Bioinformatics Analysis of a Prognostic miRNA Signature and Potential Key Genes in Pancreatic Cancer.
Bioinformatics Analysis of a Prognostic miRNA Signature and Potential Key Genes in Pancreatic Cancer.
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胰腺癌预后 miRNA 特征和潜在关键基因的生物信息学分析。
DOI：
10.3389/fonc.2021.641289
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发表时间：
2021
影响因子：
4.7
通讯作者：
Huang Z
中科院分区：
文献类型：
--
作者：
Chen S;Gao C;Yu T;Qu Y;Xiao GG;Huang Z
本研究基于生物信息学分析筛选与胰腺癌预后相关的miRNAs及其关键靶基因，为胰腺癌的预后和治疗提供靶点。R软件分别从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载差异表达的miRNA（DEM）和基因（DEG）。基于miRNA构建miRNA考克斯比例风险回归模型，并生成miRNA预后模型。用TargetScan和miRDB预测的靶基因，再用DEG进行测序，得到共同基因。对共同基因的功能进行京都基因和基因组百科全书（KEGG）和基因本体（GO）分析。利用STRING数据库构建了蛋白质-蛋白质相互作用（PPI）网络，并利用Cytoscape软件进行可视化。还用Cytoscape的MCODE和cytoHubba插件筛选关键基因。最后，还建立了由关键基因形成的预后模型，以帮助评估该筛选过程的可靠性。构建了一个包含4个下调的miRNAs（hsa-mir-424、hsa-mir-3613、hsa-mir-4772和hsa-mir-126）的胰腺癌预后模型。共有118个共同基因在两个KEGG途径和33个GO功能注释中富集，包括细胞外基质（ECM）-受体相互作用和细胞粘附。同时获得了9个与胰腺癌相关的关键基因：MMP 14、ITGA 2、THBS 2、COL 1A 1、COL 3A 1、COL 11 A1、COL 6A 3、COL 12 A1和COL 5A 2。由9个关键基因组成的预测模型也具有良好的预测能力。由4种miRNAs组成的预后模型可以可靠地预测胰腺癌患者的预后。此外，筛选出的9个关键基因，也可形成可靠的预后模型，与胰腺癌的发生发展有显著相关性。其中一个新的miRNA（hsa-mir-4772）和两个新的胰腺癌相关基因（COL 12 A1和COL 5A 2）具有很大的潜力，可作为胰腺癌的预后因子和治疗靶点。
In this study, miRNAs and their critical target genes related to the prognosis of pancreatic cancer were screened based on bioinformatics analysis to provide targets for the prognosis and treatment of pancreatic cancer. R software was used to screen differentially expressed miRNAs (DEMs) and genes (DEGs) downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, respectively. A miRNA Cox proportional hazards regression model was constructed based on the miRNAs, and a miRNA prognostic model was generated. The target genes of the prognostic miRNAs were predicted using TargetScan and miRDB and then intersected with the DEGs to obtain common genes. The functions of the common genes were subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. A protein-protein interaction (PPI) network of the common genes was constructed with the STRING database and visualized with Cytoscape software. Key genes were also screened with the MCODE and cytoHubba plug-ins of Cytoscape. Finally, a prognostic model formed by the key gene was also established to help evaluate the reliability of this screening process. A prognostic model containing four downregulated miRNAs (hsa-mir-424, hsa-mir-3613, hsa-mir-4772 and hsa-mir-126) related to the prognosis of pancreatic cancer was constructed. A total of 118 common genes were enriched in two KEGG pathways and 33 GO functional annotations, including extracellular matrix (ECM)-receptor interaction and cell adhesion. Nine key genes related to pancreatic cancer were also obtained: MMP14, ITGA2, THBS2, COL1A1, COL3A1, COL11A1, COL6A3, COL12A1 and COL5A2. The prognostic model formed by nine key genes also possessed good prognostic ability. The prognostic model consisting of four miRNAs can reliably predict the prognosis of patients with pancreatic cancer. In addition, the screened nine key genes, which can also form a reliable prognostic model, are significantly related to the occurrence and development of pancreatic cancer. Among them, one novel miRNA (hsa-mir-4772) and two novel genes (COL12A1 and COL5A2) associated with pancreatic cancer have great potential to be used as prognostic factors and therapeutic targets for this tumor.
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影响因子：
3.8
作者：
Arafat H;Lazar M;Salem K;Chipitsyna G;Gong Q;Pan TC;Zhang RZ;Yeo CJ;Chu ML
通讯作者：
Chu ML
DOI：
10.1038/s41436-018-0285-0
发表时间：
2019-04
期刊：
Genetics in medicine : official journal of the American College of Medical Genetics
影响因子：
--
作者：
Booth KT;Askew JW;Talebizadeh Z;Huygen PLM;Eudy J;Kenyon J;Hoover D;Hildebrand MS;Smith KR;Bahlo M;Kimberling WJ;Smith RJH;Azaiez H;Smith SD
通讯作者：
Smith SD
影响因子：
--
作者：
Dong P;Xiong Y;Yue J;Hanley SJB;Watari H
通讯作者：
Watari H
与癌症相关的成纤维细胞对COL11A1的过表达：胰腺癌中基质标记的临床相关性。
影响因子：
3.7
作者：
García-Pravia C;Galván JA;Gutiérrez-Corral N;Solar-García L;García-Pérez E;García-Ocaña M;Del Amo-Iribarren J;Menéndez-Rodríguez P;García-García J;de Los Toyos JR;Simón-Buela L;Barneo L
通讯作者：
Barneo L
胰腺癌细胞增殖过程中 miR-26a 介导的细胞周期蛋白 E2 转录后调控的丧失和患者生存率下降
影响因子：
3.7
作者：
Deng J;He M;Chen L;Chen C;Zheng J;Cai Z
通讯作者：
Cai Z