Linked Life Data

10554019

Source:http://linkedlifedata.com/resource/pubmed/id/10554019

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
21
pubmed:dateCreated
1999-12-2
pubmed:abstractText
Several methods have been used recently to determine gene expression profiles of cell populations. Here we demonstrate the strength of combining two approaches, serial analysis of gene expression (SAGE) and DNA arrays, to help elucidate pathways in breast cancer progression by finding genes consistently expressed at different levels in primary breast cancers, metastatic breast cancers, and normal mammary epithelial cells. SAGE profiles of 21PT and 21MT, two well-characterized breast tumor cell lines, were compared with SAGE profiles of normal breast epithelial cells to identify differentially expressed genes. A subset of these candidates was then placed on an array and screened with clinical breast tumor samples to find genes and expressed sequence tags that are consistently expressed at different levels in diseased and normal tissues. In addition to finding the predicted overexpression of known breast cancer markers HER-2/neu and MUC-1, the powerful coupling of SAGE and DNA arrays resulted in the identification of genes and potential pathways not implicated previously in breast cancer. Moreover, these techniques also generated information about the differences and similarities of expression profiles in primary and metastatic breast tumors. Thus, combining SAGE and custom array technology allowed for the rapid identification and validation of the clinical relevance of many genes potentially involved in breast cancer progression. These differentially expressed genes may be useful as tumor markers and prognostic indicators and may be suitable targets for various forms of therapeutic intervention.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0008-5472
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
59
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5464-70
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Combining serial analysis of gene expression and array technologies to identify genes differentially expressed in breast cancer.
pubmed:affiliation
Genzyme Molecular Oncology, Framingham, Massachusetts 01701, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't