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Zhang J, Xu X, Deng H, Liu L, Xiang Y, Feng J. Overcoming cancer drug-resistance calls for novel strategies targeting abnormal alternative splicing. Pharmacol Ther 2024; 261:108697. [PMID: 39025436 DOI: 10.1016/j.pharmthera.2024.108697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 05/12/2024] [Accepted: 07/15/2024] [Indexed: 07/20/2024]
Abstract
Abnormal gene alternative splicing (AS) events are strongly associated with cancer progression. Here, we summarize AS events that contribute to the development of drug resistance and classify them into three categories: alternative cis-splicing (ACS), alternative trans-splicing (ATS), and alternative back-splicing (ABS). The regulatory mechanisms underlying AS processes through cis-acting regulatory elements and trans-acting factors are comprehensively described, and the distinct functions of spliced variants, including linear spliced variants derived from ACS, chimeric spliced variants arising from ATS, and circRNAs generated through ABS, are discussed. The identification of dysregulated spliced variants, which contribute to drug resistance and hinder effective cancer treatment, suggests that abnormal AS processes may together serve as a precise regulatory mechanism enabling drug-resistant cancer cell survival or, alternatively, represent an evolutionary pathway for cancer cells to adapt to changes in the external environment. Moreover, this review summarizes recent advancements in treatment approaches targeting AS-associated drug resistance, focusing on cis-acting regulatory elements, trans-acting factors, and specific spliced variants. Collectively, gaining an in-depth understanding of the mechanisms underlying aberrant alternative splicing events and developing strategies to target this process hold great promise for overcoming cancer drug resistance.
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Affiliation(s)
- Ji Zhang
- Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China; Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China
| | - Xinyu Xu
- Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China; Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China
| | - Hongwei Deng
- Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China; Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China
| | - Li Liu
- Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China; Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China
| | - Yuancai Xiang
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southwest Medical University, Luzhou city, Sichuan 646000, China.
| | - Jianguo Feng
- Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China; Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan Province 646000, China; Nucleic Acid Medicine of Luzhou Key Laboratory, Southwest Medical University, Luzhou, Sichuan Province 646000, China.
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Ma XK, Xue W, Chen LL, Yang L. CIRCexplorer pipelines for circRNA annotation and quantification from non-polyadenylated RNA-seq datasets. Methods 2021; 196:3-10. [PMID: 33588028 DOI: 10.1016/j.ymeth.2021.02.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/02/2021] [Accepted: 02/05/2021] [Indexed: 01/01/2023] Open
Abstract
Covalently closed circular RNAs (circRNAs) produced by back-splicing of exon(s) are co-expressed with their cognate linear RNAs from the same gene loci. Most circRNAs are fully overlapped with their cognate linear RNAs in sequences except the back-spliced junction (BSJ) site, thus challenging the computational detection, experimental validation and hence functional evaluation of circRNAs. Nevertheless, specific bioinformatic pipelines were developed to identify fragments mapped to circRNA-featured BSJ sites, and circRNAs were pervasively identified from non-polyadenylated RNA-seq datasets in different cell lines/tissues and across species. Precise identification and quantification of circRNAs provide a basis to further understand their functions. Here, we describe detailed computational steps to annotate and quantify circRNAs using a series of CIRCexplorer pipelines.
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Affiliation(s)
- Xu-Kai Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Wei Xue
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Ling-Ling Chen
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China; School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Li Yang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China.
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