Multiplexed immunobead-based cytokine profiling for early detection of ovarian cancer
- PMID: 15824174
- DOI: 10.1158/1055-9965.EPI-04-0404
Multiplexed immunobead-based cytokine profiling for early detection of ovarian cancer
Abstract
Early detection of ovarian cancer might improve clinical outcome. Some studies have shown the role of cytokines as a new group of tumor markers for ovarian cancer. We hypothesized that a panel comprised of multiple cytokines, which individually may not show strong correlation with the disease, might provide higher diagnostic power. To evaluate the diagnostic utility of cytokine panel, we used a novel multianalyte LabMAP profiling technology that allows simultaneous measurement of multiple markers. Concentrations of 24 cytokines (cytokines/chemokines, growth, and angiogenic factors) in combination with cancer antigen-125 (CA-125), were measured in sera of 44 patients with early-stage ovarian cancer, 45 healthy women, and 37 patients with benign pelvic tumors. Six markers, i.e., interleukin (IL)-6, IL-8, epidermal growth factor (EGF), vascular endothelial growth factor (VEGF), monocyte chemoattractant protein-1 (MCP-1), and CA-125, showed significant differences in serum concentrations between ovarian cancer and control groups. Out of this group, IL-6, IL-8, VEGF, EGF, and CA-125, were used in a classification tree analysis that resulted in 84% sensitivity at 95% specificity. The receiver operator characteristic curve created using the combination of markers produced sensitivities between 90% and 100% in the area of 80% to 90% specificity, whereas the receiver operator characteristic curve for CA-125 alone resulted in sensitivities of 70% to 80%. The classification tree analysis for discrimination of benign condition from ovarian cancer used CA-125, granulocyte colony-stimulating factor (G-CSF), IL-6, EGF, and VEGF resulting in 86.5% sensitivity and 93.0% specificity. The presented data show that simultaneous testing of a panel of serum cytokines and CA-125 using LabMAP technology may present a promising approach for ovarian cancer detection.
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