Evolutionary unpredictability in cancer model systems.

IF 3.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Reports Pub Date : 2025-06-27 DOI:10.1038/s41598-025-07407-6

Subhayan Chattopadhyay, Jenny Karlsson, Michele Ferro, Adriana Mañas, Ryu Kanzaki, Elina Fredlund, Andrew J Murphy, Christopher L Morton, Natalie Andersson, Mary A Woolard, Karin Hansson, Katarzyna Radke, Andrew M Davidhoff, Sofie Mohlin, Kristian Pietras, Daniel Bexell, David Gisselsson

{"title":"Evolutionary unpredictability in cancer model systems.","authors":"Subhayan Chattopadhyay, Jenny Karlsson, Michele Ferro, Adriana Mañas, Ryu Kanzaki, Elina Fredlund, Andrew J Murphy, Christopher L Morton, Natalie Andersson, Mary A Woolard, Karin Hansson, Katarzyna Radke, Andrew M Davidhoff, Sofie Mohlin, Kristian Pietras, Daniel Bexell, David Gisselsson","doi":"10.1038/s41598-025-07407-6","DOIUrl":null,"url":null,"abstract":"<p><p>Despite the advent of advanced molecular prognostic tools, it is still difficult to predict the course of disease for cancer patients at the individual level. This lack of predictability is also reflected in many experimental cancer model systems, begging the question of whether certain biological aspects of cancer (eg. growth, evolution etc.) can ever be anticipated or if there remains an inherent unpredictability to cancer, similar to other complex biological systems. We demonstrate by a combination of agent-based mathematical modelling, analysis of patient-derived xenograft model systems from multiple cancer types, and in-vitro culture that certain conditions increase stochasticity of the clonal landscape of cancer growth. Our findings indicate that under those conditions, the cancer genome may behave as a complex dynamic system, making its long-term evolution inherently unpredictable.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"20334"},"PeriodicalIF":3.9000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12205069/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-07407-6","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}

引用次数: 0

Abstract

Despite the advent of advanced molecular prognostic tools, it is still difficult to predict the course of disease for cancer patients at the individual level. This lack of predictability is also reflected in many experimental cancer model systems, begging the question of whether certain biological aspects of cancer (eg. growth, evolution etc.) can ever be anticipated or if there remains an inherent unpredictability to cancer, similar to other complex biological systems. We demonstrate by a combination of agent-based mathematical modelling, analysis of patient-derived xenograft model systems from multiple cancer types, and in-vitro culture that certain conditions increase stochasticity of the clonal landscape of cancer growth. Our findings indicate that under those conditions, the cancer genome may behave as a complex dynamic system, making its long-term evolution inherently unpredictable.

查看原文本刊更多论文

癌症模型系统的进化不可预测性。

尽管出现了先进的分子预后工具，但在个体水平上预测癌症患者的病程仍然很困难。这种可预测性的缺乏也反映在许多实验性癌症模型系统中，从而回避了癌症的某些生物学方面(例如：生长，进化等)是可以预测的，或者如果癌症仍然存在固有的不可预测性，类似于其他复杂的生物系统。我们通过结合基于agent的数学建模、对多种癌症类型的患者来源的异种移植模型系统的分析以及体外培养证明，某些条件会增加癌症生长克隆景观的随机性。我们的研究结果表明，在这些条件下，癌症基因组可能表现为一个复杂的动态系统，使其长期进化本质上不可预测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Scientific Reports Natural Science Disciplines-

CiteScore

7.50

自引率

4.30%

发文量

19567

审稿时长

3.9 months

期刊介绍： We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections. Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021). •Engineering Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live. •Physical sciences Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics. •Earth and environmental sciences Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems. •Biological sciences Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants. •Health sciences The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.