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Cancer Prev Res (Phila). 2019 Feb 1. pii: canprevres.0221.2018. doi: 10.1158/1940-6207.CAPR-18-0221. [Epub ahead of print]

Simultaneous Measurement of 92 Serum Protein Biomarkers for the Development of a Multi-Protein Classifier for Ovarian Cancer Detection.

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Dept. Laboratory Medicine and Pathology, University of Minnesota
Laboratory Medicine and Pathology, University of Minnesota.
Dept. Laboratory Medicine and Pathology, University of Minnesota.
Biostatistics & Informatics Core, University of Minnesota.
Dept of Ob-Gyn & Women's Health, University of Minnesota.
Obstetrics, Gynecology and Women's Health, University of Minnesota.
Department of Gynecologic Oncology, The University of Texas MD Anderson Cancer Center.
Experimental Therapeutics, University of Texas MD Anderson Cancer Center.
Department of Gynecologic Oncology and Reproductive Medicine, M. D. Anderson Cancer Center.
Division of Biostatistics, School of Public Health, University of Minnesota.


The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek® Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the polymerase chain reaction with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high throughput quantification. We analyzed one microliter of sera from each of 61 women with ovarian cancer and compared the values obtained to those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek® plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly (p < 0.006) between ovarian cancer and healthy samples; several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multi-protein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%; thereby improving the sensitivity and specificity of CA125 alone.

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