Google Scholar RNA from each sample was labeled with Cy5–deoxyuridine triphosphate and the RNA reference with Cy3–deoxyuridine triphosphate (Amersham Biosciences, GE Healthcare, Piscataway, NJ). Each microarray is composed of ∼42,000 complementary DNA spots representing ∼27,000 unique genes. Analysis of the scanned images was performed using GenePix version 5.0 (Axon Instruments, Molecular Devices Corp, Sunnyvale, CA), and spots of poor quality were flagged for exclusion from further analysis. The data were deposited in the Stanford Microarray Database (http://genome-www5.stanford.edu) as the log base 2 ratio of the Cy5/Cy3 signal intensities and normalized with respect to the overall signal intensity for each channel.11Sherlock G. Hernandez-Boussard T. Kasarskis A. Binkley G. Matese J.C. Dwight S.S. Kaloper M. Weng S. Jin H. Ball C.A. Eisen M.B. Spellman P.T. Brown P.O. Botstein D. Cherry J.M. The Stanford Microarray Database.Nucleic Acids Res. 2001; 29: 152-155Crossref PubMed Google Scholar Data analysis used an unsupervised hierarchical clustering algorithm that evaluates for similarities in gene expression patterns between individual genes and samples. The results were pseudo-colored and visualized using TreeView.12Eisen M.B. Spellman P.T. Brown P.O. Botstein D. Cluster analysis and display of genome-wide expression patterns.Proc Natl Acad Sci U S A. 1998; 95: 14863-14868Crossref PubMed Scopus (13157) Google Scholar Cell line data were not included in the supervised or unsupervised analysis but were projected alongside the tissue-derived data to assist in the identification of genes expressed by neoplastic cells. The cell line and tissue-derived expression data did use the same common reference and were mean-centered together for each gene. Statistically significant differences in gene expression between predesignated classes were assessed using a permutation of the t statistic incorporated in the Significance Analysis of Microarrays software (SAM).13Tusher V.G. Tibshirani R. Chu G. Significance analysis of microarrays applied to the ionizing radiation response.Proc Natl Acad Sci U S A. 2001; 98: 5116-5121Crossref PubMed Scopus (9719) Google Scholar Another supervised approach using shrunken centroid analysis, which is incorporated into the Prediction Analysis of Microarrays software (PAM), was used to identify genes capable of discriminating between predesignated classes.14Tibshirani R. Hastie T. Narasimhan B. Chu G. Diagnosis of multiple cancer types by shrunken centroids of gene expression.Proc Natl Acad Sci U S A. 2002; 99: 6567-6572Crossref PubMed Scopus (2145) Google Scholar Gene annotations were obtained using SOURCE (http://source.stanford.edu).15Diehn M. Sherlock G. Binkley G. Jin H. Matese J.C. Hernandez-Boussard T. Rees C.A. Cherry J.M. Botstein D. Brown P.O. Alizadeh A.A. SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data.Nucleic Acids Res. 2003; 31: 219-223Crossref PubMed Scopus (353) Google Scholar The entire data set is available through the Stanford Microarray Database (genome-www5.stanford.edu) or the Lowe laboratory Web site (www.stanford.edu/group/lowelab) at Stanford University. Real-time polymerase chain reaction (PCR) was performed essentially as previously described.16Pfaffl M.W. A new mathematical model for relative quantification in real-time RT-PCR.Nucleic Acids Res. 2001; 29: e45Crossref PubMed Scopus (25138) Google Scholar Two-step real-time PCR was used in which complementary DNA was first synthesized using the SuperScript First-Strand Synthesis System (Invitrogen, Carlsbad, CA) followed by PCR amplification with iQ SYBR Green Supermix (Bio-Rad Laboratories, Inc, Richmond, CA) and the iCycler iQ Multicolor Real Time PCR Detection System (Bio-Rad; Hercules, CA). β-actin served as an internal control. Relative gene expression was determined using the Relative Expression Software Tool (available at http://www.gene-quantification.info/).17Pfaffl M.W. Horgan G.W. Dempfle L. Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR.Nucleic Acids Res. 2002; 30: e36Crossref PubMed Google Scholar In situ hybridizations were performed as previously described.18Iacobuzio-Donahue C.A. Ryu B. Hruban R.H. Kern S.E. Exploring the host desmoplastic response to pancreatic carcinoma: gene expression of stromal and neoplastic cells at the site of primary invasion.Am J Pathol. 2002; 160: 91-99Abstract Full Text Full Text PDF PubMed Scopus (152) Google Scholar Gene expression was evaluated for endoscopically derived tissues obtained from Barrett’s esophagus, esophageal adenocarcinoma, normal esophagus, and duodenum for 17 subjects (Table 1). One of 14 patients (sample 673) with Barrett’s esophagus exhibited high-grade dysplasia. Samples from Barrett’s esophagus adjacent to the tumor mass were obtained from 2 patients (samples B-1 and B-6).Table 1Origin of the Collected SamplesNo. of subjects17 Average age (y)66.5 ± 11.7 No. of men16Total no. of samples48 Normal tissue15 Duodenum14 Barrett’s esophagus14 with dysplasia1 Adenocarcinoma5 Open table in a new tab Gene expression profiles were also determined for esophageal adenocarcinoma and squamous carcinoma cell lines. The gene expression profiles of cancer cell lines largely reflect the tumor of origin and thus were used to help define whether the source of gene expression was the neoplastic cell or associated mesenchymal cells.19Ross D.T. Scherf U. Eisen M.B. Perou C.M. Rees C. Spellman P. Iyer V.R. Jeffrey S.S. van de Rijn M. Waltham M. Pergamenschikov A. Lee J.C.F. Lashkari D. Shalon D. Myers T.G. Weinstein J.N. Botstein D. Brown P.O. Systematic variation in gene expression patterns in human cancer cell lines.Nat Genet. 2000; 24: 227-235Crossref PubMed Scopus (1816) Google Scholar The cell lines were not incorporated into unsupervised and supervised analysis because certain genes that are enhanced by in vitro propagation could potentially distort the clustering analysis. An unsupervised hierarchical clustering approach was first used to characterize similarities in gene expression patterns among the 48 samples (Figure 1). Genes displaying similar expression patterns across many samples were clustered together in rows. Likewise, samples were clustered in columns based on similarities in gene expression profiles. Except for 2 samples, the clustering was consistent with their tissue of origin as defined by endoscopy and pathology. Sample B-6 endoscopically appeared to be Barrett’s esophagus but clustered with the adenocarcinomas and adjacent to the tumor derived from the same patient. Sample 680 clustered with Barrett’s esophagus but was determined by pathologic analysis to be invasive poorly differentiated adenocarcinoma. Gene clusters were identified that contained genes known to be specifically expressed by their tissue of origin (Figure 1, Figure 2). SAM analysis produced ranked lists of genes that are enriched in the normal esophagus, duodenum, Barrett’s esophagus, and adenocarcinoma (Supplementary Tables 1 and 2; see supplemental material online at www.gastrojournal.org). SAM analysis identified 648 genes with a 4-fold difference in expression between Barrett’s esophagus and normal-appearing esophagus. PAM analysis identified AGR2 alone as sufficient to accurately classify all the samples of Barrett’s esophagus from normal tissues (Supplementary Table 2, sheets 2 and 3; see supplemental material online at www.gastrojournal.org). Prominent among the 157 genes significantly expressed at higher levels in Barrett’s esophagus and adenocarcinomas are stromal genes such as the collagens (COL3A1, COL5A2, COL6A1, COL12A1) and CSPG2 (Supplementary Table 2, sheet 4; see supplemental material online at www.gastrojournal.org). Recent studies identified a set of stromal genes whose expression possesses prognostic significance for patients with breast cancer.20West R.B. Nuyten D.S. Subramanian S. Nielsen T.O. Corless C.L. Rubin B.P. Montgomery K. Zhu S. Patel R. Hernandez-Boussard T. Goldblum J.R. Brown P.O. Vijver M.V. Rijn M.V. Determination of stromal signatures in breast carcinoma.PLoS Biol. 2005; 3: e187Crossref PubMed Scopus (175) Google Scholar A total of 151 of the