Abstract A072 The PIK3CA/AKT pathway drives therapy resistance in rhabdomyosarcoma
Bibliographic record
Abstract
Abstract Olaparib and temozolomide (OT) combination therapy is in clinical trial evaluation for adolescent rhabdomyosarcoma (RMS) muscle cancers. Unfortunately, resistance to OT has been reported in other cancers, with no counterstrategies available. Using preclinical mouse xenograft experiments, we show that OT is effective at curbing RMS growth, yet a subset of tumors develop resistance that is associated with transcriptomic changes that occur in the absence of recurrent genomic mutation. Importantly, a vast majority of resistant RMS models upregulate the PIK3CA/AKT pathway, which in turn activates NRF2 transcription factor phosphorylation and subsequent transcriptional expression of multidrug resistance ABC transport proteins that rapidly efflux drugs from cells. Using dynamic real-time imaging of tumor growth and assessing drug responses at single-cell resolution in human cell line models, we found that the PIK3CA inhibitor alpelisib re-sensitized resistant RMS cells to OT therapy by suppressing the expression of ABC transport proteins. Excitingly, RMS uses the same PIK3CA/AKT pathway activation to drive resistance to standard-of-care combination therapy vincristine, actinomycin D, and cyclophosphamide (VAC) and the combination of OT + alpelisib effectively killed VAC-resistant RMS. Alpelisib also re-sensitized resistant RMS to chemotherapy in preclinical xenograft mouse models resulting in reduced tumor burden and extended disease-free survival. Our work defines a common resistance pathway in RMS and has credentialled a new preclinical strategy to kill therapy-resistant RMS. Citation Format: Yueyang Wang, Qiqi Yang, Chuan Yan, David M. Langenau. The PIK3CA/AKT pathway drives therapy resistance in rhabdomyosarcoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A072.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".