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Analysis of the autophagy gene expression profile of pancreatic cancer based on autophagy-related protein microtubule-associated protein 1A/1B-light chain 3

机译:基于自噬相关蛋白质微管相关蛋白1A / 1B-轻链3的胰腺癌自噬基因表达谱分析

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Pancreatic cancer is a highly invasive malignant tumor. Expression levels of the autophagy-related protein microtubule-associated protein 1A/1B-light chain 3 (LC3) and perineural invasion (PNI) are closely related to its occurrence and development. Our previous results showed that the high expression of LC3 was positively correlated with PNI in the patients with pancreatic cancer. In this study, we further searched for differential genes involved in autophagy of pancreatic cancer by gene expression profiling and analyzed their biological functions in pancreatic cancer, which provides a theoretical basis for elucidating the pathophysiological mechanism of autophagy in pancreatic cancer and PNI. To identify differentially expressed genes involved in pancreatic cancer autophagy and explore the pathogenesis at the molecular level. Two sets of gene expression profiles of pancreatic cancer/normal tissue (GSE16515 and GSE15471) were collected from the Gene Expression Omnibus. Significance analysis of microarrays algorithm was used to screen differentially expressed genes related to pancreatic cancer. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze the functional enrichment of the differentially expressed genes. Protein interaction data containing only differentially expressed genes was downloaded from String database and screened. Module mining was carried out by Cytoscape software and ClusterOne plug-in. The interaction relationship between the modules was analyzed and the pivot nodes between the functional modules were determined according to the information of the functional modules and the data of reliable protein interaction network. Based on the above two data sets of pancreatic tissue total gene expression, 6098 and 12928 differentially expressed genes were obtained by analysis of genes with higher phenotypic correlation. After extracting the intersection of the two differential gene sets, 4870 genes were determined. GO analysis showed that 14 significant functional items including negative regulation of protein ubiquitination were closely related to autophagy. A total of 986 differentially expressed genes were enriched in these functional items. After eliminating the autophagy related genes of human cancer cells which had been defined, 347 differentially expressed genes were obtained. KEGG pathway analysis showed that the pathways hsa04144 and hsa04020 were related to autophagy. In addition, 65 clustering modules were screened after the protein interaction network was constructed based on String database, and module 32 contains the LC3 gene, which interacts with multiple autophagy-related genes. Moreover, ubiquitin C acts as a pivot node in functional modules to connect multiple modules related to pancreatic cancer and autophagy. Three hundred and forty-seven genes associated with autophagy in human pancreatic cancer were concentrated, and a key gene ubiquitin C which is closely related to the occurrence of PNI was determined, suggesting that LC3 may influence the PNI and prognosis of pancreatic cancer through ubiquitin C.
机译:胰腺癌是一种高度侵入性的恶性肿瘤。自噬相关蛋白质微管相关蛋白1A / 1B-轻链3(LC3)和Per内侵袭(PNI)的表达水平与其发生和发育密切相关。我们以前的结果表明,LC3的高表达与胰腺癌患者中的PNI呈正相关。在这项研究中,我们进一步搜索了通过基因表达分析中涉及胰腺癌自噬的差异基因,并分析了它们在胰腺癌中的生物学功能,为阐明了胰腺癌和PNI中自噬的病理生理机制提供了理论依据。鉴定含有胰腺癌癌症的差异表达基因并探讨分子水平的发病机制。从基因表达Omnibus收集两组胰腺癌/正常组织(GSE16515和GSE15471)的基因表达谱。微阵列算法的意义分析用于筛选与胰腺癌相关的差异表达基因。基因本体(GO)分析(GO)分析和基因或基因组(KEGG)途径分析用于分析差异表达基因的功能性富集。从String数据库下载仅包含差异表达基因的蛋白质交互数据并筛选。模块挖掘由Cytoscape软件和群集插件进行。分析了模块之间的交互关系,并且根据功能模块的信息和可靠的蛋白质交互网络的数据确定功能模块之间的枢轴节点。基于上述两种数据组的胰腺组织总基因表达,通过分析具有较高表型相关性的基因来获得6098和12928个差异表达基因。在提取两个差分基因集的交叉后,确定4870个基因。 GO分析表明,包括蛋白质泛素的负调节的14项显着的功能项目与自噬密切相关。在这些功能项目中富集了总共986个差异表达基因。在消除已经定义的人癌细胞的自噬相关基因后,获得347个差异表达基因。 Kegg途径分析表明,HSA04144和HSA04020与自噬有关。另外,在基于串数据库构建蛋白质相互作用网络之后筛选了65种聚类模块,并且模块32包含LC3基因,其与多种自噬相关基因相互作用。此外,泛素C作为功能模块中的枢轴节点,以连接与胰腺癌和自噬相关的多个模块。浓缩了与人类胰腺癌中的自噬相关的三百四十七种基因,并确定了与PNI发生的关键相关的关键基因泛素C,表明LC3可以通过泛素C对胰腺癌的PNI和预后影响。

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