genes were also expressed in the present data set and correctly classified 16 of 17 patient samples with Barrett’s esophagus or adenocarcinoma within a single cluster (Figure 3 and Supplementary Table 3; see supplemental material online at www.gastrojournal.org). A cluster of 37 stromal genes showed higher expression in adenocarcinomas and Barrett’s esophagus and not in normal esophageal tissue. In situ hybridization was performed for 2 stromal genes in this cluster, collagen 5A2 (COL5A2) and periostin (POSTN), that also ranked high for expression in adenocarcinomas and Barrett’s esophagus by SAM analysis (Supplementary Table 2; see supplemental material online at www.gastrojournal.org). In situ hybridization showed enhanced expression in stromal cells for POSTN and COL5A2 (Figure 4).Figure 4In situ hybridization for (A and B) collagen 5A2 (COL5A2) and (C and D) periostin (POSTN). RNA probes were generated with PCR for COL5A2 (forward, 5′-GTATTGAGACACAAGGGGACCT-3′; reverse, 5′-TTATTATTTTTCCTTTAATGATGGTG-3′) and POSTN (forward, 5′-TCCTGTTCCCAAGTCCAAA-3′; reverse, 5′-TCAAATCGAAGAGTTGTGAACTG-3′). The resultant riboprobe was hybridized to sections of (A and C) Barrett’s esophagus and (B and D) normal-appearing esophagus from the same patient. Arrowheads point to collections of stromal cells. (Original magnification 200×.)View Large Image Figure ViewerDownload (PPT) SAM analysis identified 214 genes that are positively expressed at least 4-fold in adenocarcinomas compared with Barrett’s esophagus (Supplementary Table 2; see supplemental material online at www.gastrojournal.org). The same analysis identified 829 genes that are negatively expressed in esophageal adenocarcinomas compared with Barrett’s esophagus and includes genes implicated in other epithelial cancers as potential tumor suppressors (Table 2 and Supplementary Table 2, sheet 5; see supplemental material online at www.gastrojournal.org). Quantitative real-time PCR confirmed the expression for 4 genes that may have a regulatory role and include up-regulated (DKK3 and BCAS1) and down-regulated genes (CHES1 and BRD2) in adenocarcinoma compared with Barrett’s esophagus (Figure 5).Table 2Genes Associated With Other Cancers That Are Negatively Expressed in Esophageal AdenocarcinomaGene symbolGene nameReference CHES1Checkpoint suppressor 1 31El-Rifai W. Frierson Jr, H.F. Harper J.C. Powell S.M. Knuutila S. Expression profiling of gastric adenocarcinoma using cDNA array.Int J Cancer. 2001; 92: 832-838Crossref PubMed Scopus (90) Google Scholar, 32Pati D. Keller C. Groudine M. Plon S.E. Reconstitution of a MEC1-independent checkpoint in yeast by expression of a novel human fork head cDNA.Mol Cell Biol. 1997; 17: 3037-3046Crossref PubMed Scopus (90) Google Scholar CDH1E-cadherin 33Becker K.F. Atkinson M.J. Reich U. Becker I. Nekarda H. Siewert J.R. Hofler H. E-cadherin gene mutations provide clues to diffuse type gastric carcinomas.Cancer Res. 1994; 54: 3845-3852PubMed Google Scholar, 34Corn P.G. Heath E.I. Heitmiller R. Fogt F. Forastiere A.A. Herman J.G. Wu T.T. Frequent hypermethylation of the 5′ CpG island of E-cadherin in esophageal adenocarcinoma.Clin Cancer Res. 2001; 7: 2765-2769PubMed Google Scholar, 35Eads C.A. Lord R.V. Kurumboor S.K. Wickramasinghe K. Skinner M.L. Long T.I. Peters J.H. DeMeester T.R. Danenberg K.D. Danenberg P.V. Laird P.W. Skinner K.A. Fields of aberrant CpG island hypermethylation in Barrett’s esophagus and associated adenocarcinoma.Cancer Res. 2000; 60: 5021-5026PubMed Google Scholar APCAdenomatous polyposis coli 36Kawakami K. Brabender J. Lord R.V. Groshen S. Greenwald B.D. Krasna M.J. Yin J. Fleisher A.S. Abraham J.M. Beer D.G. Sidransky D. Huss H.T. Demeester T.R. Eads C. Laird P.W. Ilson D.H. Kelsen D.P. Harpole D. Moore M.B. Danenberg K.D. Danenberg P.V. Meltzer S.J. Hypermethylated APC DNA in plasma and prognosis of patients with esophageal adenocarcinoma.J Natl Cancer Inst. 2000; 92: 1805-1811Crossref PubMed Scopus (322) Google Scholar, 37Sarbia M. Geddert H. Klump B. Kiel S. Iskender E. Gabbert H.E. Hypermethylation of tumor suppressor genes (p16INK4A, p14ARF and APC) in adenocarcinomas of the upper gastrointestinal tract.Int J Cancer. 