Comparative proteomics of ovarian epithelial tumors

Abstract

We analyzed 12 ovarian epithelial tumors using 2D PAGE-based comparative proteomics to construct intra- and inter-tumoral distance map trees and to discover surrogate biomarkers indicative of an ovarian tumor. The analysis was performed after laser microdissection of 12 fresh-frozen tissue samples, including 4 serous, 5 mucinous, and 3 endometrioid tumors, with correlation with their histopathological characteristics. Ovarian epithelial tumors and normal tissues showed an apparent separation on the distance map tree. Mucinous carcinomas were closest to the normal group, whereas serous carcinomas were located furthest from the normal group. All mucinous tumors with aggressive histology were separated from the low malignant potential (LMP) group. The benign-looking cysts adjacent to the intraepithelial carcinoma (IEC) showed an expression pattern identical to that of the IEC area. The extent of change on the lineages leading to the mucinous and serous carcinoma was 1.98-fold different. The overall gene expression profiles of serous or endometrioid carcinomas appeared to be less affected by grade or stage than by histologic type. The potential candidate biomarkers screened in ovarian tumors and found to be significantly up-regulated in comparison to normal tissues were as follows: NM23, annexin-1, protein phosphatase-1, ferritin light chain, proteasome alpha-6, and NAGK (N-acetyl glucosamine kinase). In conclusion, ovarian mucinous tumors are distinct from other ovarian epithelial tumors. LMP mucinous tumors showing histologically aggressive features belong to mucinous carcinoma on the proteomic basis.