Abstract 5404: RNA sequencing-based discovery and validation of a noninvasive microRNA signature for the detection of early-stage ovarian cancer
Authors: Kandimalla Raju , Wang Wei , Hsieh Michael , Gooden Gerald C. , Spillman Monique , Wang Xin , Salhia Bodour , Goel Ajay 
Published: August 2018

Purpose Ovarian cancer (OC) is one of the most lethal gynecological malignancies with a 5-year survival rate of less than 50%. While only 15% of OCs are diagnosed at an early stage (stage 1), more than 75% of these neoplasms at first presentation are already advanced (stage 3 or 4), where a cure is very unlikely and recurrent disease is quite common. Previous attempts at discovering early detection biomarkers for OC have largely failed because of reliance on sub-optimal discovery approaches and the lack of comprehensive patient cohorts. MicroRNAs (miRNAs), which belong to the family of small non-coding RNAs, are frequently dysregulated in cancers including OC. Although several miRNA biomarkers have previously been reported for OC patients, lack of systematic biomarker discovery and validation approach has hampered their clinical translation. To address some of these limitations, we performed a comprehensive and systematic biomarker discovery and validation to identify miRNAs dysregulated in early stage OCs, with the ultimate aim of developing a blood-based early diagnostic assay. Experimental design We performed miRNA expression profiling using a high-throughput small RNA-sequencing in stage 1 ovarian cancer (N=23) and matched normal (N=10) tissues. Differentially expressed miRNAs between cancer and normal tissues were identified using the limma package, which were subsequently validated in a cohort of plasma samples (N=32, healthy individuals and N=32 stage 1 OC patients) using Taqman-based RT-PCR assays. Results Our genome-wide systematic discovery approach led to the identification of eight miRNAs which were significantly upregulated in OC vs. adjacent normal tissues. Of note, even individual miRNAs achieved AUROC values ranging from 0.80 to 0.89; however, the combined panel of these 8 miRNAs achieved an even greater AUROC of 0.90 in detecting stage 1 OC patients (p&lt;0.001). Subsequently, we analyzed this 8-miRNA panel in a set of 64 plasma (N=32, Healthy subjects and N=32, stage 1 OC patients) using RT-PCR assays. We performed binary logistic regression and ROC analysis to evaluate the diagnostic accuracy of these biomarkers. Interestingly, in accordance with the tissue findings, we achieved AUROC values ranging from 0.70 to 0.90 for individual biomarkers, while the combination panel achieved an impressive AUROC of 0.99 (95% CI: 0.98-1.00, p&lt;0.0001) for the identification of early stage ovarian cancer patients. Conclusions In conclusion, our RNA sequencing based comprehensive biomarker discovery identified an 8-miRNA panel that demonstrated a robust diagnostic accuracy in not only tissue specimens, but also in the plasma specimens from early stage OC patients. Further evaluation of these miRNAs in multicenter retrospective and prospective cohorts might lead to the development of a non-invasive diagnostic, as well as a population-screening assay for OC patients.

Citation Format: Raju Kandimalla, Wei Wang, Michael Hsieh, Gerald C. Gooden, Monique Spillman, Xin Wang, Bodour Salhia, Ajay Goel. RNA sequencing-based discovery and validation of a noninvasive microRNA signature for the detection of early-stage ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5404.