Wang Dan, Xin Lei, Lin Jin-Huan, Liao Zhuan, Ji Jun-Tao, Du Ting-Ting, Jiang Fei, Li Zhao-Shen, Hu Liang-Hao
Department of Gastroenterology Digestive Endoscopy Center, Changhai Hospital, the Second Military Medical University, Shanghai, China.
Medicine (Baltimore). 2017 May;96(21):e6668. doi: 10.1097/MD.0000000000006668.
The aim of this study was to explore the underlying molecular mechanism and potential molecular biomarkers of chronic pancreatitis (CP) and construct a miRNA-mRNA regulation network.
To explore the involvement of miRNAs in CP, we downloaded the miRNA and mRNA expression profiles of CP patients and healthy controls and identified the differentially expressed miRNAs and genes. Functional analysis was conducted and significant pathways were utilized. Finally, the miRNA-mRNA regulation network of CP was constructed.
A total of 44 miRNA risk gene pathway relationships were identified, and a complex regulation network was constructed with 3 genes (ABL1, MYC, and ANAPC13) having the highest degree in affecting the network of CP. Importantly, 4 risk genes (NOTCH3, COX5A, THBS1, and KARS) and 1 risk miRNA (hsa-miR-324-5p) were identified with high prediction accuracy.
In conclusion, we analyzed miRNAs and mRNAs expression profiles in CP, 1 risk miRNA, and 4 risk genes were identified with high prediction accuracy as biomarkers of CP. Although further evaluation in clinical study is needed, our findings provide new insights into the pathogenesis of CP and may improve the diagnosis and therapy by identifying novel targets.
本研究旨在探索慢性胰腺炎（CP）潜在的分子机制和分子生物标志物，并构建miRNA - mRNA调控网络。
为探究miRNA在CP中的作用，我们下载了CP患者和健康对照的miRNA和mRNA表达谱，鉴定差异表达的miRNA和基因。进行功能分析并利用显著的通路。最后，构建CP的miRNA - mRNA调控网络。
共鉴定出44个miRNA风险基因通路关系，构建了一个复杂的调控网络，其中3个基因（ABL1、MYC和ANAPC13）在影响CP网络方面具有最高的度数。重要的是，鉴定出4个风险基因（NOTCH3、COX5A、THBS1和KARS）和1个风险miRNA（hsa - miR - 324 - 5p），预测准确性高。
总之，我们分析了CP中的miRNA和mRNA表达谱，鉴定出1个风险miRNA和4个风险基因，作为CP的生物标志物预测准确性高。尽管需要在临床研究中进一步评估，但我们的发现为CP的发病机制提供了新见解，并可能通过识别新靶点改善诊断和治疗。
