Investigating the evolution of cancer cells through single cell genomic data.

通过单细胞基因组数据研究癌细胞的进化。

• 批准号: NE/T014199/1
• 负责人: Ruth Baker
• 金额: $ 1.29万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FT014199%2F1
• 关键词: Investigating; evolution; cancer; cells; through

BBSRC : Thomas Pak : BB/M011224/1Cancer evolution is inherent to tumour progression. Cell-intrinsic processes such as mutation accumulation, epigenetic modification or translation regulation induce diversity within tumour-comprising cell populations, providing a substrate for evolutionary selection in microenvironmental and therapeutic contexts. Yet, little is known about how to anticipate evolutionary dynamics of a malignant cell population. As such, evolution in cancers is often observed after selection has occurred, for example in the relapsed or metastatic settings-often too late for effective intervention. In this research project, we consider modelling cancer progression processes so as to anticipate, with statistical rigour, the likely growth trajectory of a cancer cell population in the context of unperturbed and perturbed states. Core open questions derived from this concept remain, including the most fundamental: "How can fitness be calculated and used as a predictive property in the growth trajectory of cancer cells?".

BBSRC: Thomas Pak: BB/ m011224 /1肿瘤进化是肿瘤进展所固有的。细胞内在过程，如突变积累、表观遗传修饰或翻译调节，诱导肿瘤细胞群体的多样性，为微环境和治疗背景下的进化选择提供了基础。然而，人们对如何预测恶性细胞群的进化动力学知之甚少。因此，癌症的进化通常是在选择发生后才观察到的，例如在复发或转移的情况下——通常为时已晚，无法进行有效的干预。在本研究项目中，我们考虑对癌症进展过程进行建模，以便以统计严谨的方式预测癌细胞群在未受干扰和受干扰状态下的可能生长轨迹。从这一概念衍生出的核心未决问题仍然存在，包括最基本的问题：“如何计算适合度，并将其作为癌细胞生长轨迹的预测属性？”