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利用提升贝塔回归算法鉴定 CD44 剪接过程中的重要 RNA 结合蛋白。

Identification of Significant RNA-Binding Proteins in the Process of CD44 Splicing Using the Boosted Beta Regression Algorithm.

机构信息

Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow, Russia.

Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.

出版信息

Dokl Biochem Biophys. 2023 Jun;510(1):99-103. doi: 10.1134/S1607672923700199. Epub 2023 Aug 15.

DOI:10.1134/S1607672923700199
PMID:37582871
Abstract

The expression of RNA-binding proteins and their interaction with the spliced pre-mRNA are the key factors in determining the final isoform profile. Transmembrane protein CD44 is involved in differentiation, invasion, motility, growth and survival of tumor cells, and is also a commonly accepted marker of cancer stem cells and epithelial-mesenchymal transition. However, the functions of the isoforms of this protein differ significantly. In this paper, we developed a method based on the boosted beta regression algorithm for identification of the significant RNA-binding proteins in the splicing process by modeling the isoform ratio. The application of this method to the analysis of CD44 splicing in colorectal cancer cells revealed 20 significant RNA-binding proteins. Many of them were previously shown as EMT regulators, but for the first time presented as potential CD44 splicing factors.

摘要

RNA 结合蛋白的表达及其与剪接前体 mRNA 的相互作用是决定最终异构体谱的关键因素。跨膜蛋白 CD44 参与肿瘤细胞的分化、浸润、迁移、生长和存活,也是公认的癌症干细胞和上皮-间充质转化的标志物。然而,该蛋白的异构体功能差异很大。在本文中,我们开发了一种基于提升贝叶斯回归算法的方法,通过建立异构体比例模型来识别剪接过程中的显著 RNA 结合蛋白。将该方法应用于结直肠癌细胞 CD44 剪接的分析中,揭示了 20 个显著的 RNA 结合蛋白。其中许多蛋白先前被证明是 EMT 调节剂,但首次被认为是潜在的 CD44 剪接因子。

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引用本文的文献

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RNA-binding proteins regulating the CD44 alternative splicing.调控CD44可变剪接的RNA结合蛋白
Front Mol Biosci. 2023 Dec 1;10:1326148. doi: 10.3389/fmolb.2023.1326148. eCollection 2023.

本文引用的文献

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CD44 as a tumor biomarker and therapeutic target.CD44作为一种肿瘤生物标志物和治疗靶点。
Exp Hematol Oncol. 2020 Dec 10;9(1):36. doi: 10.1186/s40164-020-00192-0.
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QKI, a miR-200 target gene, suppresses epithelial-to-mesenchymal transition and tumor growth.QKI,miR-200 的靶基因,抑制上皮间质转化和肿瘤生长。
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Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing.通过高通量测序对人类转录组中可变剪接复杂性进行深度研究。
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