Estimation of prognostic marker genes by public microarray data in patients with ovarian serous cystadenocarcinoma

San Duk Yang, Se Song Jang, Jeong A. Han, Hyun Seok Park, Jong Il Kim

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)872-878
Number of pages7
JournalYonsei Medical Journal
Issue number4
StatePublished - Jul 2016

Bibliographical note

Funding Information:
This study was supported by the Research Grant from Seoul National University Hospital (No. 04-2009-0780). This research was supported by a grant of the Korean Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI13C2148). The study resources were provided by TCGA.

Publisher Copyright:
© Yonsei University College of Medicine 2016.


  • Gene expression
  • Microarray analysis
  • Ovarian cancer
  • Prognosis


Dive into the research topics of 'Estimation of prognostic marker genes by public microarray data in patients with ovarian serous cystadenocarcinoma'. Together they form a unique fingerprint.

Cite this