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In Vitro Tumor Cell Rechallenge For Predictive Evaluation of Chimeric Antigen Receptor T Cell Antitumor Function
Published on: February 27, 2019
Clonal differences underlie variable responses to sequential and prolonged treatment
Abstract:
Cancer cells exhibit dramatic differences in gene expression at the single-cell level which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA-sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor.
Insights
Cancer cell heterogeneity drives treatment resistance. Clones respond differently to subsequent therapies, guiding future treatment selection for aggressive cancer cells.
Area of Science:
- Oncology
- Genomics
- Cell Biology
Background:
- Cancer cells display significant single-cell gene expression variability, influencing treatment resistance.
- Treatment can exacerbate this heterogeneity, leading to diverse resistant cell states.
- The distinct responses of these resistant clones to further or continued treatment are not well understood.
Approach:
- Utilized single-cell RNA-sequencing combined with barcoding techniques.
- Tracked the evolution of resistant cancer clones under prolonged and sequential treatment conditions.
- Analyzed gene expression states to identify predictors of clone survival.
Key Points:
- Cells within the same clone maintain similar gene expression profiles after multiple treatment rounds.
- Individual clones exhibit distinct and varied outcomes (growth, survival, death) upon re-treatment or continued therapy.
- Identified specific gene expression signatures associated with clone survival.
Conclusions:
- Cancer clone heterogeneity dictates differential responses to therapeutic interventions.
- Understanding clone-specific fates is crucial for developing targeted cancer therapies.
- This research lays the groundwork for selecting optimal treatments against aggressive resistant clones.
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