Serum Proteomic Abnormality Predating Screen Detection of Ovarian Cancer

Ovarian cancer is characterized by vague, non-specific symptoms, advanced stage at diagnosis and poor overall survival. A nested case control study was undertaken on stored serial serum samples from women who developed ovarian cancer and healthy controls (matched for serum processing and storage con...

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Bibliographic Details
Published in:Computer journal 2009-05, Vol.52 (3), p.326-333
Main Authors: Gammerman, Alex, Vovk, Volodya, Burford, Brian, Nouretdinov, Ilia, Luo, Zhiyuan, Chervonenkis, Alexey, Waterfield, Mike, Cramer, Rainer, Tempst, Paul, Villanueva, Josep, Kabir, Musarat, Camuzeaux, Stephane, Timms, John, Menon, Usha, Jacobs, Ian
Format: Article
Language:English
Subjects:
Bioinformatics
Biomarkers
Blood tests
Computer science
Datasets
Hypotheses
Mass spectrometry
Medical research
Medical screening
Ovarian cancer
Pilot projects
Proteomics
Research methodology
Scientific imaging
Triplets
Womens health
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Summary:Ovarian cancer is characterized by vague, non-specific symptoms, advanced stage at diagnosis and poor overall survival. A nested case control study was undertaken on stored serial serum samples from women who developed ovarian cancer and healthy controls (matched for serum processing and storage conditions as well as attributes such as age) in a pilot randomized controlled trial of ovarian cancer screening. The unique feature of this study is that the women were screened for up to 7 years. The serum samples underwent prefractionation using a reversed-phase batch extraction protocol prior to MALDI-TOF MS data acquisition. Our exploratory analysis shows that combining a single MS peak with CA125 allows statistically significant discrimination at the 5% level between cases and controls up to 12 months in advance of the original diagnosis of ovarian cancer. Such combinations work much better than a single peak or CA125 alone. This paper demonstrates that mass spectra from the low molecular weight serum proteome carry information useful for early detection of ovarian cancer. The next step is to identify the specific biomarkers that make early detection possible.
ISSN:0010-4620
1460-2067
DOI:10.1093/comjnl/bxn021