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Updated: Jun 13, 2025

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
Published on: December 9, 2015
Epigenetic Heritability of Cell Plasticity Drives Cancer Drug Resistance through a One-to-Many Genotype-to-Phenotype
Erica A Oliveira1, Salvatore Milite2, Javier Fernandez-Mateos1
1Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
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.
Significance:
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.
Insights
Cancer drug resistance involves genetic changes and adaptability. This study shows targeted drugs select specific cancer cell groups, while chemotherapy resistance relies on temporary cell changes, revealing a "permissive epigenome" that aids cancer adaptability.
Area of Science:
- Oncology
- Cancer Biology
- Epigenetics
Background:
- Cancer drug resistance is a complex challenge, stemming from both genetic alterations and cellular adaptability.
- Understanding the interplay between heritable changes and phenotypic plasticity is crucial for overcoming treatment failure.
Purpose of the Study:
- To investigate the distinct drivers of drug resistance in colorectal cancer using patient-derived organoids.
- To elucidate the mechanisms underlying acquired resistance to targeted therapies versus chemotherapy.
Main Methods:
- Longitudinal drug perturbation of colorectal cancer patient-derived organoids.
- Single-cell multi-omics analysis, lineage tracking, and evolutionary modeling.
- Application of machine learning to analyze complex resistance data.
Main Results:
- Targeted drugs selectively expand distinct cancer cell subclones, informing rational drug sequencing.
- A heritable epigenetic configuration acts as cellular memory, enabling a one-to-many genotype-to-phenotype map for resistance.
- Chemotherapy resistance is primarily driven by transient phenotypic plasticity, not stable clonal selection.
- Chromosomal instability influences clonal evolution but not convergent transcriptional programs.
Conclusions:
- The study identifies a
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