A panel of 8 miRNAs as a novel diagnostic biomarker in pancreatic cancer. Issue 38 (18th September 2020)

• Record Type: Journal Article
• Authors: Deng, Benyuan; Wang, Ming; Liu, Zhongwu
• Other Names: Severino. Patricia section editor.
• Is Part Of: Medicine. Volume 99:Issue 38(2020)
• Publication Date: 2020-09-18
• Subjects: diagnostic biomarker -- genes -- miRNAs -- pancreatic cancer; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000022261
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: 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.