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New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling

机译:对RAS生物学的新见解重新研究RAS信令的数学建模兴趣

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摘要

RAS is the most frequently mutated gene across human cancers, but developing inhibitors of mutant RAS has proven to be challenging. Given the difficulties of targeting RAS directly, drugs that impact the other components of pathways where mutant RAS operates may potentially be effective. However, the system-level features, including different localizations of RAS isoforms, competition between downstream effectors, and interlocking feedback and feed-forward loops, must be understood to fully grasp the opportunities and limitations of inhibiting specific targets. Mathematical modeling can help us discern the system-level impacts of these features in normal and cancer cells. New technologies enable the acquisition of experimental data that will facilitate development of realistic models of oncogenic RAS behavior. In light of the wealth of empirical data accumulated over decades of study and the advancement of experimental methods for gathering new data, modelers now have the opportunity to advance progress toward realization of targeted treatment for mutant RAS-driven cancers.
机译:Ras是人类癌症中最常突变的基因,但突变RAS的抑制剂已被证明是挑战性的。鉴于直接靶向RAS的困难,影响突变场RAS操作的其他部件的药物可能是有效的。然而,必须理解,在下游效应器和互锁反馈和前馈回路之间的竞争,包括RAS同种型的不同本地化,并且必须理解为完全掌握抑制特定目标的机会和限制。数学建模可以帮助我们辨别正常和癌细胞中这些特征的系统级别影响。新技术使得采购能够促进致癌性RAS行为的现实模型的发展。鉴于几十年的研究和收集新数据的实验方法的实验方法的大量经验数据,建模者现在有机会推动实现突变体RAS驱动癌症的靶向治疗的进展。

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