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对mRNA稳定性调节的综合分析揭示了乳腺癌中转移抑制计划

Heather Karner^1,2,3, Tabea C Mittmann^1,2,3,4, Vicky W Chen^1,2,3,5

¹Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA.

Science advances

|March 11, 2026

概括

使者RNA (mRNA) 的稳定性显著影响乳腺癌中的基因表达变异性. 一个新的深度学习模型,GreyHound,确定了像RBMS3这样的RNA结合蛋白 (RBPs),这些蛋白调节mRNA稳定性,影响转移.

科学领域:

分子生物学分子生物学
基因组学就是基因组学.
计算生物学计算生物学

背景情况:

癌症基因表达异质性主要归因于遗传和表观遗传因素.
转录后调节的作用,特别是mRNA稳定性,在推动这种异质性方面尚未完全理解.

研究的目的:

在乳腺癌模型中系统测量信使RNA (mRNA) 动态.
研究mRNA稳定性对基因表达变异性的贡献.
开发一种用于破译RNA动态和监管网络的计算框架.

主要方法:

在各种乳腺癌模型中对mRNA动态的系统测量.
开发GreyHound,一个可解释的多模式深度学习框架,集成RNA序列特征和RNA结合蛋白 (RBP) 表达.
在体内表观性研究以证实调节机制.

主要成果:

确定mRNA稳定性是乳腺癌中基因表达变异的重要驱动因素.
灰猎犬发现了一个广泛的RBP网络,调节mRNA稳定性,包括一个关键轴,涉及RBMS3和TXNIP.
减少RBMS3导致了转录破坏稳定,不良的临床结果,并增加了转移潜力,这与TXNIP mRNA调节有关.

结论:

通过mRNA稳定性的转录后调节是乳腺癌的一个关键机制.
在RBMS3-TXNIP调节轴抑制转移.
可解释的深度学习模型可以揭示与疾病相关的RNA调节程序.

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