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

Title
Estimation of prognostic marker genes by public microarray data in patients with ovarian serous cystadenocarcinoma
Authors
Yang S.-D.Jang S.-S.Han J.A.Park H.-S.Kim J.-I.
Ewha Authors
박현석
SCOPUS Author ID
박현석scopus
Issue Date
2016
Journal Title
Yonsei Medical Journal
ISSN
0513-5796JCR Link
Citation
vol. 57, no. 4, pp. 872 - 878
Keywords
Gene expressionMicroarray analysisOvarian cancerPrognosis
Publisher
Yonsei University College of Medicine
Indexed
SCI; SCIE; SCOPUS; KCI WOS scopus
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. © Yonsei University College of Medicine 2016.
DOI
10.3349/ymj.2016.57.4.872
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엘텍공과대학 > 컴퓨터공학과 > Journal papers
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