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Published on: June 13, 2016
Extracellular Vesicle MicroRNA in Malignant Pleural Effusion
Samira Shojaee1, Giulia Romano2, Trinidad M Sanchez2
1Vanderbilt University Medical Center, Department of Internal Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, 1301 Medical Center Drive, Suite B187, Nashville, TN 37232, USA.
Abstract:
Lung and breast cancer are the two most common causes of malignant pleural effusion (MPE). MPE diagnosis plays a crucial role in determining staging and therapeutic interventions in these cancers. However, our understanding of the pathogenesis and progression of MPE at the molecular level is limited. Extracellular Vesicles (EVs) and their contents, including microRNAs (miRNAs), can be isolated from all bodily fluids, including pleural fluid. This study aims to compare EV-miRNA patterns of expression in MPE caused by breast (BA-MPE) and lung (LA-MPE) adenocarcinomas compared to the control group of heart-failure-induced effusions (HF-PE). We conducted an analysis of 24 pleural fluid samples (8 LA-MPE, 8 BA-MPE, and 8 HF-PE). Using NanoString technology, we profiled miRNAs within EVs isolated from 12 cases. Bioinformatic analysis demonstrated differential expression of miR-1246 in the MPE group vs. HF-PE group and miR-150-5p and miR-1246 in the BA-MPE vs. LA-MPE group, respectively. This difference was demonstrated and validated in an independent cohort using real-time PCR (RT-PCR). miRNA-1246 demonstrated 4-fold increased expression (OR: 3.87, 95% CI: 0.43, 35) in the MPE vs. HF-PE group, resulting in an area under the curve of 0.80 (95% CI: 0.60, 0.99). The highest accuracy for differentiating MPE vs. HF-PE was seen with a combination of miRNAs compared to each miRNA alone. Consistent with prior studies, this study demonstrates dysregulation of specific EV-based miRNAs in breast and lung cancer; pleural fluid provides direct access for the analysis of these EV-miRNAs as biomarkers and potential targets and may provide insight into the underlying pathogenesis of tumor progression. These findings should be explored in large prospective studies.
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