4.6 Article

The detection of differentially expressed microRNAs from the serum of ovarian cancer patients using a novel real-time PCR platform

期刊

GYNECOLOGIC ONCOLOGY
卷 112, 期 1, 页码 55-59

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygyno.2008.08.036

关键词

Ovarian cancer; MicroRNA; Biomarkers

资金

  1. Jacquelyn L. Wells Endowment in Ovarian Cancer Research
  2. The Ohio State University

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Objective. To determine the utility of serum miRNAs as biomarkers for epithelial ovarian cancer. Methods. Twenty-eight patients with histologically confirmed epithelial ovarian cancer were identified from a tissue and serum bank. Serum was collected prior to definitive therapy. Fifteen unmatched, healthy controls were used for comparison. Serum was obtained from all patients. RNA was extracted using a derivation of the single step Trizol method. The RNA from 9 cancer specimens was compared to 4 normal specimens with real-time PCR using the TaqMan Array Human MicroRNA panel. Twenty-one miRNAs were differentially expressed between normal and patient serum. Real-time PCR for the 21 individual miRNAs was performed on the remaining 19 cancer specimens and 11 normal specimens. Results. Eight mRNAs of the original twenty-one were identified that were significantly differentially expressed between cancer and normal specimens using the comparative C-t method. MiRNAs-21, 92, 93, 126 and 29a were significantly over-expressed in the serum from cancer patients compared to controls (p <.01). MiRNAs-155, 127 and 99b were significantly under-expressed (p <.01). Additionally, miRs-21, 92 and 93 were over-expressed in 3 patients with normal pre-operative CA-125. Conclusion. We demonstrate that the extraction of RNA and subsequent identification of miRNAs from the serum of individuals diagnosed with ovarian cancer is feasible. Real-time PCR-based microarray is a novel and practical means to performing high-throughput investigation of serum RNA samples. miRNAs-21, 92 and 93 are known oncogenes with therapeutic and biomarker potential. (c) 2008 Elsevier Inc. All rights reserved.

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