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Journal of Ovarian Research
Published in: Journal of Ovarian Research 1/2015

Open Access 01-12-2015 | Research

Gene expression profiling of ovarian carcinomas and prognostic analysis of outcome

Authors: Sheng-Yun Cai, Tian Yang, Yu Chen, Jing-Wen Wang, Li Li, Ming-Juan Xu

Published in: Journal of Ovarian Research | Issue 1/2015

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Abstract

Background

Ovarian cancer (OCA), the fifth leading deaths cancer to women, is famous for its low survival rate in epithelial ovarian cancer cases, which is very complicated and hard to be diagnosed from asymptomatic nature in the early stage. Thus, it is urgent to develop an effective genetic prognostic strategy.

Methods

Current study using the Database for Annotation, Visualization and Integrated Discovery tool for the generation and analysis of quantitative gene expression profiles; all the annotated gene and biochemical pathway membership realized according to shared categorical data from Pathway and Kyoto Encyclopedia of Genes and Genomes; correlation networks based on current gene screening actualize by Weighted correlation network analysis to identify therapeutic targets gene and candidate bio-markers.

Results

3095 differentially expressed genes were collected from genome expression profiles of OCA patients (n = 53, 35 advanced, 8 early and 10 normal). By pathway enrichment, most genes showed contribution to cell cycle and chromosome maintenance.1073 differentially expression genes involved in the 4 dominant network modules are further generated for prognostic pattern establish, we divided a dataset with random OCA cases (n = 80) into 3 groups efficiently (p = 0.0323, 95 % CIs in Kaplan-Meier). Finally, 6 prognosis related genes were selected out by COX regression analysis, TFCP2L1 related to cancer-stem cell, probably contributes to chemotherapy efficiency.

Conclusions

Our study presents an integrated original model of the differentially expression genes related to ovarian cancer progressing, providing the identification of genes relevant for its pathological physiology which can potentially be new clinical markers.
Appendix
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Metadata
Title
Gene expression profiling of ovarian carcinomas and prognostic analysis of outcome
Authors
Sheng-Yun Cai
Tian Yang
Yu Chen
Jing-Wen Wang
Li Li
Ming-Juan Xu
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Journal of Ovarian Research / Issue 1/2015
Electronic ISSN: 1757-2215
DOI
https://doi.org/10.1186/s13048-015-0176-9

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