草履虫致癌 Ras 变异活动的功能性区别

IF 4 3区 医学 Q2 CELL BIOLOGY
Disease Models & Mechanisms Pub Date : 2024-08-01 Epub Date: 2024-08-14 DOI:10.1242/dmm.050577
Haimeng Lyu, Helen M Chamberlin
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引用次数: 0

摘要

Ras 基因是重要的致癌基因,在癌症中经常发生突变。人类致癌变体在不同癌症类型中的代表性、对细胞靶点的影响以及对药物治疗的敏感性等方面表现出不同的功能。然而,人们对这些不同的变体如何影响和应对它们所处的细胞网络却知之甚少。为了确定 Ras 基因型与体内细胞相互作用网络之间复杂相互作用的新参与者,我们利用线虫 C. elegans 的简单外阴发育实验开发并测试了一个实验框架。利用这一系统,我们评估了 G12、G13 和 Q61 处的一组 Ras 致癌替代变化。我们发现,这些变体根据表型差异、对基因剂量和下游激酶 MEK 抑制的敏感性,以及它们对以非自主方式影响 Ras 活性的基因调节剂的反应分为不同的组。总之,我们的研究结果表明致癌秀丽隐杆线虫 Ras 变体在如何与外阴发育网络连接方面表现出明显的差异,并表明细胞外调节剂在体内产生了变体限制效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Functional distinction in oncogenic Ras variant activity in Caenorhabditis elegans.

Ras genes are important oncogenes that are frequently mutated in cancer. Human oncogenic variants exhibit functional distinctions in terms of their representation in different cancer types, impact on cellular targets and sensitivity to pharmacological treatments. However, how these distinct variants influence and respond to the cellular networks in which they are embedded is poorly understood. To identify novel participants in the complex interplay between Ras genotype and cell interaction networks in vivo, we have developed and tested an experimental framework using a simple vulva-development assay in the nematode C. elegans. Using this system, we evaluated a set of Ras oncogenic substitution changes at G12, G13 and Q61. We found that these variants fall into distinct groups based on phenotypic differences, sensitivity to gene dosage and inhibition of the downstream kinase MEK and their response to genetic modulators that influence Ras activity in a non-autonomous manner. Together, our results demonstrated that oncogenic C. elegans Ras variants exhibit clear distinctions in how they interface with the vulva-development network and showed that extracellular modulators yield variant-restricted effects in vivo.

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来源期刊
Disease Models & Mechanisms
Disease Models & Mechanisms 医学-病理学
CiteScore
6.60
自引率
7.00%
发文量
203
审稿时长
6-12 weeks
期刊介绍: Disease Models & Mechanisms (DMM) is an online Open Access journal focusing on the use of model systems to better understand, diagnose and treat human disease.
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