A Combination Approach of Pseudotime Analysis And Mathematical Modeling For Understanding The Drug-Resistant Mechanisms Article Swipe
Shigeyuki Magi
,
Sewon Ki
,
Masao Ukai
,
Elisa Domínguez‐Hüttinger
,
Atsuhiko T. Naito
,
Yutaka Suzuki
,
Mariko Okada
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-136924/v2
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-136924/v2
Cancer cells acquire drug resistance through the following nonresistant, pre-resistant, and resistant stages. 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. The other showed 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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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-136924/v2
- OA Status
- green
- Cited By
- 1
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4288793348
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4288793348Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-136924/v2Digital Object Identifier
- Title
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A Combination Approach of Pseudotime Analysis And Mathematical Modeling For Understanding The Drug-Resistant MechanismsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-07-07Full publication date if available
- Authors
-
Shigeyuki Magi, Sewon Ki, Masao Ukai, Elisa Domínguez‐Hüttinger, Atsuhiko T. Naito, Yutaka Suzuki, Mariko OkadaList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-136924/v2Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://doi.org/10.21203/rs.3.rs-136924/v2Direct OA link when available
- Concepts
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Tamoxifen, Drug resistance, Gene, Biology, Gene expression, Mechanism (biology), Computational biology, Breast cancer, Drug, Cancer, Cancer research, Genetics, Pharmacology, Philosophy, EpistemologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2022: 1Per-year citation counts (last 5 years)
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41Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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