Research ArticleNo Access

Multi-omics data analysis reveals the biological implications of alternative splicing events in lung adenocarcinoma

Department of Statistics, School of Science, Wuhan University of Technology, 122 Luoshi Road, Wuhan, Hubei 430070, P. R. China

E-mail Address: fuyanhu@whut.edu.cn

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Bifeng Chen

Department of Biological Science and Technology, School of Chemistry Chemical Engineering and Life Sciences, Wuhan University of Technology Wuhan, Hubei, P. R. China

E-mail Address: cbifeng@whut.edu.cn

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Qing Wang

Department of Traditional Chinese Medicine of Wuhan Puren Hospital, Affiliated Hospital of Wuhan University of Science and Technology, 1# Benxi Street, Qingshan District, Wuhan, Hubei, P. R. China

E-mail Address: 1172665170@qq.com

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Zhiyuan Yang

School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou, Zhejiang, P. R. China

E-mail Address: yangzhiyuan@hdu.edu.cn

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, and

Man Chu

The Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi 712046, P. R. China

E-mail Address: 2071013@sntcm.edu.cn

Corresponding author.

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https://doi.org/10.1142/S0219720023500208Cited by:0 (Source: Crossref)

Abstract

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.

Keywords:

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