Linked Life Data

18028381

Source:http://linkedlifedata.com/resource/pubmed/id/18028381

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2008-10-1
pubmed:abstractText
We set out to discover ovarian cancer biomarkers useful for monitoring progression during and after chemotherapy and possibly for diagnosis. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry was used to create serum protein profiles of ovarian cancer patients before chemotherapy or at progression (n = 51) (trial initiated by the Gynecological Cancer Cooperative Group of the European Organization for Research and Treatment of Cancer trial) that were compared with those of healthy individuals (n = 31). In addition, sera profiles from ovarian cancer patients after chemotherapy (n = 12) were compared with those of ovarian cancer patients at progression (n = 24). One of the discovered biomarkers was identified and subsequently confirmed and validated using enzyme-linked immunosorbent assay (ELISA). Eight primary (sens = 94%, spec = 97%, P < 0.0001) and seven progression tumor biomarkers (sens = 91%, spec = 97%, P < 0.0001) were discovered. In addition, we discovered eight potential progression monitoring biomarkers (sens = 75%, spec = 83%, P = 0.0008) of which one, a biomarker of 11.7 kd, was further identified as serum amyloid A1. Independent validation (ELISA) showed an elevated expression of this protein at relapse in four of the seven ovarian cancer patients tested. Combining the eight newly discovered progression monitoring biomarkers with CA125 resulted in a clear increase of the sensitivity (91-100%). These biomarkers, in combination with for instance CA125, should be validated in large ovarian cancer and control groups. The resulting multimarker assay could be suitable for disease monitoring during and after therapy and might also be useful for ovarian cancer screening.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1525-1438
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
985-95
pubmed:meshHeading
pubmed:articleTitle
Serum proteomic patterns for ovarian cancer monitoring.
pubmed:affiliation
Department of Medical Oncology, Erasmus MC/Daniel den Hoed Cancer Center, Rotterdam, The Netherlands.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't