The authors thank Peter Andersen for technical assistance in FACS, Karen Fox-Talbot for immunohistochemistry, and Renjun Zhu for the Matlab scripts used to process the electrophysiology recordings. The authors acknowledge the following funding sources: Magic That Matters Fund for Cardiovascular Research, Johns Hopkins Institute for NanoBioTechnology Seed Grant, Zegar Family Foundation and the Maryland Stem Cell Research Fund (2016-MSCRFI-2735).
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It is well known that dysregulations of miRNAs are important to keep the malignant phenotype of many tumors. The distorted and unique expression profile of miRNAs in different types and subsets of tumors make miRNAs an attractive source of sensitive biomarkers [19]. Importantly, miRNAs not only regulate the expression of oncogenes and tumor suppressors but also play the roles as oncogenes and tumor suppressors. It is very important to screen the expression of these miRNAs in tumor and normal tissues by using miRNA profiling. In our study, we compared the differential expression of 1145 miRNAs between carcinoid tissues vs. matched normal lung tissues, by using miRNA microarray, a high throughput approach. Recently, Kolbert et al. [20] compared the results of miRNA expression levels by using several platforms, including Illumina miRNA arrays and Illumina Next Generation Sequencing, and verified these results with those of quantitative PCR data. It was demonstrated that the within-platform reproducibility for each method was consistently high and detection of miRNA transcripts was similar across multiple platforms. As a result, we believe it is reliable to test the levels of miRNA expression by using Illumnia arrays. 2ff7e9595c
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