基于共表达网络挖掘不同前列腺特异抗原水平下的前列腺癌发展相关基因

Mining related genes for the development of prostate cancer at different prostate-specific antigen levels based on co-expression networks

目的采用权重基因共表达网络分析方法(WGCNA)挖掘不同前列腺特异抗原(PSA)水平下的前列腺癌发展枢纽基因。方法数据来自NCBI的GEO数据库中下载不同PSA水平下的前列腺癌全基因组表达数据集,经过数据预处理后,用WGCNA构建基因共表达网络,识别不同PSA水平下的前列腺癌发展模块与枢纽基因。结果筛选出的差异基因聚集成一个模块,并且找到10个枢纽基因。结论结合文献发现,SNAI2、TRIM29、LAMB3、CYP3A5和SLC14A1这5个基因很可能影响不同PSA水平下前列腺癌的发展。

Objective Aim Genes of pivotal genes for the development of prostate cancer at different prostate specific antigen（PSA）levels were scored using the weighted co-expression network analysis method（WGCNA）.Methods Data were downloaded from the NCBI＇s GEO database to download genome-wide expression datasets of prostate cancer at different PSA levels.After data preprocessing,gene co-expression networks were constructed with WGCNA to identify modules and hinge genes for the development of prostate cancer at different PSA levels. Results The results showed that the differentially selected genes clustered into one module,and found 10 hub genes. Conclusion Combined with the literature,it is found that the five genes of SNAI2,TRIM29,LAMB3,CYP3 A5 and SLC14 A1 are likely to affect the development of prostate cancer at different PSA levels.