胰腺癌转移相关基因的生物信息学分析
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摘要
目的通过对胰腺癌转移相关基因芯片数据进行生物信息学分析,为探索胰腺癌转移的分子机制提供理论依据。方法从基因芯片公共数据库(GEO)下载胰腺癌转移相关基因芯片数据,经R语言数据预处理及筛选差异表达基因后,分别通过DAVID在线分析软件、STRING在线数据库、Cytoscape软件和GEPIA在线分析工具进行差异表达基因的功能注释、通路分析、蛋白互作网络分析及预后分析。结果共筛选出109个胰腺癌转移差异表达基因,其中上调49个,下调60个;功能注释和通路分析发现,这些基因主要集中在急性炎症反应、蛋白质活化级联、细胞外基质构建、细胞外基质分解等生物学过程,以及补体和凝血级联、PPAR信号通路、PI3K-Akt信号通路、ECM受体相互作用等通路。蛋白互作网络分析获得2个关键模块和10个关键基因,分别为ORM1、IGFBP1、HPX、F2、APOA1、ALB、PLG、SERPINC1、KNG1和INS。预后分析得到4个基因的表达水平与胰腺癌患者总生存时间显著相关,分别是SCG5、CRYBA2、CPE和CHGB。结论通过生物信息学的方法对胰腺癌转移相关基因芯片数据进行数据挖掘,为深入研究胰腺癌转移的相关分子机制提供了理论依据。
Objective To provide theoretical basis for the molecular mechanism of the development of metastatic pancreatic cancer by screening differentially expressed genes based on bioinformatical analysis. Methods We analyzed metastasis-related pancreatic cancer microarray datasets derived from GEO database. After preprocessing the data, R language package limma was used to screen differentially expressed genes. Then DAVID online tool was used for GO annotation and KEGG pathway enrichment analysis. STRING online database and Cytoscape software were utilized for protein-protein interaction network analysis. GEPIA online tool was used to evaluate prognostic performance. Results We found 109 differentially expressed genes between metastatic pancreatic cancer tissues and primary pancreatic cancer tissues. Of them 49 genes were up-regulated and 60 were down-regulated. Enrichment analysis indicated that most of the genes were enriched in acute inflammatory response, complement and coagulation cascades, PPAR signaling pathway, and PI3 K-Akt signaling pathway. Protein-protein interaction network analysis screened 2 key modules and 10 key genes(ORM1, IGFBP1, HPX, F2, APOA1, ALB, PLG, SERPINC1, KNG1 and INS). Prognostic analysis showed that 4 genes(SCG5, CRYBA2, CPE, and CHGB) were significantly associated with the patients' OS. Conclusion The internal biological information in metastatic pancreatic cancer can be revealed by integrative bioinformaticalanalysis, providing theoretical basis for further research on molecular mechanism of metastatic pancreatic cancer.
Objective To provide theoretical basis for the molecular mechanism of the development of metastatic pancreatic cancer by screening differentially expressed genes based on bioinformatical analysis. Methods We analyzed metastasis-related pancreatic cancer microarray datasets derived from GEO database. After preprocessing the data, R language package limma was used to screen differentially expressed genes. Then DAVID online tool was used for GO annotation and KEGG pathway enrichment analysis. STRING online database and Cytoscape software were utilized for protein-protein interaction network analysis. GEPIA online tool was used to evaluate prognostic performance. Results We found 109 differentially expressed genes between metastatic pancreatic cancer tissues and primary pancreatic cancer tissues. Of them 49 genes were up-regulated and 60 were down-regulated. Enrichment analysis indicated that most of the genes were enriched in acute inflammatory response, complement and coagulation cascades, PPAR signaling pathway, and PI3 K-Akt signaling pathway. Protein-protein interaction network analysis screened 2 key modules and 10 key genes(ORM1, IGFBP1, HPX, F2, APOA1, ALB, PLG, SERPINC1, KNG1 and INS). Prognostic analysis showed that 4 genes(SCG5, CRYBA2, CPE, and CHGB) were significantly associated with the patients' OS. Conclusion The internal biological information in metastatic pancreatic cancer can be revealed by integrative bioinformaticalanalysis, providing theoretical basis for further research on molecular mechanism of metastatic pancreatic cancer.
引文
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[22]KIM JC,HA YJ,TAK KH,et al.Complex behavior of AL-DH1A1 and IGFBP1in liver metastasis from a colorectal cancer[J].PLoS One,2016,11(5):e0155160.
