Omics · study · 2026
Mathematical modelling reveals a ribosome level-induced survival checkpoint in drug-tolerant cancer persister cells
Listed in NCBI GEO
Systemic treatments for advanced cancers initially provide benefits but rarely lead to a cure due to acquired resistance.
Description
Drug-tolerant persister (DTP) cells, devoid of new mutations, can temporarily tolerate treatment. In previous study, we observed that melanoma DTP cells downregulated mRNA translation activity while enhancing the selective translation of a subset of mRNAs.
However, the mechanisms governing the selective translation in DTP cells remain unclear. In this study, we have established a mathematical framework to investigate selective mRNA translation in DTP cells, employing a combination of stochastic mathematical modelling and experimental characterization. Our findings indicate that changes in mRNA translation are a common occurrence in DTP cells across various cancer types and treatments.
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The diminished activity of Myc-mediated ribosome biogenesis leads to a restricted resource for active mRNA translation in DTP cells. This bottleneck effect, resulting from reduced ribosome levels, initiates a competition among mRNAs, as demonstrated through stochastic mathematical modelling. Utilizing this mathematical model, we have explored potential therapeutic strategies to delay the onset of drug resistance.
Hence, our theoretical framework exposes a ribosome-induced survival checkpoint in DTP cells, driven by limited ribosome levels. This discovery suggests therapeutic potential based on ribosome thresholds, providing a foundation for developing strategies to counteract drug resistance.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE313nnn/GSE313946 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE313946 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1387408 ncbi.nlm.nih.gov/bioproject/PRJNA1387408 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens · Mus musculus
- From keywords
- Life Sciences
- Inferred from text
- Cancer 75%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE313946 | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[organism].NCBITaxon:10090 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |