Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
44
pubmed:dateCreated
2007-11-5
pubmed:abstractText
Ovarian cancer is a leading cause of deaths, yet many aspects of the biology of the disease and a routine means of its detection are lacking. We have used protein microarrays and autoantibodies from cancer patients to identify proteins that are aberrantly expressed in ovarian tissue. Sera from 30 cancer patients and 30 healthy individuals were used to probe microarrays containing 5,005 human proteins. Ninety-four antigens were identified that exhibited enhanced reactivity from sera in cancer patients relative to control sera. The differential reactivity of four antigens was tested by using immunoblot analysis and tissue microarrays. Lamin A/C, SSRP1, and RALBP1 were found to exhibit increased expression in the cancer tissue relative to controls. The combined signals from multiple antigens proved to be a robust test to identify cancerous ovarian tissue. These antigens were also reactive with tissue from other types of cancer and thus are not specific to ovarian cancer. Overall our studies identified candidate tissue marker proteins for ovarian cancer and demonstrate that protein microarrays provide a powerful approach to identify proteins aberrantly expressed in disease states.
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-10766157, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-10924126, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-11158614, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-11344167, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-11448987, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-11875502, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-12532422, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-12804702, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-14595809, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-15274142, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-15381683, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-15837765, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-15867203, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-15890779, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-15950949, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-16083262, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-16424057, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-16434085, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-16514137, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-17109749, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-17360355, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-17465333, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-3453101, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-6310399, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-9151109, http://linkedlifedata.com/resource/pubmed/commentcorrection/17954908-9398045
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0027-8424
pubmed:author
pubmed:issnType
Print
pubmed:day
30
pubmed:volume
104
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
17494-9
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Identification of differentially expressed proteins in ovarian cancer using high-density protein microarrays.
pubmed:affiliation
Department of Molecular, Cellular, and Developmental Biology, Yale University, 210 Prospect Street, New Haven, CT 06520-8103, USA.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural