ArticleScientific reports2021
A combination approach of pseudotime analysis and mathematical modeling for understanding drug-resistant mechanisms.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Inference of Genetic Networks from Pseudo Time Series of Single-cell Gene Expression Data using Modified Random Forests.Bulletin of mathematical biology · 2026Article
- Single-cell transcriptomics reveals biomarker heterogeneity linked to CDK4/6 Inhibitor resistance in breast cancer cell lines.NPJ breast cancer · 2025Article
- A mathematical framework for human neutrophil state transitions inferred from single-cell RNA sequence data.Frontiers in immunology · 2025Article
- Human-Brain-Derived Ischemia-Induced Stem Cell Transplantation Is Associated with a Greater Neurological Functional Improvement Compared with Human-Bone Marrow-Derived Mesenchymal Stem Cell Transplantation in Mice After Stroke.International journal of molecular sciences · 2024Article
- Article
- Transplantation of Human Brain-Derived Ischemia-Induced Multipotent Stem Cells Ameliorates Neurological Dysfunction in Mice After Stroke.Stem cells translational medicine · 2023Article
- Proteomic time course of breast cancer cells highlights enhanced sensitivity to Stat3 and Src inhibitors prior to endocrine resistance development.Cancer gene therapy · 2023Article
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7 authors.
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Abstract
Cancer cells acquire drug resistance through the following stages: nonresistant, pre-resistant, and resistant. Although the molecular mechanism of drug resistance is well investigated, the process of drug resistance acquisition remains largely unknown. Here we elucidate the molecular mechanisms underlying the process of drug resistance acquisition by sequential analysis of gene expression patterns in tamoxifen-treated breast cancer cells. Single-cell RNA-sequencing indicates that tamoxifen-resistant cells can be subgrouped into two, one showing altered gene expression related to metabolic regulation and another showing high expression levels of adhesion-related molecules and histone-modifying enzymes. Pseudotime analysis showed a cell transition trajectory to the two resistant subgroups that stem from a shared pre-resistant state. An ordinary differential equation model based on the trajectory fitted well with the experimental results of cell growth. Based on the established model, it was predicted and experimentally validated that inhibition of transition to both resistant subtypes would prevent the appearance of tamoxifen resistance.
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