Literature DB >> 24427346

Analysis of differentially expressed genes in colorectal adenocarcinoma with versus without metastasis by three-dimensional oligonucleotide microarray.

Rita M A M Moura Franco1, Marcelo M Linhares1, Suzana S Lustosa1, Ismael D G C Silva1, Naiara C N Souza2, Delcio Matos1.   

Abstract

BACKGROUND: Our objective was to examine how the gene expression profile of tumor tissue correlates with lymph node metastasis in patients with advanced colorectal adenocarcinoma (CRAC).
METHODS: We studied 36 patients (20 men and 16 women, 22-90 years of age) treated for CRAC (classifications of T2, T3, or T4; histological grade of G1 or G2). Amplified tumor mRNA samples were exposed to 20,000 human sequence probes and digitized images of the hybridized samples were analyzed.
RESULTS: On average, 2389 probes were detected above the background, with an average correlation R value of 0.19 between data from different patient groups (with or without lymph node invasion, colon or rectal, with or without angio-lymphatic invasion, with or without recurrence). Lymph node metastasis had a statistically significant signature according to Significance Analysis of Microarrays (SAM) and parametric t-tests, with a false discovery rate (FDR)=0.1% and p=0.001, respectively. Cross-correlation of these two tests identified 102 transcripts as being potentially related to node metastases, with fold changes in the range of 2.182-12.960.
CONCLUSION: We identified 102 differentially expressed genes related to the presence of lymph node metastases in patients with advanced colorectal cancer.

Entities:  

Keywords:  Colorectal cancer; gene expression; metastasis; three-dimensional oligonucleotide microarray

Mesh:

Year:  2013        PMID: 24427346      PMCID: PMC3885480     

Source DB:  PubMed          Journal:  Int J Clin Exp Pathol        ISSN: 1936-2625


  14 in total

1.  Significance analysis of microarrays applied to the ionizing radiation response.

Authors:  V G Tusher; R Tibshirani; G Chu
Journal:  Proc Natl Acad Sci U S A       Date:  2001-04-17       Impact factor: 11.205

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Authors:  Ramesh Ramakrishnan; David Dorris; Anna Lublinsky; Allen Nguyen; Marc Domanus; Anna Prokhorova; Linn Gieser; Edward Touma; Randall Lockner; Murthy Tata; Xiaomei Zhu; Marcus Patterson; Richard Shippy; Timothy J Sendera; Abhijit Mazumder
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3.  A comparative review of statistical methods for discovering differentially expressed genes in replicated microarray experiments.

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Journal:  Bioinformatics       Date:  2002-04       Impact factor: 6.937

Review 4.  DNA microarrays: a new diagnostic tool and its implications in colorectal cancer.

Authors:  C Stremmel; A Wein; W Hohenberger; B Reingruber
Journal:  Int J Colorectal Dis       Date:  2002-05       Impact factor: 2.571

5.  GenBank: update.

Authors:  Dennis A Benson; Ilene Karsch-Mizrachi; David J Lipman; James Ostell; David L Wheeler
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

6.  Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

Authors:  Marco Severgnini; Silvio Bicciato; Eleonora Mangano; Francesca Scarlatti; Alessandra Mezzelani; Michela Mattioli; Riccardo Ghidoni; Clelia Peano; Raoul Bonnal; Federica Viti; Luciano Milanesi; Gianluca De Bellis; Cristina Battaglia
Journal:  Anal Biochem       Date:  2006-04-03       Impact factor: 3.365

Review 7.  Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting.

Authors:  Alain Dupuy; Richard M Simon
Journal:  J Natl Cancer Inst       Date:  2007-01-17       Impact factor: 13.506

Review 8.  Oncogenes and cancer.

Authors:  Carlo M Croce
Journal:  N Engl J Med       Date:  2008-01-31       Impact factor: 91.245

Review 9.  Cancer genetics and their application to individualised medicine.

Authors:  G-J Liefers; R A E M Tollenaar
Journal:  Eur J Cancer       Date:  2002-05       Impact factor: 9.162

10.  Comparison of the latest commercial short and long oligonucleotide microarray technologies.

Authors:  Aurélien de Reyniès; Daniela Geromin; Jean-Michel Cayuela; Fabien Petel; Philippe Dessen; François Sigaux; David S Rickman
Journal:  BMC Genomics       Date:  2006-03-15       Impact factor: 3.969

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  1 in total

1.  Early response index: a statistic to discover potential early stage disease biomarkers.

Authors:  Sirajul Salekin; Mehrab Ghanat Bari; Itay Raphael; Thomas G Forsthuber; Jianqiu Michelle Zhang
Journal:  BMC Bioinformatics       Date:  2017-06-23       Impact factor: 3.169

  1 in total

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