[2]HARADA T,CHELALA C,CRNOGORAC-JURCEVIC T,et al.Genome-wide analysis of pancreatic cancer using microarray-based techniques[J].Pancreatology,2009,9(1-2):13-24.
[3]VILLASENOR-PARK J,ORTEGA-LOAYZA AG.Microarray technique,analysis,and applications in dermatology[J].J Invest Dermatol,2013,133(4):e7.
[4]BARRY S,CHELALA C,LINES K,et al.S100P is a metastasis-associated gene that facilitates transendothelial migration of pancreatic cancer cells[J].Clin Exp Metastas,2013,30(3):251-264.
[5]VANBA,VANKELECOM H,VAN ER,et al.Molecular markers associated with outcome and metastasis in human pancreatic cancer[J].J Exp Clin Cancer Res,2012,31(1):68.
[6]MOFFITT RA,RAOUD M,FLATE EL,et al.Virtual microdissection identifies distinct tumor-and stroma-specific subtypes of pancreatic ductal adenocarcinoma[J].Nat Genet,2015,47(10):1168-1178.
[7]BARRETT T,TROUP DB,WILHITE SE,et al.NCBI GEO:mining tens of millions of expression profiles-database and tools update[J].Nucleic Acids Res,2007,35(Database issue):760-765.
[8]DIBOUN I,WERNISCH L,ORENGO CA,et al.Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma[J].BMC Genomics,2006,7(1):252.
[9]RITCHIE ME,PHIPSON B,WU D,et al.Limma powers differential expression analyses for RNA-sequencing and microarray studies[J].Nucleic Acids Res,2015,43(7):e47.
[10]DENNIS G,SHERMAN BT,HOSACK DA,et al.DAVID:Database for annotation,visualization,and integrated discovery[J].Genome Biol,2003,4(5):P3.
[11]HUANG DW,SHERMAN BT,LEMPICKI RA.Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources[J].Nat Protoc,2009,4(1):44.
[12]SZKLARCZYK D,FRANCESCHINI A,WYDER S,et al.STRING v10:Protein-protein interaction networks,integrated over the tree of life[J].Nucleic Acids Res,2015,43(Database issue):447-452.
[13]KOHL M,WIESE S,WARSCHEID B.Cytoscape:Software for visualization and analysis of biological networks[J].Methods Mol Biol,2011,696(696):291-303.
[14]TANG Z,LI C,KANG B,et al.GEPIA:A web server for cancer and normal gene expression profiling and interactive analyses[J].Nucleic Acids Res,2017,45(Web Server issue):98-102.
[15]KAMISAWA T,WOOD LD,ITOI T,et al.Pancreatic cancer[J].Lancet,2016,388(10039):73-85.
[16]LI Y,ZHANG DW,LIN DQ,et al.Peroxisome proliferatoractivated receptor-γinhibits pancreatic cancer cell invasion and metastasis via regulating MMP-2 expression through PTEN[J].Mol Med Rep,2015,12(4):6255-6260.
[17]WANG MC,JIAO M,WU T,et al.Polycomb complex protein BMI-1 promotes invasion and metastasis of pancreatic cancer stem cells by activating PI3K/AKT signaling,an ex vivo,in vitro,and in vivo study[J].Oncotarget,2016,7(8):9586-9599.
[18]LIU X,TAN X,LIU P,et al.Phosphoglycerate mutase 1(PGAM1)promotes pancreatic ductal adenocarcinoma(PDAC)metastasis by acting as a novel downstream target of PI3K/Akt/mTOR pathway[J].Oncol Res,2018,26(7):1123-1131.
[19]RUMMAN M,JUNG KH,FANG Z,et al.HS-173,a novel PI3K inhibitor suppresses EMT and metastasis in pancreatic cancer[J].Oncotarget,2016,7(47):78029-78047.
[20]THAKUR A,BOLLIG A,WU J,et al.Gene expression profiles in primary pancreatic tumors and metastatic lesions of Elac-myctransgenic mice[J].Mol Cancer,2008,7(1):11.
[21]GONG J,SHEN S,YANG Y,et al.Inhibition of FASN suppresses migration,invasion and growth in hepatoma carcinoma cells by deregulating the HIF-1α/IGFBP1 pathway[J].Int JOncol,2017,50(3):883-892.
[22]KIM JC,HA YJ,TAK KH,et al.Complex behavior of AL-DH1A1 and IGFBP1in liver metastasis from a colorectal cancer[J].PLoS One,2016,11(5):e0155160.