Integrative analysis of the inverse expression patterns in pancreas development and cancer progression

胰腺发育和癌症进展中反向表达模式的整合分析

阅读:1

Abstract

BACKGROUND: As the malignant tumor, pancreatic cancer with a meager 5-years survival rate has been widely concerning. However, the molecular mechanisms that result in malignant transformation of pancreatic cells remain elusive. AIM: To investigate the gene expression profiles in normal or malignant transformed pancreas development. METHODS: MaSigPro and ANOVA were performed on two pancreas development datasets downloaded from the Gene Expression Omnibus database. Six pancreatic cancer datasets collected from TCGA database were used to establish differentially expressed genes related to pancreas development and pancreatic cancer. Moreover, gene clusters with highly similar interpretation patterns between pancreas development and pancreatic cancer progression were established by self-organizing map and singular value decomposition. Additionally, the hypergeometric test was performed to compare the corresponding interpretation patterns. Abnormal regions of metabolic pathway were analyzed using the Sub-pathway-GM method. RESULTS: This study established the continuously upregulated and downregulated genes at different stages in pancreas development and progression of pancreatic cancer. Through analysis of the differentially expressed genes, we established the inverse and consistent direction development-cancer pattern associations. Based on the application of the Subpathway-GM analysis, we established 17 significant metabolic sub-pathways that were closely associated with pancreatic cancer. Of note, the most significant metabolites sub-pathway was related to glycerophospholipid metabolism. CONCLUSION: The inverse and consistent direction development-cancer pattern associations were established. There was a significant correlation in the inverse patterns, but not consistent direction patterns.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。