2004; 111: 224-228Crossref PubMed Scopus (78) Google Scholar BRD2Bromodomain-containing protein 2 38Guo N. Faller D.V. Denis G.V. Activation-induced nuclear translocation of RING3.J Cell Sci. 2000; 113: 3085-3091PubMed Google Scholar BBXBobby sox homolog 39Minami M. Daimon Y. Mori K. Takashima H. Nakajima T. Itoh Y. Okanoue T. Hepatitis B virus-related insertional mutagenesis in chronic hepatitis B patients as an early drastic genetic change leading to hepatocarcinogenesis.Oncogene. 2005; 24: 4340-4348Crossref PubMed Scopus (74) Google Scholar FOXP1Forkhead box P1 40Banham A.H. Beasley N. Campo E. Fernandez P.L. Fidler C. Gatter K. Jones M. Mason D.Y. Prime J.E. Trougouboff P. Wood K. Cordell J.L. The FOXP1 winged helix transcription factor is a novel candidate tumor suppressor gene on chromosome 3p.Cancer Res. 2001; 61: 8820-8829PubMed Google Scholar STK4Serine/threonine kinase 4 41O’Neill E.E. Matallanas D. Kolch W. Mammalian sterile 20-like kinases in tumor suppression: an emerging pathway.Cancer Res. 2005; 65: 5485-5487Crossref PubMed Scopus (46) Google Scholar, 42Cheung W.L. Ajiro K. Samejima K. Kloc M. Cheung P. Mizzen C.A. Beeser A. Etkin L.D. Chernoff J. Earnshaw W.C. Allis C.D. Apoptotic phosphorylation of histone H2B is mediated by mammalian sterile twenty kinase.Cell. 2003; 113: 507-517Abstract Full Text Full Text PDF PubMed Scopus (397) Google Scholar HIPK1Homeodomain interacting protein kinase 1 43Li X. Zhang R. Luo D. Park S.J. Wang Q. Kim Y. Min W. Tumor necrosis factor alpha-induced desumoylation and cytoplasmic translocation of homeodomain-interacting protein kinase 1 are critical for apoptosis signal-regulating kinase 1-JNK/p38 activation.J Biol Chem. 2005; 280: 15061-15070Crossref PubMed Scopus (65) Google Scholar FOXO3AForkhead box O3A 44Medema R.H. Kops G.J. Bos J.L. Burgering B.M. AFX-like Forkhead transcription factors mediate cell-cycle regulation by Ras and PKB through p27kip1.Nature. 2000; 404: 782-787Crossref PubMed Scopus (1216) Google Scholar Open table in a new tab Supervised and unsupervised analysis was performed between samples of short-segment and long-segment Barrett’s esophagus. A total of 12 samples were studied, with 6 long-segment (average, 5.3 [SD, ±2.5] cm) and 6 short-segment (average, 1.6 [SD, ± 0.7] cm) Barrett’s esophagus. Analysis with unsupervised hierarchical clustering and SAM analysis failed to identify any genes whose gene expression was significantly different between short-segment and long-segment Barrett’s esophagus. The expanded genome-wide coverage available with current microarrays was applied to normal, metaplastic, and neoplastic tissues. The resultant gene expression profiles were able to distinguish Barrett’s esophagus, duodenum, normal esophagus, and esophageal adenocarcinoma from each other. For 2 patients, the samples were apparently misclassified. Barrett’s esophagus is often heterogeneous, and because the pathology was inferred from an adjacent biopsy specimen, variations based on sampling error are plausible. Many genes overexpressed in Barrett’s esophagus and adenocarcinoma, such as AGR2, BCAS1, and cyclooxygenase 2 (PTGS2), are also overexpressed by other epithelial cancers, suggesting mutual mechanisms in pathogenesis.21Fletcher G.C. Patel S. Tyson K. Adam P.J. Schenker M. Loader J.A. Daviet L. Legrain P. Parekh R. Harris A.L. Terrett J.A. hAG-2 and hAG-3, human homologues of genes involved in differentiation, are associated with oestrogen receptor-positive breast tumours and interact with metastasis gene C4.4a and dystroglycan.Br J Cancer. 2003; 88: 579-585Crossref PubMed Scopus (154) Google Scholar, 22Thompson D.A. Weigel R.J. hAG-2, the human homologue of the Xenopus laevis cement gland gene XAG- 2, is coexpressed with estrogen receptor in breast cancer cell lines.Biochem Biophys Res Commun. 