胰腺癌相关糖尿病致病基因表达谱的分析

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目的 探讨胰腺癌相关糖尿病( PCA-DM)致病基因的表达谱,为PCA-DM发病机制的研究提供新线索. 方法 对前期获得的4例PCA-DM患者、4例无糖尿病胰腺癌( PC)患者和4例慢性胰腺炎( CP)患者胰腺组织基因芯片分析结果进一步进行盒图、火山图、热图分析;基因相互作用网络分析;染色体定位分析;Gene ontology ( GO)分析,并采用实时PCR对差异表达基因进行验证. 结果 芯片检测质量可靠. PCA-DM与无糖尿病PC差异表达基因共2778个,其中表达倍数差异>10的有123个基因;无糖尿病PC与CP差异表达基因共7475个,其中表达倍数差异>10的有730个. PCA-DM与无糖尿病PC差异表达基因的数量及差异倍数明显少于无糖尿病PC与CP的差异表达基因. PCA-DM和无糖尿病PC的差异表达基因大多分布于PC与CP差异表达基因的染色体位点上. GO分析显示,与药物代谢、色素沉着、GTPase活性有关的条目上调,而与蛋白代谢、核酸代谢有关的条目下调. 在PCA-DM相关基因网络中,HSPA1A、CSNK1A1、EIF4A2、MYCBP2、PRKRA、NGFR等40 个基因参与PCA-DM发生. TFF1、MSMB、NOX1等13个基因对PCA-DM具有潜在诊断价值. 结论 建立了PCA-DM致病基因表达谱,发现了潜在的致病基因及具有潜在诊断价值的基因.“,”Objective To explore the gene expression profiles related to pathogenesis of pancreatic cancer associated diabetes ( PCA-DM) and provide new clues for the study of PCA-DM.Methods The tissues of four patients with pancreatic ductal adenocarcinoma with diabetes ( PCA-DM) , four patients with pancreatic ductal adenocarcinoma without diabetes (PC) and four patients with chronic pancreatitis (CP) were analyzed by microarrays individually , and following box diagram , volcano diagram , heat map analysis , gene interaction network analysis;chromosome positioning analysis , gene ontology ( GO) analysis, and RT-PCR was used to confirm the results.Results Data showed that the microarray analysis was well controlled in quality .There were 2 778 differentially expressed genes of pancreatic cancer tissues between PCA-DM and PC individuals , among them, there were 123 genes with difference expression >10 folds; and there were 7 475 differentially expressed genes between PC and CP , among them, there were 730 genes with difference expression >10 folds. The differentially expressed genes between PCA-DM and PC individuals were less than those of PC and CP in quantity and fold changes .Furthermore, the majority of differentially expressed genes between PCA-DM and PC were located near the PC and CP on the genome .GO analysis demonstrated that the overrepresented items included drug catabolic process , pigmentation, GTPase activity.The decreased GO items included protein metabolic process, protein binding.Gene network analysis indicated that a total of 40 genes including HSPA1A,CSNK1A1,EIF4A2 ,MYCBP2,PRKRA and NGFR may be related the pathogenesis of PCA-DM.Totally 13 genes including TFF1, MSMB, NOX1 were of potential diagnostic value to PCA-DM. Conclusions Pathogenic gene expression profiles of PCA-DM is established , potential causative genes and genes of potential diagnostic value are discovered .
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