Abstract 760: miRNA and mRNA detection in plasma-derived extracellular vesicles (EVs) using the nCounter NanoString platform

Abstract

Abstract Introduction: Although genetic and transcriptomic analysis of tumor tissue can provide useful information for prognosis and treatment decision making, 5-20% of advanced-stage lung cancer patients cannot be biopsied, or the amount of tumor tissue is insufficient for successful analysis. In addition, repeated sampling is often not possible. Liquid biopsies have shown potential to be used as minimally invasive, safe and sensitive alternative for tissue biopsies, but lack of standardized protocols is hampering implementation in the clinic. The nCounter platform could provide the solution for this problem, with an easy-to-use technical workflow and straightforward data analysis. Extracellular vesicles (EVs) are mediators of intercellular communication and may play a role in early cancer development. Therefore, RNA found within EVs can be used as a biomarker for cancer development and progression. In addition, the lipid bilayer of EVs makes their cargo particularly stable and allows the use of biobank stored samples. Methods: EVs were isolated from 600 μL plasma of 19 cancer patients and 10 healthy donors, using the miRCURY® Exosome Serum/Plasma Kit (Qiagen), and total RNA was extracted using TRI Reagent® (MRC Inc) or the automated QIAsymphony® System (Qiagen) with the DSP Virus/Pathogen Kit, after RNAse A (Sigma-Aldrich) treatment to remove plasma cell-free RNA. The Human Immune V2 panel (NanoString Technologies), including 600 mRNA targets, was used to analyze EV-derived mRNA after a pre-amplification (pre-amp) step with the Low RNA Input Amplification Kit. In addition, the Human V3 miRNA panel (NanoString Technologies), including 800 miRNA targets, was used to analyze the same EV samples without pre-amp. Results: Total amount of RNA isolated from EVs was found to be significantly higher using TRI Reagent®, versus automated RNA isolation. In addition, the conditions for the pre-amp step were tested and optimized. A pre-amp of 10 cycles for the mRNA panel was shown to be sufficient to detect mRNA targets in EVs without saturation, and the NanoString retrotranscription (RT) enzyme outperformed the other RT enzyme tested. In addition, supernatant collected during EV isolation was also analyzed, and results showed that the RNA targets were derived from within the EVs. On average, 337 mRNA targets were detected within the EVs, while 157 miRNA targets were detected in the same samples without pre-amp, with no significant differences between cancer patients and healthy donors. Interestingly, most differentially expressed (DE) mRNAs were shown to be lower expressed in cancer patients, while most DE miRNAs were found to be higher expressed in cancer patients. Conclusion: Our results demonstrate that the nCounter NanoString platform can be used for miRNA and mRNA detection in plasma-derived EVs from cancer patients and healthy donors. Further studies will focus on specific mRNA and miRNA expression differences between these two cohorts. Citation Format: Jillian Wilhelmina Bracht, Ana Gimenez-Capitan, Chung-Ying Huang, Carlos Pedraz-Valdunciel, Joselyn Valarezo, Sarah Warren, Rafael Rosell, Miguel Angel Molina-Vila. miRNA and mRNA detection in plasma-derived extracellular vesicles (EVs) using the nCounter NanoString platform [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 760.