1998; 251: 111-116Crossref PubMed Scopus (142) Google Scholar, 23Beardsley D.I. Kowbel D. Lataxes T.A. Mannino J.M. Xin H. Kim W.J. Collins C. Brown K.D. Characterization of the novel amplified in breast cancer-1 (NABC1) gene product.Exp Cell Res. 2003; 290: 402-413Crossref PubMed Scopus (27) Google Scholar, 24Collins C. Rommens J.M. Kowbel D. Godfrey T. Tanner M. Hwang S.I. Polikoff D. Nonet G. Cochran J. Myambo K. Jay K.E. Froula J. Cloutier T. Kuo W.L. Yaswen P. Dairkee S. Giovanola J. Hutchinson G.B. Isola J. Kallioniemi O.P. Palazzolo M. Martin C. Ericsson C. Pinkel D. Albertson D. Li W.B. Gray J.W. Positional cloning of ZNF217 and NABC1: genes amplified at 20q13.2 and overexpressed in breast carcinoma.Proc Natl Acad Sci U S A. 1998; 95: 8703-8708Crossref PubMed Scopus (274) Google Scholar These genes and others whose expression increases in esophageal adenocarcinomas compared with Barrett’s esophagus serve as potential markers for risk stratification and diagnosis. A striking finding is the stromal gene expression shared between adenocarcinoma and Barrett’s esophagus, which is not observed in the normal esophagus or duodenum. The results indicate that stromal and extracellular matrix genes associated with tumor growth are expressed long before there is pathologic evidence of dysplasia. Although many stromal genes expressed in adenocarcinomas are likely to be expressed by associated mesenchymal cells and not neoplastic cells, they may still serve as excellent targets for diagnostic or therapeutic studies. Studies of other epithelial tumors support a significant role by the stroma in influencing tumor formation and growth.25Littlepage L.E. Egeblad M. Werb Z. Coevolution of cancer and stromal cellular responses.Cancer Cell. 2005; 7: 499-500Abstract Full Text Full Text PDF PubMed Scopus (99) Google Scholar, 26Coussens L.M. Werb Z. Inflammation and cancer.Nature. 2002; 420: 860-867Crossref PubMed Scopus (11050) Google Scholar Combined with the decreased expression observed for many genes, the results support a model in which the establishment of a specific extracellular matrix is an early event in carcinogenesis that precedes gene inactivation. There were no differences in gene expression patterns between short-segment and long-segment Barrett’s esophagus. It is therefore unlikely that differences in cell type or cell physiology are responsible for the higher risk of transformation to adenocarcinoma by long-segment Barrett’s esophagus. An alternative hypothesis includes the overall extent of disease as a cause of increased risk rather than any intrinsic biological differences in the responsible cells. Download .xls (1.83 MB) Help with xls files Supplementary Table 1Microsoft Excel workbook of differentially expressed genes between duodenum and normal esophagus identified by significance analysis (SAM). Download .xls (3.17 MB) Help with xls files Supplementary Table 2Microsoft Excel workbook containing differentially expressed genes for Barrett's esophagus and esophageal adenocarcinoma as determined by significance analysis (SAM) and analysis using shrunken centroids (PAM). Table of contents for the workbook is on sheet 1. Download .xls (.03 MB) Help with xls files Supplementary Table 3Microsoft Excel workbook listing the stromal genes that are able to discriminate between esophageal adenocarcinoma and Barrett's esophagus after shrunken centroid analysis with PAM software." @default.
• W2001556983 created "2016-06-24" @default.
• W2001556983 creator A5000851669 @default.
• W2001556983 creator A5007337339 @default.
• W2001556983 creator A5013525493 @default.
• W2001556983 creator A5053186275 @default.
• W2001556983 creator A5068488754 @default.
• W2001556983 creator A5081285787 @default.
• W2001556983 date "2006-09-01" @default.
• W2001556983 modified "2023-10-17" @default.
• W2001556983 title "Gene Expression Profiling Reveals Stromal Genes Expressed in Common Between Barrett’s Esophagus and Adenocarcinoma" @default.
• W2001556983 cites W134625928 @default.
• W2001556983 cites W1608780556 @default.
• W2001556983 cites W1947903640 @default.
• W2001556983 cites W1965037168 @default.
• W2001556983 cites W1980648321 @default.
• W2001556983 cites W1982427071 @default.
