Yonsei Med J.  2016 Jul;57(4):872-878. 10.3349/ymj.2016.57.4.872.

Estimation of Prognostic Marker Genes by Public Microarray Data in Patients with Ovarian Serous Cystadenocarcinoma

Affiliations
  • 1Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea. jongil@snu.ac.kr
  • 2Department of Biochemistry and Molecular Biology, Kangwon National University School of Medicine, Chuncheon, Korea.
  • 3Center for Convergence Research of Advanced Technologies, Ewha Womans University, Seoul, Korea.
  • 4Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Korea.
  • 5Cancer Research Institute, Seoul National University, Seoul, Korea.

Abstract

PURPOSE
Lymphatic invasion (LI) is regarded as a predictor of the aggressiveness of ovarian cancer (OC). However, LI is not always the major determinant of long-term patient survival. To establish proper diagnosis and treatment for OC, we analyzed differentially expressed genes (DEGs) for patients with serous epithelial OC, with or without LI, who did or did not survive for 5 years.
MATERIALS AND METHODS
Gene expression data from 63 patients with OC and LI, and 35 patients with OC but without LI, were investigated using an Affymetrix Human Genome U133 Array and analyzed using The Cancer Genome Atlas (TCGA) database. Among these 98 patients, 16 survived for 5 years or more. DEGs were identified using the Bioconductor R package, and their functions were analyzed using the DAVID web tool.
RESULTS
We found 55 significant DEGs (p<0.01) from the patients with LI and 20 highly significant DEGs (p<0.001) from those without it. Pathway analysis showed that DEGs associated with carbohydrate metabolism or with renal cell carcinoma pathways were enriched in the patients with and without LI, respectively. Using the top five prognostic marker genes, we generated survival scores that could be used to predict the 5-year survival of patients with OC without LI.
CONCLUSION
The DEGs identified in this study could be used to elucidate the mechanism of tumor progression and to guide the prognosis and treatment of patients with serous OC but without LI.

Keyword

Gene expression; microarray analysis; ovarian cancer; prognosis

MeSH Terms

Cystadenocarcinoma, Serous/*genetics/*mortality/pathology
Databases, Genetic
Female
Gene Expression Regulation, Neoplastic
Humans
Microarray Analysis
Middle Aged
Ovarian Neoplasms/*genetics/*mortality/pathology
Prognosis
Regression Analysis
Retrospective Studies
Survival Rate
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