Harnessing the power of serum microRNAs to predict surgical outcome for women with ovarian cancer — ASN Events
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  3. Harnessing the power of serum microRNAs to predict surgical outcome for women with ovarian cancer

Harnessing the power of serum microRNAs to predict surgical outcome for women with ovarian cancer (#145)

Jaynish S Shah 1 , Gregory Gard 2 , Patsy Soon 3 , Deborah J Marsh 1
  1. Kolling Institute of Medical Research, Royal North Shore Hospital and University of Sydney, St Leonards, NSW, Australia
  2. Obstetrics and Gynaecology, Royal North Shore Hospital and University of Sydney, St Leonards
  3. Ingham Institute of Applied Medical Research, University of New South Wales, Sydney, NSW, Australia

Optimal cytoreduction, complete surgical removal of the tumour, is one of the most important prognostic factors for women with ovarian cancer, yet remains challenging to predict prior to surgery. A molecular tool to assist in this prediction, in combination with other clinical factors, could help plan surgery and decide the best treatment options for individual patients. An emerging hypothesis suggests that genetic makeup of the tumour could influence the surgical outcome. Short RNAs, called microRNAs, are promising biomarkers due to their remarkable stability and disease-specific expression.  We tested if circulating microRNAs could separate women with ovarian cancer from healthy women and, further,  predict their surgical outcome.         

Methods and materials:

The study was setup in two phases containing 15 healthy, 15 optimally and 13 suboptimally cytoreduced (>10mm) ovarian cancer patients each. Pre-surgical sera were sourced from the Kolling’s Tumour bank. Expression of 167 microRNAs was measured using the Serum/Plasma focus panel (Exiqon) in the ‘Discovery’ phase. A total of 48 microRNAs including promising candidates, endogenous reference microRNAs and various controls were validated using the Custom Pick-&-Mix panel (Exiqon) in the second phase. Levels of the serum biomarker CA-125 were measured by sandwich ELISA (R&D Systems). Data were analysed using GenEx software (v 6.0, Exiqon) and statistical language R.

Results and conclusions:

Two microRNAs were found to be significantly different between sera of healthy women and ovarian cancer patients in both phases (Benjamini-Hochberg adjusted P <0.05; AUC: 0.7714 – 0.9000). One microRNA was differentially expressed in optimally versus suboptimally cytoreduced patients in both phases (P <0.05; AUC: 0.8360 and 0.8564). The microRNA outperformed CA-125 levels in predicting surgical outcomes (AUC: 0.6988). Pooled data from both phases and the effect of combining CA-125 levels with microRNAs on predicting the surgical outcome will be presented.