基因表达谱结合共表达网络分析发现胰腺导管腺癌预后分子机制

Identify mechanism of the prognosis of pancreatic ductal adenocarcinoma using gene expression profiles and co-expression network analysis

目的 结合胰腺导管癌（PDAC）表达谱数据、临床资料以及分析基因共表达网络,定义PDAC预后相关的基因,并挖掘其预后相关的分子调控机制.方法 通过Cox生存分析寻找表达水平与生存时间相关的基因（P＜ 0.000 1）.计算得到的相关基因之间的共表达关系,建立共表达网络,进一步寻找网络中核心模块.结果 Cox生存分析得到273个与患者的生存数据相关的候选基因,构建共表达网络[Pearson相关系数（r）＞ 0.9,P＜0.05]寻找核心模块（MCODE算法,得分＞2）,最后发现1个包含6个基因（PTMAP7、FTSJ3、TLK2、GOLGA3、PTTG1IP、ZBTB37） 14个共表达关系的核心模块.其中GOLGA3基因已经被发现与PDAC的转移侵染有关;其他基因也都被研究发现属于已知癌基因.结论 构建的PDAC相关基因的共表达模块与PDAC预后相关,且可能作为PDAC预后相关标志分子.

Objective To detect genes expression related to the prognosis of pancreatic ductal adenocarcinoma （PDAC） and explore the potential molecular mechanism applying PDAC gene expression data,co-expression network and clinical data.Methods Univariate Cox proportional hazards model was used to find genes which were significantly correlated with patient survival data （P ＜ 0.000 1）.Then calculated the correlation coefficient of these genes to establish co-expression network and found key modules of the network.Results 273 candidate genes were found related to survival data.With these genes,genes co-expression network （Pearson correlation r ＞ 0.9,P ＜ 0.05） and key modules were constructed,and then,a key module including 6 genes （PTMAP7,FTSJ3,TLK2,GOLGA3,PTTG1IP,ZBTB37） and 14 co-expression relationships between them were found.Among these genes,GOLGA3 had been known to associate with invasion and metastasis of PDAC,and the other 5 genes were all known as cancer genes.Conclusion These findings may suggest that these 6 survival genes in the key module of co-expression network are highly associated with the prognosis of PDAC,and may be biomarkers for PDAC prognosis.