An integrated clinical-genomics approach identifies a candidate multi-analyte blood test for serous ovarian carcinoma

Purpose: Cancer of the ovary confers the worst prognosis among women with gynecological malignancies, underscoring the need to develop new biomarkers for detection of early disease, particularly those that can be readily monitored in the blood.

Experimental Design: We developed an algorithm to identify secreted proteins encoded among ~22,500 genes on commercial oligonucleotide arrays, and applied it to gene expression profiles of 67 stage 1-IV serous papillary carcinomas and 9 crudely enriched normal ovarian tissues, to identify putative diagnostic markers. ELISA assays were used to validate increased levels of secreted proteins in patient sera encoded by genes with differentially high expression.

Results: We identified 276 genes predicted to encode secreted proteins with increased expression in ovarian cancers (<0.5>2-fold, p<0.001). The serum levels of four of these proteins, MMP-7, osteopontin (OPN), secretory leukoprotease inhibitor (SLPI) and kallikrein 10 (KLK10) were significantly elevated in a series of 67 independent patients with serous ovarian carcinomas as compared to 67 healthy controls (p<0.001, Wilcoxon rank sum test). Optimized Support Vector Machine (SVM) classifiers with as few as two of these markers (OPN or KLK-10/MMP-7) in combination with CA-125 yielded sensitivity and specificity values ranging from 96–98.7% and 99.7–100%, respectively, with the ability to discern early-stage disease from normal, healthy controls.

Conclusions: Our data suggest that this assay combination warrants further investigation as a multi-analyte diagnostic test for serous ovarian adenocarcinoma.