Department of Hepatobiliary and Pancreatic Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, Jilin Province, China.
Department of Hematology, Jilin Province Blood Center, Changchun 130000, Jilin Province, China.
World J Gastroenterol. 2019 Aug 28;25(32):4727-4738. doi: 10.3748/wjg.v25.i32.4727.
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.
To investigate the gene expression profiles in normal or malignant transformed pancreas development.
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.
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.
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.
作为一种恶性肿瘤，胰腺癌的 5 年生存率很低，因此受到广泛关注。然而，导致胰腺细胞恶性转化的分子机制仍不清楚。
研究正常或恶性转化胰腺发育过程中的基因表达谱。
使用 MaSigPro 和 ANOVA 对从基因表达综合数据库下载的两个胰腺发育数据集进行分析。从 TCGA 数据库中收集了六个胰腺癌数据集，用于建立与胰腺发育和胰腺癌相关的差异表达基因。此外，通过自组织映射和奇异值分解建立了具有相似解释模式的基因簇，用于胰腺发育和胰腺癌进展之间的比较。通过超几何检验比较相应的解释模式。使用 Sub-pathway-GM 方法分析代谢途径的异常区域。
本研究建立了在胰腺发育和胰腺癌进展的不同阶段连续上调和下调的基因。通过对差异表达基因的分析，我们建立了癌症发展的反转和一致方向的关联模式。基于 Subpathway-GM 分析的应用，我们建立了 17 个与胰腺癌密切相关的显著代谢亚途径。值得注意的是，最显著的代谢物亚途径与甘油磷脂代谢有关。
建立了反转和一致方向的发展-癌症关联模式。虽然存在反转模式的显著相关性，但不存在一致方向模式的相关性。
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