Wang Cong-Jun, Xu Rong-Hua, Yuan Qiong-Ying, Wang Yong-Kun, Shen Dong-Wei, Wang Xu-Jing, Gao Wei, Zhang Hui, Jiang Hua
Biliary and Pancreatic Department, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
J Comput Biol. 2013 Jun;20(6):444-52. doi: 10.1089/cmb.2012.0281. Epub 2013 Apr 24.
Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97-98% due to widespread metastatic disease. A better understanding of the molecular mechanism of pancreatic cancer is beneficial for the development of novel approaches for early detection and monitoring of pancreatic cancer. We aim to comprehensively identify the gene expression profile in pancreatic cancer and explore the molecular pathway of pancreatic cancer disorder. Using GSE15471 datasets downloaded from Gene Expression Omnibus data, we first screened the differentially expressed genes in pancreatic cancer using packages in R language. The key pathways of differentially expressed genes were investigated with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and synergetic network construction based on weighted Jaccard index. A total of 13,211 differentially expressed genes were identified, and they were enriched in several pathways, such as mitogen-activated protein kinase (MAPK) signaling pathway, transforming growth factor (TGF)-beta signaling pathway, Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling pathway, and calcium signaling pathway, as well as cell cycle, focal adhesion, complement and coagulation cascades, and leukocyte transendothelial migration. Synergetic pathway network analysis revealed that cytokine-cytokine receptor interaction pathway, calcium signaling pathway, and focal adhesion pathway were three important pathways in the development of pancreatic cancer. The method introduced here is helpful to screen the key pathways for controlling pancreatic cancer progression and provide potential therapeutic targets in the treatment of pancreatic cancer.
胰腺癌是一种侵袭性恶性肿瘤，由于广泛的转移性疾病，其五年死亡率为97-98%。更好地了解胰腺癌的分子机制有助于开发早期检测和监测胰腺癌的新方法。我们旨在全面鉴定胰腺癌中的基因表达谱，并探索胰腺癌紊乱的分子途径。使用从基因表达综合数据库下载的GSE15471数据集，我们首先使用R语言中的软件包筛选胰腺癌中差异表达的基因。通过京都基因与基因组百科全书（KEGG）途径富集分析和基于加权杰卡德指数的协同网络构建，研究差异表达基因的关键途径。共鉴定出13211个差异表达基因，它们富集于多个途径，如丝裂原活化蛋白激酶（MAPK）信号通路、转化生长因子（TGF）-β信号通路、Janus激酶-信号转导子和转录激活子（JAK-STAT）信号通路、钙信号通路，以及细胞周期、粘着斑、补体和凝血级联反应、白细胞跨内皮迁移。协同途径网络分析表明，细胞因子-细胞因子受体相互作用途径、钙信号通路和粘着斑途径是胰腺癌发生发展中的三个重要途径。这里介绍的方法有助于筛选控制胰腺癌进展的关键途径，并为胰腺癌治疗提供潜在的治疗靶点。
