{"title":"On the patterns of genetic intra-tumour heterogeneity before and after treatment.","authors":"Alexander Stein, Benjamin Werner","doi":"10.1093/genetics/iyaf101","DOIUrl":null,"url":null,"abstract":"<p><p>Genetic intra-tumour heterogeneity (gITH) is a universal property of all cancers. It emerges from the interplay of cell division, mutation accumulation and selection with important implications for the evolution of treatment resistance. Theoretical and data-driven approaches extensively studied gITH in ageing somatic tissues or cancers at detection. Yet, the expected patterns of gITH during and after treatment are less well understood. Here, we use stochastic birth-death processes to investigate the expected patterns of gITH across different treatment scenarios. We consider homogeneous treatment response with shrinking, growing and stable disease, and follow up investigating heterogeneous treatment response with sensitive and resistant cell types. We derive analytic expressions for the site frequency spectrum, the total mutational burden and the single-cell mutational burden distribution that we validate with computer simulations. We find that the site frequency spectrum after homogeneous treatment response retains its characteristic power-law tail, while emergent resistant clones cause peaks corresponding to their sizes. The frequency of the largest resistant clone is subdominant and independent of the population size at detection, whereas the relative total number of resistant cells increases with detection size. Furthermore, the growth dynamics under treatment determine whether the total mutational burden is dominated by preexisting or newly acquired mutations, suggesting different possible treatment strategies.</p>","PeriodicalId":12706,"journal":{"name":"Genetics","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/genetics/iyaf101","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Genetic intra-tumour heterogeneity (gITH) is a universal property of all cancers. It emerges from the interplay of cell division, mutation accumulation and selection with important implications for the evolution of treatment resistance. Theoretical and data-driven approaches extensively studied gITH in ageing somatic tissues or cancers at detection. Yet, the expected patterns of gITH during and after treatment are less well understood. Here, we use stochastic birth-death processes to investigate the expected patterns of gITH across different treatment scenarios. We consider homogeneous treatment response with shrinking, growing and stable disease, and follow up investigating heterogeneous treatment response with sensitive and resistant cell types. We derive analytic expressions for the site frequency spectrum, the total mutational burden and the single-cell mutational burden distribution that we validate with computer simulations. We find that the site frequency spectrum after homogeneous treatment response retains its characteristic power-law tail, while emergent resistant clones cause peaks corresponding to their sizes. The frequency of the largest resistant clone is subdominant and independent of the population size at detection, whereas the relative total number of resistant cells increases with detection size. Furthermore, the growth dynamics under treatment determine whether the total mutational burden is dominated by preexisting or newly acquired mutations, suggesting different possible treatment strategies.
期刊介绍:
GENETICS is published by the Genetics Society of America, a scholarly society that seeks to deepen our understanding of the living world by advancing our understanding of genetics. Since 1916, GENETICS has published high-quality, original research presenting novel findings bearing on genetics and genomics. The journal publishes empirical studies of organisms ranging from microbes to humans, as well as theoretical work.
While it has an illustrious history, GENETICS has changed along with the communities it serves: it is not your mentor''s journal.
The editors make decisions quickly – in around 30 days – without sacrificing the excellence and scholarship for which the journal has long been known. GENETICS is a peer reviewed, peer-edited journal, with an international reach and increasing visibility and impact. All editorial decisions are made through collaboration of at least two editors who are practicing scientists.
GENETICS is constantly innovating: expanded types of content include Reviews, Commentary (current issues of interest to geneticists), Perspectives (historical), Primers (to introduce primary literature into the classroom), Toolbox Reviews, plus YeastBook, FlyBook, and WormBook (coming spring 2016). For particularly time-sensitive results, we publish Communications. As part of our mission to serve our communities, we''ve published thematic collections, including Genomic Selection, Multiparental Populations, Mouse Collaborative Cross, and the Genetics of Sex.