Navigating Nongenetic Plasticity in Cancer Drug Resistance

Nongenetic plasticity has emerged as a key driver of cancer drug resistance, yet its precise origins, nature, and consequences are not fully clarified. This review examines technological, computational, and conceptual developments in the nongenetic determinants of drug resistance. We begin by proposing refined definitions of cellular state, fate, and plasticity. We subsequently contextualize the findings from multimodal approaches to investigate plasticity, highlighting how new single-cell lineage-tracing methods provide opportunities for quantitatively capturing state transitions, their timescales and heritability, and how they contribute to resistance mechanisms. We also draw parallels with concepts from developmental biology and microbial persistence research. Next, we cover the role that computational approaches have played in revealing the otherwise latent patterns of heterogeneity that underlie plasticity from complex datasets. We conclude by emphasizing the need for standardized terminology in this rapidly evolving field and the path from bench to bedside.

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Publication Details

Journal
Annual Review of Cancer Biology
Published
2024-12-11
DOI
https://doi.org/10.1146/annurev-cancerbio-071924-084617
Citations
6
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
1.71
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article

Navigating Nongenetic Plasticity in Cancer Drug Resistance

Vadim Backman, Madeline E. Melzer, Nitu Kumari, Yogesh Goyal et al.
6 citations
Annual Review of Cancer Biology
Cancer Genomics and Diagnostics
1.71
article

Navigating Nongenetic Plasticity in Cancer Drug Resistance

Vadim Backman, Madeline E. Melzer, Nitu Kumari, Yogesh Goyal, Hanxiao Sun
article en
6 citations

Abstract

Nongenetic plasticity has emerged as a key driver of cancer drug resistance, yet its precise origins, nature, and consequences are not fully clarified. This review examines technological, computational, and conceptual developments in the nongenetic determinants of drug resistance. We begin by proposing refined definitions of cellular state, fate, and plasticity. We subsequently contextualize the findings from multimodal approaches to investigate plasticity, highlighting how new single-cell lineage-tracing methods provide opportunities for quantitatively capturing state transitions, their timescales and heritability, and how they contribute to resistance mechanisms. We also draw parallels with concepts from developmental biology and microbial persistence research. Next, we cover the role that computational approaches have played in revealing the otherwise latent patterns of heterogeneity that underlie plasticity from complex datasets. We conclude by emphasizing the need for standardized terminology in this rapidly evolving field and the path from bench to bedside.

Annual Review of Cancer BiologyVol. 9(1)
Northwestern University (US), Chan Zuckerberg Initiative (United States) (US), Chan Zuckerberg Biohub Chicago
Good health and well-being
Openalex Percentile: Top 14%
Cancer Genomics and Diagnostics
1.71
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