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Updated: May 4, 2026
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Circulating biomarkers for detection of ovarian cancer and predicting cancer outcomes
I Shapira1, M Oswald2, J Lovecchio3
11] Monter Cancer Center, NorthShore LIJ, 450 Lakeville Road, Lake Success, NY 11040, USA [2] Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA.
Background:
Securing a diagnosis of ovarian cancer and establishing means to predict outcomes to therapeutics remain formidable clinical challenges. Early diagnosis is particularly important since survival rates are markedly improved if tumour is detected early.
Methods:
Comprehensive miRNA profiles were generated on presurgical plasma samples from 42 women with confirmed serous epithelial ovarian cancer, 36 women diagnosed with a benign neoplasm, and 23 comparably age-matched women with no known pelvic mass.
Results:
Twenty-two miRNAs were differentially expressed between healthy controls and the ovarian cancer group (P<0.05), while a six miRNA profile subset distinguished presurgical plasma from benign and ovarian cancer patients. There were also significant differences in miRNA profiles in presurgical plasma from women diagnosed with ovarian cancer who had short overall survival when compared to women with long overall survival (P<0.05).
Conclusion:
Our preliminary data support the utility of circulating plasma miRNAs to distinguish women with ovarian cancer from those with a benign mass and identify women likely to benefit from currently available treatment for serous epithelial ovarian cancer from those who may not.
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