Epigenetic Heritability of Cell Plasticity Drives Cancer Drug Resistance through a One-to-Many Genotype-to-Phenotype Paradigm

表观遗传学 基因型 表型 癌症 生物 遗传力 表型可塑性 遗传学 抗药性 基因型-表型区分 生物信息学 基因
作者
Érica A. Oliveira,Salvatore Milite,Javier Fernández-Mateos,George D. Cresswell,Erika Yara-Romero,Georgios Vlachogiannis,Bingjie Chen,Chela James,Lucrezia Patruno,Gianluca Ascolani,Ahmet Acar,Timon Heide,Inmaculada Spiteri,Alex Graudenzi,Giulio Caravagna,Andrea Bertotti,Trevor A. Graham,Luca Magnani,Nicola Valeri,Andrea Sottoriva
出处
期刊:Cancer Research [American Association for Cancer Research]
卷期号:85 (15): 2921-2938
标识
DOI:10.1158/0008-5472.can-25-0999
摘要

Cancer drug resistance is multifactorial, driven by heritable (epi)genetic changes but also by phenotypic plasticity. In this study, we dissected the drivers of resistance by perturbing organoids derived from patients with colorectal cancer longitudinally with drugs in sequence. Combined longitudinal lineage tracking, single-cell multiomics analysis, evolutionary modeling, and machine learning revealed that different targeted drugs select for distinct subclones, supporting rationally designed drug sequences. The cellular memory of drug resistance was encoded as a heritable epigenetic configuration from which multiple transcriptional programs could run, supporting a one-to-many (epi)genotype-to-phenotype map that explains how clonal expansions and plasticity manifest together. This epigenetic landscape may ensure drug-resistant subclones can exhibit distinct phenotypes in changing environments while still preserving the cellular memory encoding for their selective advantage. Chemotherapy resistance was instead entirely driven by transient phenotypic plasticity rather than stable clonal selection. Inducing further chromosomal instability before drug application changed clonal evolution but not convergent transcriptional programs. Collectively, these data show how genetic and epigenetic alterations are selected to engender a "permissive epigenome" that enables phenotypic plasticity. Drug resistance is driven by genetic-epigenetic memory that enables cancer cells to adopt multiple phenotypic states depending on environmental conditions, supporting integration of evolutionary principles into biomarker discovery and personalized treatment strategies. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
cocohan应助科研通管家采纳,获得10
刚刚
molihuakai应助科研通管家采纳,获得10
刚刚
刚刚
Meng应助科研通管家采纳,获得10
刚刚
ding应助科研通管家采纳,获得10
1秒前
酷波er应助科研通管家采纳,获得10
1秒前
Vanilla应助科研通管家采纳,获得10
1秒前
1秒前
甘特发布了新的文献求助10
1秒前
澄子发布了新的文献求助10
2秒前
Sabrina发布了新的文献求助30
2秒前
3秒前
陶醉若云完成签到,获得积分10
3秒前
hhhhh完成签到 ,获得积分10
3秒前
3秒前
3秒前
麻瓜晋升小巫师完成签到,获得积分10
4秒前
eric完成签到,获得积分10
4秒前
5秒前
yalyy完成签到,获得积分10
5秒前
6秒前
小昭完成签到,获得积分10
6秒前
快来吃甜瓜完成签到,获得积分10
6秒前
7秒前
橙子发布了新的文献求助10
7秒前
科研民工给科研民工的求助进行了留言
7秒前
7秒前
7秒前
8秒前
8秒前
de应助你可以永远相信Sccc采纳,获得20
8秒前
shiona发布了新的文献求助10
8秒前
111完成签到,获得积分10
8秒前
Jry发布了新的文献求助10
8秒前
9秒前
英姑应助chenpaul1983采纳,获得10
9秒前
9秒前
桐桐应助深井的朵拉采纳,获得10
9秒前
盛万发布了新的文献求助10
9秒前
Hipposong应助thinking采纳,获得10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The anomeric effect 1314
Principles of town planning: translating concepts to applications 1000
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7734597
求助须知:如何正确求助?哪些是违规求助? 9284938
关于积分的说明 20167585
捐赠科研通 7312558
什么是DOI,文献DOI怎么找? 3304681
关于科研通互助平台的介绍 2457297
邀请新用户注册赠送积分活动 2313989