多组学数据分析揭示了肺腺癌中选择性剪接事件的生物学意义。

IF 0.9 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Fuyan Hu, Bifeng Chen, Qing Wang, Zhiyuan Yang, Man Chu
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引用次数: 0

摘要

癌症的特点是选择性剪接(AS)失调。然而,AS在肺腺癌(LUAD)中的综合调控机制尚不清楚。在这里,我们基于对LUAD的多组学数据的综合分析,展示了LUAD中的AS景观。我们在6309个基因中鉴定出13995个AS事件为主要覆盖蛋白质编码基因的差异表达选择性剪接事件(DEASEs)。这些DEASE与“癌症特征”密切相关,如凋亡、DNA修复、细胞周期、细胞增殖、血管生成、免疫反应、前体代谢产物和能量的产生、p53信号通路和PI3K-AKT信号通路。我们进一步建立了一个连接剪接因子(SF)和DEASE的调控网络。此外,研究了可影响DEASE的RNA结合蛋白(RBP)突变,以寻找一些潜在的癌症驱动因素。进一步的关联分析表明,DNA甲基化水平与DEASE高度相关。总之,我们的研究结果可以为理解AS的机制带来新的见解,并为LUAD的个性化医学提供新的生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-omics data analysis reveals the biological implications of alternative splicing events in lung adenocarcinoma.

Cancer is characterized by the dysregulation of alternative splicing (AS). However, the comprehensive regulatory mechanisms of AS in lung adenocarcinoma (LUAD) are poorly understood. Here, we displayed the AS landscape in LUAD based on the integrated analyses of LUAD's multi-omics data. We identified 13,995 AS events in 6309 genes as differentially expressed alternative splicing events (DEASEs) mainly covering protein-coding genes. These DEASEs were strongly linked to "cancer hallmarks", such as apoptosis, DNA repair, cell cycle, cell proliferation, angiogenesis, immune response, generation of precursor metabolites and energy, p53 signaling pathway and PI3K-AKT signaling pathway. We further built a regulatory network connecting splicing factors (SFs) and DEASEs. In addition, RNA-binding protein (RBP) mutations that can affect DEASEs were investigated to find some potential cancer drivers. Further association analysis demonstrated that DNA methylation levels were highly correlated with DEASEs. In summary, our results can bring new insight into understanding the mechanism of AS and provide novel biomarkers for personalized medicine of LUAD.

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来源期刊
Journal of Bioinformatics and Computational Biology
Journal of Bioinformatics and Computational Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.10
自引率
0.00%
发文量
57
期刊介绍: The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information. The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.
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