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PMID: 11568890 Published · ppublish English Journal Article Review

Towards a novel classification of human malignancies based on gene expression patterns.

The Journal of pathology ·Vol. 195 ·No. 1 ·2001-09-00 ·Pages 41-52

Alizadeh AA, Ross DT, Perou CM, van de Rijn M

Abstract

As a result of progress on the human genome project, approximately 19 000 genes have been identified and tens of thousands more tentatively identified as partial fragments of genes termed expressed sequence tags (ESTs). Most of these genes are only partially characterized and the functions of the vast majority are as yet unknown. It is likely that many genes that might be useful for diagnosis and/or prognostication of human malignancies have yet to be recognized. The advent of cDNA microarray technology now allows the efficient measurement of expression for almost every gene in the human genome in a single overnight hybridization experiment. This genomic scale approach has begun to reveal novel molecular-based sub-classes of tumours in breast carcinoma, colon carcinoma, lymphoma, leukaemia, and melanoma. In several instances, gene microarray analysis has already identified genes that appear to be useful for predicting clinical behaviour. This review discusses some recent findings using gene microarray technology and describes how this and related technologies are likely to contribute to the emergence of novel molecular classifications of human malignancies.

MeSH Terms
Breast Neoplasms/genetics Cluster Analysis DNA Fingerprinting Expressed Sequence Tags Gene Expression Regulation, Neoplastic Genetic Markers Genome, Human Humans Lymphoma/genetics Neoplasms/classification,genetics Oligonucleotide Array Sequence Analysis Prognosis
Chemicals
Genetic Markers
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Alizadeh A A
Department of Biochemistry, Stanford University, Stanford, CA 94305, USA.
Ross D T
Perou C M
van de Rijn M
Article Info
Journal
The Journal of pathology
Abbr.
J Pathol
ISSN
0022-3417
Published
2001-09-00
Pages
41-52
Language
English
Region
England
NLM ID
0204634
Subset
IM
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