Zhou Xintong, Dang Shengchun, Jiang Huaji, Gu Min
Department of General Surgery, The Affiliated Zhangjiagang Hospital of Soochow University, Zhangjiagang, China.
Department of General Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
J Gastrointest Oncol. 2021 Jun;12(3):1164-1179. doi: 10.21037/jgo-21-224.
Pancreatic adenocarcinoma (PAAD) has a high rate of mortality. Unfortunately, it is difficult to diagnosis. This study aimed to develop a more in-depth understanding of the disease.
A total of 177 patients with PAAD were recruited from The Cancer Genome Atlas (TCGA) database. Microarray analysis was performed to identify differentially expressed genes (DEGs) in PAAD. The microarray data were adapted to the ingenuity pathway analysis (IPA) for annotation and visualization, followed by protein-protein interaction (PPI) network analysis. transwell migration assays were conducted to explore the molecular and functional characteristics of pancreatic adenocarcinoma cells (PANC-1) with stable low expression of G-protein signaling modulator 2 (). Expression of and the associated hub genes were detected by reverse transcription-quantitative polymerase chain reaction (qPCR).
The overexpression of was proved in PAAD, as compared with the healthy tissues, as well as its correlation with history of chronic pancreatitis, T stage, TNM stage and tumor grade. We described it as an independent prognostic factor and found that it could influence the infiltration of immune cells in the tumor microenvironment. Silencing of restrained the and migration of the cells. Microarray analysis identified 1,631 DEGs in PAAD cells. The PPI network analysis identified hub genes including , , , , , , , and , and their relationship with was confirmed by qPCR.
is a novel prognostic factor and therapeutic target for PAAD. promoted the migration of pancreatic adenocarcinoma cells .Targeting and its downstream genes may prolong the survival time of patients with PAAD.
胰腺腺癌（PAAD）死亡率高。不幸的是，其诊断困难。本研究旨在更深入地了解该疾病。
从癌症基因组图谱（TCGA）数据库招募了总共177例PAAD患者。进行微阵列分析以鉴定PAAD中差异表达基因（DEG）。将微阵列数据应用于 Ingenuity 通路分析（IPA）进行注释和可视化，随后进行蛋白质 - 蛋白质相互作用（PPI）网络分析。进行Transwell迁移试验以探索G蛋白信号调节剂2稳定低表达的胰腺腺癌细胞（PANC - 1）的分子和功能特征。通过逆转录定量聚合酶链反应（qPCR）检测G蛋白信号调节剂2及相关枢纽基因的表达。
与健康组织相比，PAAD中证实了G蛋白信号调节剂2的过表达，以及其与慢性胰腺炎病史、T分期、TNM分期和肿瘤分级的相关性。我们将其描述为独立的预后因素，并发现它可影响肿瘤微环境中免疫细胞的浸润。沉默G蛋白信号调节剂2可抑制细胞的侵袭和迁移。微阵列分析在PAAD细胞中鉴定出1631个DEG。PPI网络分析鉴定出枢纽基因，包括[具体基因1]、[具体基因2]、[具体基因3]、[具体基因4]、[具体基因5]、[具体基因6]、[具体基因7]、[具体基因8]和[具体基因9]，并且通过qPCR证实了它们与G蛋白信号调节剂2的关系。
G蛋白信号调节剂2是PAAD的一种新型预后因素和治疗靶点。G蛋白信号调节剂2促进胰腺腺癌细胞的迁移。靶向G蛋白信号调节剂2及其下游基因可能延长PAAD患者的生存时间。
