Zhang Tiejun, Wang Xiaojuan, Yue Zhenyu
GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong 511436, China.
Institute of Health Sciences, School of Computer Science and Technology, Anhui University, Hefei, Anhui 230601, China.
Oncotarget. 2017 Aug 24;8(41):71105-71116. doi: 10.18632/oncotarget.20537. eCollection 2017 Sep 19.
Pancreatic cancer (PC) is one of the most common causes of cancer mortality worldwide. As the genetic mechanism of this complex disease is not uncovered clearly, identification of related genes of PC is of great significance that could provide new insights into gene function as well as potential therapy targets. In this study, we performed an integrated network method to discover PC candidate genes based on known PC related genes. Utilizing the subnetwork extraction algorithm with gene co-expression profiles and protein-protein interaction data, we obtained the integrated network comprising of the known PC related genes (denoted as seed genes) and the putative genes (denoted as linker genes). We then prioritized the linker genes based on their network information and inferred six key genes (, , , , and ) as candidate genes of PC. Further analysis indicated that all of these genes have been reported as pancreatic cancer associated genes. Finally, we developed an expression signature using these six key genes which significantly stratified PC patients according to overall survival (Logrank = 0.003) and was validated on an independent clinical cohort (Logrank = 0.03). Overall, the identified six genes might offer helpful prognostic stratification information and be suitable to transfer to clinical use in PC patients.
胰腺癌（PC）是全球癌症死亡的最常见原因之一。由于这种复杂疾病的遗传机制尚未完全阐明，鉴定胰腺癌相关基因具有重要意义，可为基因功能及潜在治疗靶点提供新的见解。在本研究中，我们基于已知的胰腺癌相关基因，采用整合网络方法来发现胰腺癌候选基因。利用基因共表达谱和蛋白质 - 蛋白质相互作用数据的子网提取算法，我们获得了由已知的胰腺癌相关基因（称为种子基因）和推定基因（称为连接基因）组成的整合网络。然后，我们根据连接基因的网络信息对其进行优先级排序，并推断出六个关键基因（、、、、和）作为胰腺癌的候选基因。进一步分析表明，所有这些基因均已被报道为胰腺癌相关基因。最后，我们利用这六个关键基因开发了一种表达特征，该特征根据总生存期对胰腺癌患者进行了显著分层（对数秩检验=0.003），并在一个独立的临床队列中得到验证（对数秩检验=0.03）。总体而言，鉴定出的这六个基因可能提供有用的预后分层信息，适合应用于胰腺癌患者的临床治疗。
