Protein expression patterns of epithelial ovarian cancers characterized by proteomic analysis.
- Author:
Seon Young PARK
1
;
Jae Yun SONG
;
Jae Kwan LEE
;
Nak Woo LEE
;
Hak Hyun JUNG
;
Kyu Wan LEE
Author Information
1. Department of Obstetrics and Gynecology, Korea University College of Medicine, Seoul, Korea. pumplee@korea.ac.kr
- Publication Type:Original Article
- Keywords:
Ovarian cancer;
Protein expression;
Tumor marker
- MeSH:
Electrophoresis;
Humans;
Molecular Weight;
Ovarian Neoplasms*;
RNA, Messenger;
Up-Regulation
- From:Korean Journal of Gynecologic Oncology
2007;18(4):341-350
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVE: The purpose of the present study is to identify the expression profiles of proteins in human epithelial ovarian cancers, as compared with those seen in normal ovarian tissues, via proteomic analysis. METHODS: Three epithelial ovarian cancer tissues and three normal ovarian tissues were intraoperatively obtained. We performed two- dimensional electrophoresis in order to separate tissue proteins by molecular weight, and then compared protein expression patterns. 21 up-regulated spots were identified by MALDI-TOF in epithelial ovarian cancers. Then, the expression of some of the up-regulated proteins was evaluated at the mRNA level via RT-PCR, in both the epithelial ovarian cancer tissues and the normal ovarian tissues. RESULTS: Proteomic analysis revealed about 200 up-regulated spots in epithelial ovarian cancer tissues, of which 21 were selected and identified by MALDI-TOF. 16 proteins were matched to MLC3nm, MACMARCKS, MYL2, S100A14, MIA, VHL, GUCA1B, RABL2A, BRMS1, IFI30, VILIP1, MAPRE1, NME5, DIO2, KLK 2, and CPA2. The up-regulation of these proteins was also evaluated at the mRNA level via RT-PCR, which revealed that MACMARCKS, S100A14, GUCA1B, RABL2A, VILIP1, MAPRE1, NME5, DIO2, and KLK2 were distinctly up-regulated in the cancer tissues. Five protein spots could not be matched, even with RT-PCR. CONCLUSION: This proteomic analysis may constitute a powerful tool for the identification and characterization of many promising candidate proteins related to epithelial ovarian cancers.
