Genetic variation drives cancer cell adaptation to ECM stiffness

The progression of many solid tumors is accompanied by temporal and spatial changes in the stiffness of the extracellular matrix (ECM). Cancer cells adapt to soft and stiff ECM through mechanisms that are not fully understood. It is well known that there is significant genetic heterogeneity from cell to cell in tumors, but how ECM stiffness as a parameter might interact with that genetic variation is not known. Here, we employed experimental evolution to study the response of genetically variable and clonal populations of tumor cells to variable ECM stiffness. Proliferation rates of genetically variable populations cultured on soft ECM increased over a period of several weeks, whereas clonal populations did not evolve. Tracking of DNA barcoded cell lineages revealed that soft ECM consistently selected for the same few variants. These data provide evidence that ECM stiffness exerts natural selection on genetically variable tumor populations. Soft-selected cells were highly migratory, with enriched oncogenic signatures and unusual behaviors such as spreading and traction force generation on ECMs with stiffness as low as 1 kPa. Rho-regulated cell spreading was found to be the directly selected trait, with yes-associated protein 1 translocation to the nucleus mediating fitness on soft ECM. Overall, these data show that genetic variation can drive cancer cell adaptation to ECM stiffness.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2024-09-20
DOI
https://doi.org/10.1073/pnas.2403062121
Citations
8
Primary Topic
Cellular Mechanics and Interactions
Type
article
Field-Weighted Citation Impact
2.61

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article

Genetic variation drives cancer cell adaptation to ECM stiffness

Richard L. Bennett, Tanmay P. Lele, Richa Rashmi, Ting‐Ching Wang et al.
8 citations
Proceedings of the National Academy of Sciences
Cellular Mechanics and Interactions
2.61
article

Genetic variation drives cancer cell adaptation to ECM stiffness

Richard L. Bennett, Tanmay P. Lele, Richa Rashmi, Ting‐Ching Wang, Jonathan D. Licht, Marcos R. Estecio, Charles F. Baer, Amy Brock, Irtisha Singh, Daylin Morgan, Suchitaa Sawhney
article en
8 citations

Abstract

The progression of many solid tumors is accompanied by temporal and spatial changes in the stiffness of the extracellular matrix (ECM). Cancer cells adapt to soft and stiff ECM through mechanisms that are not fully understood. It is well known that there is significant genetic heterogeneity from cell to cell in tumors, but how ECM stiffness as a parameter might interact with that genetic variation is not known. Here, we employed experimental evolution to study the response of genetically variable and clonal populations of tumor cells to variable ECM stiffness. Proliferation rates of genetically variable populations cultured on soft ECM increased over a period of several weeks, whereas clonal populations did not evolve. Tracking of DNA barcoded cell lineages revealed that soft ECM consistently selected for the same few variants. These data provide evidence that ECM stiffness exerts natural selection on genetically variable tumor populations. Soft-selected cells were highly migratory, with enriched oncogenic signatures and unusual behaviors such as spreading and traction force generation on ECMs with stiffness as low as 1 kPa. Rho-regulated cell spreading was found to be the directly selected trait, with yes-associated protein 1 translocation to the nucleus mediating fitness on soft ECM. Overall, these data show that genetic variation can drive cancer cell adaptation to ECM stiffness.

Proceedings of the National Academy of SciencesVol. 121(39)
The University of Texas MD Anderson Cancer Center (US), University of Florida Health (US), University of Florida (US), UF Health Cancer Center, The University of Texas at Austin (US), Texas A&M University (US), Bryan College (US)
Cancer Prevention and Research Institute of Texas, National Institutes of Health
Openalex Percentile: Top 11%
Cellular Mechanics and Interactions
2.61
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