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Large-scale proteomics analysis of human ovarian cancer for biomarkers
KTH, School of Biotechnology (BIO), Proteomics.ORCID iD: 0000-0001-6990-1905
KTH, School of Biotechnology (BIO), Proteomics.ORCID iD: 0000-0001-8993-048X
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2007 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 6, no 4, 1440-1450 p.Article in journal (Refereed) Published
Abstract [en]

Ovarian cancer is usually found at a late stage when the prognosis is often bad. Relative survival rates decrease with tumor stage or grade, and the 5-year survival rate for women with carcinoma is only 38%. Thus, there is a great need to find biomarkers that can be used to carry out routine screening, especially in high-risk patient groups. Here, we present a large-scale study of 64 tissue samples taken from patients at all stages and show that we can identify statistically valid markers using nonsupervised methods that distinguish between normal, benign, borderline, and malignant tissue. We have identified 217 of the significantly changing protein spots. We are expressing and raising antibodies to 35 of these. Currently, we have validated 5 of these antibodies for use in immunohistochemical analysis using tissue microarrays of healthy and diseased ovarian, as well as other, human tissues.

Place, publisher, year, edition, pages
2007. Vol. 6, no 4, 1440-1450 p.
Keyword [en]
biomarkers, ovarian cancer, DIGE, proteomics, statistical analysis, lung-cancer, cathepsin-b, 2-dimensional electrophoresis, gel-electrophoresis, protein expression, colon-cancer, cell-lines, breast, carcinoma, overexpression
URN: urn:nbn:se:kth:diva-16534DOI: 10.1021/pr060593yISI: 000245510900022ScopusID: 2-s2.0-34248207230OAI: diva2:334576
QC 20100525Available from: 2010-08-05 Created: 2010-08-05Bibliographically approved

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