Literature DB >> 18055315

[Gene expression profiling in cancer research].

Stefan Michiels1, S Koscielny, Thomas Boulet, Catherine Hill.   

Abstract

Gene expression profiling is increasingly used in cancer research. For each patient, the expression of thousands of genes in the tumour can be measured simultaneously on a microarray. Microarray studies aim at classifying patients based on two types of classification schemes: unsupervised classification, which uses clustering in order to identify homogeneous subtypes of a disease on the basis of gene expression, or supervised classification, which principally aims at the identification of genes or set of genes differentially expressed between tumours with different characteristics (molecular signature), for instance between a group of patients with bad and good prognosis. The data consists of a small number of patients and a large number of variables, raising serious methodological problems. We will use published results on breast cancer in order both to study the power of the experiments and to illustrate the problems in interpretation and validity of their results. We recommend rigorous evaluation of this new technology.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 18055315

Source DB:  PubMed          Journal:  Bull Cancer        ISSN: 0007-4551            Impact factor:   1.276


  3 in total

1.  Quantifying stability in gene list ranking across microarray derived clinical biomarkers.

Authors:  Sebastian Schneckener; Nilou S Arden; Andreas Schuppert
Journal:  BMC Med Genomics       Date:  2011-10-14       Impact factor: 3.063

2.  Use of gene expression profiles of peripheral blood lymphocytes to distinguish BRCA1 mutation carriers in high risk breast cancer families.

Authors:  Marie-Laure Vuillaume; Nancy Uhrhammer; Véronique Vidal; Valérie Sylvain Vidal; Valérie Chabaud; Beline Jesson; Fabrice Kwiatkowski; Yves-Jean Bignon
Journal:  Cancer Inform       Date:  2009-03-02

3.  The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma.

Authors:  Yunfeng Wang; Haoliang Xue; Marine Aglave; Antoine Lainé; Mélina Gallopin; Daniel Gautheret
Journal:  NAR Cancer       Date:  2022-02-01
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.