Dynamic analysis of pulsed cisplatin identifies effectors of resistance in lung adenocarcinoma
Bibliographic record
Abstract
Abstract Identification of clinically viable strategies for overcoming resistance to platinum chemotherapy in lung adenocarcinoma has been hampered by inappropriately tailored in vitro assays of drug response. Therefore, using a pulse model that closely recapitulates the in vivo pharmacokinetics of platinum therapy, we profiled cisplatin-induced signalling, DNA damage and apoptotic responses across a panel of lung adenocarcinoma cell lines. By coupling this data with real-time, single cell imaging of cell cycle and apoptosis, we show that TP53 mutation status influenced the mode of cisplatin induced cell cycle arrest, but could not predict cisplatin sensitivity. In contrast, P70S6K-mediated signalling promoted resistance by increasing p53/p63 and p21 expression, reducing double-stranded DNA breaks and apoptosis. Targeting P70S6K sensitised both TP53 wildtype and null lines to cisplatin, but not TP53 mutant lines. In summary, using in vitro assays that mimic in vivo pharmacokinetics identified P70S6K as a robust mediator of cisplatin resistance and highlighted the importance of considering somatic mutation status when designing patient-specific combination therapies.
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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".