A miR-200 microRNA cluster as prognostic marker in advanced ovarian cancer

Xiaoxia Hu, Dusten M. Macdonald, Phyllis C. Huettner, Zhihui Feng, Issam M. El Naqa, Julie K. Schwarz, David G. Mutch, Perry W. Grigsby, Simon N. Powell, Xiaowei Wang

Research output: Contribution to journalArticle

228 Scopus citations

Abstract

Objective: Ovarian cancer is one of the most deadly human cancers, resulting in over 15,000 deaths in the US each year. A reliable method that could predict disease outcome would improve care of patients with this disease. The main aim of this study is to identify novel prognostic biomarkers for advanced ovarian cancer. Methods: We hypothesized that microRNAs (miRNAs) may predict outcome and have examined the prognostic value of these small RNA molecules on disease outcome prediction. miRNAs are a newly identified family of non-coding RNA genes, and recent studies have shown that miRNAs are extensively involved in the tumor development process. We have profiled the expression of miRNAs in advanced ovarian cancer using a novel PCR-based platform and correlated miRNA expression profiles with disease outcome. Results: By performing miRNA expression profiling analysis of 55 advanced ovarian tumors, we have shown that three miR-200 miRNAs (miR-200a, miR-200b and miR-429) in the miR-200b-429 cluster are significantly associated with cancer recurrence and overall survival. Further target analysis indicates that these miR-200 miRNAs target multiple genes that are involved in cancer development. In addition, we have also shown that overexpression of this miR-200 cluster inhibits ovarian cancer cell migration. Conclusions: miR-200b-429 may be used as a prognostic marker for ovarian cancer outcome, and low-level expression of miR-200 miRNAs in this cluster predicts poor survival. In addition, our study suggests that miR-200 miRNAs could play an important regulatory role in ovarian cancer.

Original languageEnglish
Pages (from-to)457-464
Number of pages8
JournalGynecologic oncology
Volume114
Issue number3
DOIs
StatePublished - Sep 1 2009

Keywords

  • Expression profiling
  • Ovarian cancer
  • Prognosis
  • Real-time PCR
  • microRNA

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