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posted on 2025-08-01, 07:21 authored by Erica A. Oliveira, Salvatore Milite, Javier Fernandez-Mateos, George D. Cresswell, Erika Yara-Romero, Georgios Vlachogiannis, Bingjie Chen, Chela T. 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 <p>Experimental design of long-term drug resistance evolution in colorectal cancer organoids. <b>A,</b> Workflow of lentiviral barcoding in colorectal cancer (CRC) organoid single cells as an evolutionary tracking tool. MOI, multiplicity of infection; RFP, red fluorescent protein. <b>B,</b> Experimental design of long-term drug resistance evolution in an MSS AKT–mutant organoid. Bulk DNA profiling was performed for genomic characterization and barcode measurement, as well as scRNA-seq and corresponding single-cell barcode extraction of five “solid” time points over 5 months: parental, under drug 1, regrowth after drug 1, under drug 2, and regrowth after drug 2. Additionally, floating DNA was collected every 2 days from the supernatant to profile barcodes as a “liquid biopsy.” <b>C,</b> Cells were exposed to four different sequences of drugs with first- and second-line treatments. <b>D,</b> In a second experiment, both organoid lines (MSS and MSI) were exposed to an ERK inhibitor and oxaliplatin. Before drug pressure, CIN was induced with CENP-E inhibitors alone or in combination with the MPS1 inhibitor to assess CIN effects on drug resistance. AKTi, AKT inhibitor; ERKi, ERK inhibitor; MEKi, MEK inhibitor. Created in BioRender. Sottoriva, A. (2025) <a href="https://BioRender.com/7toyszr" target="_blank">https://BioRender.com/7toyszr</a>.</p>
Funding
Cancer Research UK (CRUK)
Wellcome Trust (WT)
Fondazione AIRC per la ricerca sul cancro ETS (AIRC)
NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research (BRC)
Department of Aeronautics, Imperial College London
History
ARTICLE ABSTRACT
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.
