基于转录组数据的网络分析挖掘鼻咽癌与口腔鳞癌的共享功能模块

摘要

鼻咽癌和口腔鳞癌是两种在临床上高度相关的疾病,从分子层面系统性研究这两种疾病的相互关系却鲜见报道.本研究通过大规模的转录组数据分析识别鼻咽癌和口腔鳞癌的共享功能模块及其核心基因(一因多效模块和基因),以期阐明这两种疾病共享的分子机制.从GEO数据库获取这两种癌症的两套转录组数据,应用倍数法和经验贝叶斯方法筛选出鼻咽癌差异表达基因1279个,口腔鳞癌差异表达基因1293个,其中两者共享基因278个.以共享基因为种子,通过蛋白质-蛋白质互作知识引导构建基因网络,其中最大子网包含1290个基因和1766互作对.应用Newman算法提取了15个共享功能模块.对这些模块进行拓扑学分析,挖掘出58个核心基因,包括已知的与鼻咽癌或口腔鳞癌相关的基因(如PCNA、CDK1、STAT1、CCL5和MMP1等)和鲜有报道的基因(如MELK、NME1、RACGAP1、INHBA和NID1等).通路富集分析发现鼻咽癌和口腔鳞癌的共享功能模块参与多个生物学通路,包括p53信号通路、ECM受体相互作用、黏着斑、细胞周期等.本研究表明鼻咽癌和口腔鳞癌具有相似的致癌机制,所挖掘的共享模块可能是这两种疾病演化的核心分子相互作用机制.%Although nasopharyngeal carcinoma (NPC) and oral squamous cell carcinoma (OSCC) are highly correlated clinical diseases, the underling molecular mechanisms to link the two diseases remain largely unknown. The aim of thisstudy is to identify the shared functional modules for NPC and OSCC by using large-scale transcriptomic data. Gene expression profile datasets of NPC and OSCC were obtained from the GEO database. A total of 1279 differentially expressed genes (DEGs) of NPC and 1293 DEGs of OSCC were identified by fold change and empirical Bayes method, and278 DEGs were common to these two diseases. These overlapped genes were translated into a primary network consisting of 1290 nodes (genes) and 1766 edges. The primary network was then decomposed into 15 compacted modules (subnets) with high modularity by Newman's algorithm. Topological analysis of these modules identified a total of 58 hub genes, most of which (e.g., PCNA, CDK1, STAT1, CCL5, and MMP1) have been proved to be associated with NPC and/or OSCC, while the rest (e.g., MELK, NME1, RACGAP1, INHBA, and NID1) might be novel risk genes for the two diseases. Further bioinformatics analysis of KEGG databases revealed that these modules are involved in multiple pathogenic biological pathways for either NPC or OSCC (e.g., p53 signaling pathway, ECM-receptor interaction, focal adhesion, and cell cycle).This study demonstrates that NPC and OSCC have similar molecular bases, and the identified pleiotropic modules may shape the complicated molecular interplays underlying the two clinically correlated diseases.