Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
My Menu
Saved Items

Original Contribution

Gene Expression Profiling of Nonneoplastic Mucosa May Predict Clinical Outcome of Colon Cancer Patients

Alain Barrier1, 2, 3 Contact Information, Pierre-Yves BoelleContact Information, Antoinette Lemoine4, Chantal Tse5, Didier Brault5, Franck Chiappini4, François Lacaine1, Sidney Houry1, Michel Huguier1, Antoine Flahault2 and Sandrine Dudoit3

(1)  Service de Chirurgie Digestive, Hôpital Tenon, Université Pierre et Marie Curie, Assistance Publique, Paris, France
(2)  INSERM U444, Faculté de Médecine Saint-Antoine, Université Pierre et Marie Curie, Paris, France
(3)  Division of Biostatistics, School of Public Health, University of California, Berkeley, California, France
(4)  INSERM U602, Hôpital Paul Brousse, Université Paris XI, Villejuif, France
(5)  Service de Biochimie, Hôpital Tenon, Université Pierre et Marie Curie, Assistance Publique, Paris, France

Published online: 3 October 2005

PURPOSE  This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in Stage II and III colon cancer patients.
METHODS  Tumor and nonneoplastic mucosa mRNA samples from 12 colon cancer patients were profiled using the Affymetrix HGU133A GeneChip. Six of 12 patients experienced a metachronous metastasis, whereas the 6 others remained disease-free for more than five years. Three datasets were constituted, including, respectively, the gene expression measures in tumor samples (T), in adjacent nonneoplastic mucosa samples (A), and the log-ratio of the gene expression measures (L). The step-down procedure of Westfall and Young and the k-nearest neighbor class prediction method were applied on T, A, and L. Leave-one-out cross-validation was used to estimate the generalization error of predictors based on different numbers of genes and neighbors.
RESULTS  The most frequent results were one false prediction with the A-based predictors (95 percent) and two false predictions with the T- and l-based predictors (65 and 60 percent, respectively). A-based predictors were more stable (i.e., less sensitive to changes of parameters, such as numbers of genes and neighbors) than T- and l-based predictors. Informative genes in A-based predictors included genes involved in the oxidative and phosphorylative mitochondrial metabolism and genes involved in cell-signaling pathways and their receptors.
CONCLUSIONS  This study suggests that one can build a prognosis predictor for Stage II and III colon cancer patients, based on microarray gene expression measures, and suggests the potential usefulness of nonneoplastic mucosa for this purpose.

Key words  Functional genomics - Colon cancer - Prognosis prediction - Nonneoplastic mucosa

Supported by a grant from the Fondation de France/Fédération Nationale des Centres de Lutte Contre le Cancer for a stay in the Division of Biostatistics at the University of California, Berkeley (AB).

Contact Information Pierre-Yves Boelle
Division of Biostatistics, School of Public Health, 140 Earl Warren Hall, Berkeley, California, 94720-7360,
Email: barrier@stat.berkeley.edu
Fulltext Preview (Small, Large)
Image of the first page of the fulltext

References secured to subscribers.



Export this article
Export this article as RIS | Text
 
Referenced by
4 newer articles

  1. Walther, Axel (2009) Genetic prognostic and predictive markers in colorectal cancer. Nature Reviews Cancer
    [CrossRef]
  2. Kim, Kyongrae (2008) Gene profiling of colonic serrated adenomas by using oligonucleotide microarray. International Journal of Colorectal Disease
    [CrossRef]
  3. Dihal, Ashwin A. (2008) Transcriptome and proteome profiling of colon mucosa from quercetin fed F344 rats point to tumor preventive mechanisms, increased mitochondrial fatty acid degradation and decreased glycolysis. PROTEOMICS 8(1)
    [CrossRef]
  4. Dihal, Ashwin A. (2007) Pathway and single gene analyses of inhibited Caco-2 differentiation by ascorbate-stabilized quercetin suggest enhancement of cellular processes associated with development of colon cancer. Molecular Nutrition & Food Research
    [CrossRef]
Remote Address: 38.107.191.115 • Server: mpweb03
HTTP User Agent: CCBot/1.0 (+http://www.commoncrawl.org/bot.html)