Deng Benyuan, Wang Ming, Liu Zhongwu
Department of General Surgery, West China Health care Hospital of Sichuan University.
Department of General Surgery, The Third People's Hospital of Chengdu, Chengdu, China.
Medicine (Baltimore). 2020 Sep 18;99(38):e22261. doi: 10.1097/MD.0000000000022261.
Pancreatic cancer (PC) is one of the major causes of cancer mortality in developed countries. Therefore, there is an urgent need to derive biomarkers for early diagnosis of PC patients at high risk.This study was designed to identify a panel of miRNAs that might serve as biomarkers for the early diagnosis of PC.The data containing both PC and control samples were extracted from the Gene Expression Omnibus (GEO) database. EdgeR was applied to identify the differentially expressed miRNAs and genes between PC patients and healthy controls. Then a miRNA-mRNA network was constructed based on the differentially expressed miRNAs and genes. The miRNAs-based biomarker for PC was finally constructed by random forest. Finally, AUC was used to evaluate the performance of miRNAs to classify PC and control samples.A total of 33 differentially expressed miRNAs, 753 differentially expressed genes, and 8 miRNAs (hsa-mir-139, hsa-mir-31, hsa-mir-196b, hsa-mir-221, hsa-mir-203b, hsa-mir-215, hsa-mir-144, and hsa-mir-4433b) that play important roles in PC were identified. The target genes of these miRNAs were found to be mainly enriched in negative regulation of acute inflammatory response cell-substrate responses, and o-glycan processing pathways. The constructed biomarkers based on these 8 miRNAs could distinguish samples coming from PC and healthy controls.We identified a panel of eight-miRNAs that would serve as early diagnostic biomarkers for PC patients.
胰腺癌(PC)是发达国家癌症死亡的主要原因之一。因此,迫切需要找到用于早期诊断高危PC患者的生物标志物。本研究旨在鉴定一组可能作为PC早期诊断生物标志物的miRNA。包含PC样本和对照样本的数据从基因表达综合数据库(GEO)中提取。应用EdgeR来鉴定PC患者和健康对照之间差异表达的miRNA和基因。然后基于差异表达的miRNA和基因构建miRNA-mRNA网络。最终通过随机森林构建基于miRNA的PC生物标志物。最后,使用曲线下面积(AUC)评估miRNA对PC样本和对照样本进行分类的性能。共鉴定出33个差异表达的miRNA、753个差异表达的基因,以及在PC中起重要作用的8个miRNA(hsa-mir-139、hsa-mir-31、hsa-mir-196b、hsa-mir-221、hsa-mir-203b、hsa-mir-215、hsa-mir-144和hsa-mir-4433b)。发现这些miRNA的靶基因主要富集于急性炎症反应的负调控、细胞-底物反应和O-聚糖加工途径。基于这8个miRNA构建的生物标志物能够区分PC样本和健康对照样本。我们鉴定出一组8个miRNA,它们可作为PC患者的早期诊断生物标志物。