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

Journal: Cancer research
Published Date:

Abstract

UNLABELLED: 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.

Authors

  • Erica A Oliveira
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
  • Salvatore Milite
    Computational Biology Research Centre, Human Technopole, Milan, Italy. salvatore.milite@fht.org.
  • Javier Fernández-Mateos
    Molecular Medicine Unit, IBSAL, Department of Medicine, University of Salamanca, Salamanca, Spain.
  • George D Cresswell
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
  • Erika Yara-Romero
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
  • Georgios Vlachogiannis
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
  • Bingjie Chen
    Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu, China.
  • Chela T James
    Computational Biology Research Centre, Human Technopole, Milan, Italy.
  • Lucrezia Patruno
    Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.
  • Gianluca Ascolani
    Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.
  • Ahmet Acar
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
  • Timon Heide
    Computational Biology Research Centre, Human Technopole, Milan, Italy.
  • Inmaculada Spiteri
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
  • Alex Graudenzi
    Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.
  • Giulio Caravagna
    Department of Mathematics, Informatics and Geosciences, University of Trieste, Trieste, Italy. gcaravagna@units.it.
  • Andrea Bertotti
    Department of Oncology, University of Torino, Turin, Italy.
  • Trevor A Graham
    Centre for Evolution and Cancer, Institute of Cancer Research, London, United Kingdom.
  • Luca Magnani
    Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom.
  • Nicola Valeri
    Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
  • Andrea Sottoriva
    Computational Biology Research Centre, Human Technopole, Milan, Italy. andrea.sottoriva@fht.org.