Literature DB >> 18455427

Using microarrays to study the microenvironment in tumor biology: the crucial role of statistics.

Stuart G Baker1, Barnett S Kramer.   

Abstract

Microarrays represent a potentially powerful tool for better understanding the role of the microenvironment on tumor biology. To make the best use of microarray data and avoid incorrect or unsubstantiated conclusions, care must be taken in the statistical analysis. To illustrate the statistical issues involved we discuss three microarray studies related to the microenvironment and tumor biology involving: (i) prostatic stroma cells in cancer and non-cancer tissues; (ii) breast stroma and epithelial cells in breast cancer patients and non-cancer patients; and (iii) serum associated with wound response and stroma in cancer patients. Using these examples we critically discuss three types of analyses: differential gene expression, cluster analysis, and class prediction. We also discuss design issues.

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Year:  2008        PMID: 18455427      PMCID: PMC2584335          DOI: 10.1016/j.semcancer.2008.03.001

Source DB:  PubMed          Journal:  Semin Cancer Biol        ISSN: 1044-579X            Impact factor:   15.707


  22 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

Review 2.  Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification.

Authors:  Richard Simon; Michael D Radmacher; Kevin Dobbin; Lisa M McShane
Journal:  J Natl Cancer Inst       Date:  2003-01-01       Impact factor: 13.506

3.  Outcome signature genes in breast cancer: is there a unique set?

Authors:  Liat Ein-Dor; Itai Kela; Gad Getz; David Givol; Eytan Domany
Journal:  Bioinformatics       Date:  2004-08-12       Impact factor: 6.937

4.  Prediction of cancer outcome with microarrays: a multiple random validation strategy.

Authors:  Stefan Michiels; Serge Koscielny; Catherine Hill
Journal:  Lancet       Date:  2005 Feb 5-11       Impact factor: 79.321

Review 5.  Bias as a threat to the validity of cancer molecular-marker research.

Authors:  David F Ransohoff
Journal:  Nat Rev Cancer       Date:  2005-02       Impact factor: 60.716

6.  Drinking from the fire hose--statistical issues in genomewide association studies.

Authors:  David J Hunter; Peter Kraft
Journal:  N Engl J Med       Date:  2007-07-18       Impact factor: 91.245

7.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.

Authors:  T R Golub; D K Slonim; P Tamayo; C Huard; M Gaasenbeek; J P Mesirov; H Coller; M L Loh; J R Downing; M A Caligiuri; C D Bloomfield; E S Lander
Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

8.  Cluster analysis and display of genome-wide expression patterns.

Authors:  M B Eisen; P T Spellman; P O Brown; D Botstein
Journal:  Proc Natl Acad Sci U S A       Date:  1998-12-08       Impact factor: 11.205

9.  Markers for early detection of cancer: statistical guidelines for nested case-control studies.

Authors:  Stuart G Baker; Barnett S Kramer; Sudhir Srivastava
Journal:  BMC Med Res Methodol       Date:  2002-02-28       Impact factor: 4.615

10.  Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds.

Authors:  Howard Y Chang; Julie B Sneddon; Ash A Alizadeh; Ruchira Sood; Rob B West; Kelli Montgomery; Jen-Tsan Chi; Matt van de Rijn; David Botstein; Patrick O Brown
Journal:  PLoS Biol       Date:  2004-01-13       Impact factor: 8.029

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  2 in total

1.  Improving the quality of biomarker discovery research: the right samples and enough of them.

Authors:  Margaret S Pepe; Christopher I Li; Ziding Feng
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-04-02       Impact factor: 4.254

2.  Improving the biomarker pipeline to develop and evaluate cancer screening tests.

Authors:  Stuart G Baker
Journal:  J Natl Cancer Inst       Date:  2009-07-02       Impact factor: 13.506

  2 in total

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