Long-term competition experiments reveal limited adaptive evolution in human cell lines

Cancer progression is driven by somatic evolution, where mutations and selection generate more adapted clones. However, it remains unclear whether human cells continue to evolve under stable laboratory conditions or instead reach a near-optimal state. We addressed this using two human cell lines, HeLa and 293, with isogenic subpopulations differing only by a fitness-neutral marker (inducible GFP expression). Mixed GFP⁺ and GFP⁻ populations were co-cultured for 12 months under constant conditions, with competition assays performed with or without periodic GFP induction and sorting. In a parallel experiment inspired by Velicer's microbial studies, GFP⁺ cells were exposed to independently cultured, non-evolving GFP⁻ populations to test whether competitively advantageous variants could emerge when competitors could not respond. Initially, we observed patterns consistent with genetic drift, followed by a gradual expansion of GFP⁻ cells. After 4-6 months, a likely beneficial mutation in the GFP⁺ 293 population reversed this trend, whereas GFP⁻ HeLa cells retained their advantage. Fitness differences were small, and observed dynamics were consistent with weak selection. These results suggest that long-term cultured human cells evolve slowly without rapid clonal expansion.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-06-19
DOI
https://doi.org/10.1038/s41598-026-58033-9
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Long-term competition experiments reveal limited adaptive evolution in human cell lines

Elżbieta Speina, Jacek Bardowski, Kamila Kłosowska-Kosicka, Agnieszka Tupalska et al.
Scientific Reports
Single-cell and spatial transcriptomics
article

Long-term competition experiments reveal limited adaptive evolution in human cell lines

Elżbieta Speina, Jacek Bardowski, Kamila Kłosowska-Kosicka, Agnieszka Tupalska, Iwona Grądzka, Szymon Kaczanowski, Roman J. Szczęsny
article en

Abstract

Cancer progression is driven by somatic evolution, where mutations and selection generate more adapted clones. However, it remains unclear whether human cells continue to evolve under stable laboratory conditions or instead reach a near-optimal state. We addressed this using two human cell lines, HeLa and 293, with isogenic subpopulations differing only by a fitness-neutral marker (inducible GFP expression). Mixed GFP⁺ and GFP⁻ populations were co-cultured for 12 months under constant conditions, with competition assays performed with or without periodic GFP induction and sorting. In a parallel experiment inspired by Velicer's microbial studies, GFP⁺ cells were exposed to independently cultured, non-evolving GFP⁻ populations to test whether competitively advantageous variants could emerge when competitors could not respond. Initially, we observed patterns consistent with genetic drift, followed by a gradual expansion of GFP⁻ cells. After 4-6 months, a likely beneficial mutation in the GFP⁺ 293 population reversed this trend, whereas GFP⁻ HeLa cells retained their advantage. Fitness differences were small, and observed dynamics were consistent with weak selection. These results suggest that long-term cultured human cells evolve slowly without rapid clonal expansion.

Scientific Reports
Instytut Chemii i Techniki Jądrowej (PL), Institute of Biochemistry and Biophysics, Polish Academy of Sciences (PL)
Narodowe Centrum Nauki
Openalex Percentile: Top 11%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.