Identification of hub genes and key pathways targeted by miRNAs in pancreatic ductal adenocarcinoma: MAPK3/8/9 and TGFBR1/2

IF 0.5 Q4 GENETICS & HEREDITY
Cigdem Gungormez
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Abstract

Ductal adenocarcinoma of the pancreas(PDAC) is one of the malignancies with the worst prognosis still among solid tumors. Local and distant spread is observed at the time of diagnosis in a very significant part of patients. In recent years, significant improvements have been made in pancreatic cancer surgery, and serious decreases in morbidity and mortality rates have been detected, especially in specific centers. Studies on target gene therapy in all types of cancer, including pancreatic cancer, are very laborious and costly. For this reason, it provides convenience for research aimed at determining clinical markers by using bioinformatics software. In this study, it was aimed to determine the target gene and pathway by performing transcriptome analysis of 14 control and 28 PDAC data belonging to GSE123377 and GSE 163031. As a result of the analysis, it was found that 49 genes were in direct interaction with PDAC by determining the targets of 46 miRNAs with DIANA Path, whose expression differences were determined as a result of the analysis. Based on the PPI topological analysis, it was determined that 46 miRNAs of prostate cancer directly target 12 hub proteins (BRAF, STAT3,TGFBR1,SMAD2,SMAD3, TP53, TGFBR2, KRAS, MAPK1,MAPK3, MAPK8 and MAPK9). Functional Enrichment Analysis and biological process; cell communication with 59.18% and signal transmission with 73.47%; It was observed that protein serine/threonine kinase activity in molecular function was associated with a 22.45% effect on pathways. Thus, it is planned to support research by providing a system-level view by processing data networks for potential diagnostic biomarkers and target gene therapy for early diagnosis of PDAC.

确定胰腺导管腺癌中 miRNA 靶向的枢纽基因和关键通路:MAPK3/8/9 和 TGFBR1/2
胰腺导管腺癌(PDAC)是实体瘤中预后最差的恶性肿瘤之一。很大一部分患者在确诊时就已出现局部和远处扩散。近年来,胰腺癌手术取得了重大进展,发病率和死亡率大幅下降,特别是在一些特定中心。对包括胰腺癌在内的各类癌症进行靶向基因治疗的研究非常耗费精力和财力。因此,利用生物信息学软件确定临床标志物的研究就变得非常方便。本研究旨在通过对属于 GSE123377 和 GSE 163031 的 14 个对照组和 28 个 PDAC 数据进行转录组分析,确定目标基因和通路。分析结果显示,通过 DIANA Path 确定了 46 个 miRNA 的靶标,发现 49 个基因与 PDAC 有直接相互作用,分析结果确定了这些基因的表达差异。根据 PPI 拓扑分析,确定前列腺癌的 46 个 miRNA 直接靶向 12 个枢纽蛋白(BRAF、STAT3、TGFBR1、SMAD2、SMAD3、TP53、TGFBR2、KRAS、MAPK1、MAPK3、MAPK8 和 MAPK9)。功能富集分析和生物过程;细胞通讯占 59.18%,信号传递占 73.47%;据观察,分子功能中蛋白丝氨酸/苏氨酸激酶活性对通路的影响占 22.45%。因此,计划通过处理数据网络来提供系统级视图,从而为潜在的诊断生物标志物和早期诊断 PDAC 的靶向基因治疗提供研究支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Human Gene
Human Gene Biochemistry, Genetics and Molecular Biology (General), Genetics
CiteScore
1.60
自引率
0.00%
发文量
0
审稿时长
54 days
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