Temporally sequenced anticancer drugs overcome adaptive resistance by targeting a vulnerable chemotherapy-induced phenotypic transition
Bibliographic record
Abstract
Understanding the emerging models of adaptive resistance is key to overcoming cancer chemotherapy failure. Using human breast cancer explants, in vitro cell lines, mouse in vivo studies and mathematical modelling, here we show that exposure to a taxane induces phenotypic cell state transition towards a favoured transient CD44(Hi)CD24(Hi) chemotherapy-tolerant state. This state is associated with a clustering of CD44 and CD24 in membrane lipid rafts, leading to the activation of Src Family Kinase (SFK)/hemopoietic cell kinase (Hck) and suppression of apoptosis. The use of pharmacological inhibitors of SFK/Hck in combination with taxanes in a temporally constrained manner, where the kinase inhibitor is administered post taxane treatment, but not when co-administered, markedly sensitizes the chemotolerant cells to the chemotherapy. This approach of harnessing chemotherapy-induced phenotypic cell state transition for improving antitumour outcome could emerge as a translational strategy for the management of cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".