Ma Xuhui, Li Lu, Tian Tongde, Liu Huaimin, Li Qiujian, Gao Qilong
Department of Oncology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, China.
Saudi J Biol Sci. 2017 Mar;24(3):649-657. doi: 10.1016/j.sjbs.2017.01.038. Epub 2017 Jan 27.
Our purpose is to screen out serum tumor markers closely correlated to the nature of solitary pulmonary nodule (SPN) and to draw a regulatory network containing genes correlated to lung cancer. Two hundred and sixty cases of SPN patients confirmed through pathological diagnosis were collected as subjects, factors closely correlated to the nature of SPN were screened out from eight tumor markers through Fisher discriminant method, and functional annotation and pathway analysis were conducted on erbB4 as well as its tumor marker genes by GO and KEGG databases. Four key tumor markers: CYFRA21-1, CA125, SCC-Ag and CA153 were successfully screened out and the first three proteins' corresponding gene were KRT19, MUC16 and SERPINB3 while that of CA153 was not found. GO analysis on erbB4, KRT19, MUC16 and SERPINB3 showed that they covered three domains, cell components, molecular function and biological process; meanwhile, combined with KEGG database and based on signal pathway of erbB4, a regulatory network of lung cancer cells escaping from apoptosis was successfully made. This study indicates that serum tumor marker genes play an important role in the occurrence and development of lung cancer, besides, this study primarily discussed the molecular mechanism of these tumor markers in predicting tumor, which provides a basis for in-depth information about lung cancer.
我们的目的是筛选出与孤立性肺结节(SPN)性质密切相关的血清肿瘤标志物,并绘制包含与肺癌相关基因的调控网络。收集经病理诊断确诊的260例SPN患者作为研究对象,通过Fisher判别法从8种肿瘤标志物中筛选出与SPN性质密切相关的因素,并利用GO和KEGG数据库对erbB4及其肿瘤标志物基因进行功能注释和通路分析。成功筛选出4种关键肿瘤标志物:CYFRA21-1、CA125、SCC-Ag和CA153,前三种蛋白对应的基因分别为KRT19、MUC16和SERPINB3,而CA153对应的基因未找到。对erbB4、KRT19、MUC16和SERPINB3进行GO分析表明,它们涵盖细胞成分、分子功能和生物学过程三个结构域;同时,结合KEGG数据库,基于erbB4信号通路成功构建了肺癌细胞逃避凋亡的调控网络。本研究表明血清肿瘤标志物基因在肺癌的发生发展中起重要作用,此外,本研究初步探讨了这些肿瘤标志物预测肿瘤的分子机制,为深入了解肺癌提供了依据。