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MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening
Published on: October 26, 2017
Bioinformatics-based prediction of hsa-miR-4651 and hsa-miR-608 as novel biomarkers for diagnosing silicosis
Jing Wu1, Yimin Shi2, Cuiyun Zuo3
1School of Medical Sciences Xiamen Medical College, Xiamen, China.
Objective:
Based on GEO database and bioinformatics to screen silicosis-related differentially expressed genes and analyze the biological functions, in order to provide new ideas and methods for the treatment of silicosis fibrosis.
Methods:
We predicted microRNAs related to silicosis through bioinformatics and verified the expression of microRNAs in patients with silicosis and healthy people by Real-time Fluorescence Quantitative PCR.
Results:
Three key genes (LCN2, MMP9, and CCL2) were identified, with hsa-miR-4651, hsa-miR-608, and hsa-miR-3151-5p predicted as their regulatory miRNAs. Hsa-miR-4651 and hsa-miR-608 were significantly upregulated in silicosis patient plasma, indicating their potential as biomarkers for silicosis diagnosis.
Conclusions:
Hsa-miR-4651 and hsa-miR-608 were identified as potential novel biomarkers for silicosis diagnosis, offering new insights for clinical diagnosis and treatment of silicosis fibrosis.
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MicroRNAs
lncRNA - Long Non-coding RNAs