• W2001556983 cites W1989076816 @default.
• W2001556983 cites W2003265168 @default.
• W2001556983 cites W2006134426 @default.
• W2001556983 cites W2029420654 @default.
• W2001556983 cites W2033057816 @default.
• W2001556983 cites W2036919653 @default.
• W2001556983 cites W2044702943 @default.
• W2001556983 cites W2050183186 @default.
• W2001556983 cites W2066606290 @default.
• W2001556983 cites W2073984866 @default.
• W2001556983 cites W2074418456 @default.
• W2001556983 cites W2082396164 @default.
• W2001556983 cites W2083006984 @default.
• W2001556983 cites W2083954549 @default.
• W2001556983 cites W2086539941 @default.
• W2001556983 cites W2090157467 @default.
• W2001556983 cites W2092288709 @default.
• W2001556983 cites W2097255042 @default.
• W2001556983 cites W2099249565 @default.
• W2001556983 cites W2099373309 @default.
• W2001556983 cites W2108244474 @default.
• W2001556983 cites W2120646148 @default.
• W2001556983 cites W2132322909 @default.
• W2001556983 cites W2133973332 @default.
• W2001556983 cites W2136898497 @default.
• W2001556983 cites W2138550913 @default.
• W2001556983 cites W2144020093 @default.
• W2001556983 cites W2147246240 @default.
• W2001556983 cites W2150926065 @default.
• W2001556983 cites W2157795344 @default.
• W2001556983 cites W2166525118 @default.
• W2001556983 cites W2167196552 @default.
• W2001556983 cites W2171088586 @default.
• W2001556983 cites W2259802687 @default.
• W2001556983 cites W2312335434 @default.
• W2001556983 cites W2412903328 @default.
• W2001556983 cites W4294107304 @default.
• W2001556983 doi "https://doi.org/10.1053/j.gastro.2006.04.026" @default.
• W2001556983 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2575112" @default.
• W2001556983 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/16952561" @default.
• W2001556983 hasPublicationYear "2006" @default.
• W2001556983 type Work @default.
• W2001556983 sameAs 2001556983 @default.
• W2001556983 citedByCount "133" @default.
• W2001556983 countsByYear W20015569832012 @default.
• W2001556983 countsByYear W20015569832013 @default.
• W2001556983 countsByYear W20015569832014 @default.
• W2001556983 countsByYear W20015569832015 @default.
• W2001556983 countsByYear W20015569832016 @default.
• W2001556983 countsByYear W20015569832017 @default.
• W2001556983 countsByYear W20015569832018 @default.
• W2001556983 countsByYear W20015569832019 @default.
• W2001556983 countsByYear W20015569832020 @default.
• W2001556983 countsByYear W20015569832021 @default.
• W2001556983 countsByYear W20015569832022 @default.
• W2001556983 countsByYear W20015569832023 @default.
• W2001556983 crossrefType "journal-article" @default.
• W2001556983 hasAuthorship W2001556983A5000851669 @default.
• W2001556983 hasAuthorship W2001556983A5007337339 @default.
• W2001556983 hasAuthorship W2001556983A5013525493 @default.
• W2001556983 hasAuthorship W2001556983A5053186275 @default.
• W2001556983 hasAuthorship W2001556983A5068488754 @default.
• W2001556983 hasAuthorship W2001556983A5081285787 @default.
• W2001556983 hasBestOaLocation W20015569831 @default.
• W2001556983 hasConcept C104317684 @default.
• W2001556983 hasConcept C105702510 @default.
• W2001556983 hasConcept C121608353 @default.
• W2001556983 hasConcept C150194340 @default.
• W2001556983 hasConcept C16930146 @default.
• W2001556983 hasConcept C18431079 @default.
• W2001556983 hasConcept C2777819096 @default.
• W2001556983 hasConcept C2778589982 @default.
• W2001556983 hasConcept C2781182431 @default.
• W2001556983 hasConcept C2992824209 @default.
• W2001556983 hasConcept C502942594 @default.
• W2001556983 hasConcept C54355233 @default.
• W2001556983 hasConcept C86803240 @default.
• W2001556983 hasConceptScore W2001556983C104317684 @default.
• W2001556983 hasConceptScore W2001556983C105702510 @default.
• W2001556983 hasConceptScore W2001556983C121608353 @default.
• W2001556983 hasConceptScore W2001556983C150194340 @default.

• next