Integrative system genetic analysis reveals mRNA-lncRNA network associated with mouse spontaneous lung cancer susceptibility

整合系统遗传分析揭示了与小鼠自发性肺癌易感性相关的mRNA-lncRNA网络

阅读:1

Abstract

INTRODUCTION: Lung cancer continues to be a significant health burden in the United States. Lung cancer in never smokers is considered as a different disease and underlying mechanism of spontaneous lung cancer susceptibility is still poorly known. Meanwhile, the roles of long non-coding RNAs (lncRNAs), which have multiple functions in biological processes, have seldom been studied in spontaneous lung cancer susceptibility. METHODS: In this study, microarray analyses of normal lung tissues were performed in 23 different mouse strains. LncRNA profile was analyzed by re-annotating exon array for lncRNAs detection. LncRNA/mRNA co-expression networks were constructed and the association between significant lncRNA module and significant mRNA modules was calculated. Finally, Genome-wide association (GWA) results were used to further highlight the key mRNAs and lncRNAs associated with spontaneous lung cancer susceptibility. RESULTS: Four mRNA modules were significantly associated with spontaneous lung cancer susceptibility. Genes in these modules were enriched in "blood coagulation" and "immune system process". Only one lncRNA module was significantly associated with spontaneous lung cancer susceptibility. Many lncRNAs in this module were co-expressed with mRNAs in the second most significant mRNA module. This co-expression network contained 113 interactions between 30 lncRNAs and 40 mRNAs. After GWA filtration, two mRNAs (Myo7a and Zfp874a) and two lncRNAs (n290048 and n271850) were highlighted as the candidates responsible for genetic susceptibility to lung cancer. CONCLUSIONS: We firstly used integrative system genetic analysis to report the mRNA-lncRNA network associated with spontaneous lung cancer susceptibility and identified potential targets for lung cancer prevention.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。