Abstract A018: YAP signaling promotes resistance to MEK and AKT inhibition in NF1-related MPNSTs
Bibliographic record
Abstract
Abstract Malignant peripheral nerve sheath tumors (MPNSTs) are a rare and deadly sarcoma with few therapeutic options that are the leading cause of death for patients with Neurofibromatosis Type 1 (NF1). MPNSTs are characterized by a large burden of genomic alterations, chemoresistance, and a 5-year survival rate of 25-50%. NF1 is the major negative regulator of RAS, therefore a hallmark of MPNSTs is deregulated RAS/MAPK signaling. To date, no targeted therapies have been approved for MPNST treatment, highlighting the need for an understanding of adaptive signaling mechanisms that drive resistance. The HIPPO pathway is a key regulator of organ growth and cellular differentiation and is a central driver of resistance to RAS pathway inhibition in other cancers. The key HIPPO effector, YAP1, interacts with RAS and AKT signaling pathways, creating alternate routes for resistance in multiple cancers. In our studies, we identified strong YAP activation in response to MEK and AKT inhibition in MPNST cell lines. Since YAP acts as a transcriptional co-activator through interaction with TEAD transcription factors, we proposed that targeting the Hippo pathway in MPNST will abrogate MAPK inhibitor resistance. To investigate tumor signaling responses and efficacy in vivo, we utilized 3 genomically distinct MPNST patient-derived xenograft (PDX) models. To assess drivers of MPNST resistance, we have developed a preclinical model of drug resistance that simulates clinical treatment schedules. Using a cross-over and a drug holiday design, we are able to evaluate patterns of response and resistance to resumed treatment. We observed distinctive responses to MEK and AKT inhibitors in each PDX line; however, the impact on MPNST growth was minimal with single agent treatment. Comparison of pathway activation between the “drug holiday” biopsies and the treatment endpoint, demonstrated distinct YAP and RAS (pERK) activation levels in resistant tumors. For example, strong YAP activation is observed in correlation with decreased pERK in resistant tumors. YAP activation was strongest at the invasive edge of viable tumor regions. Currently, we are evaluating the efficacy and signaling adaptations to investigate the underlying molecular mechanisms in these MPNST models. Overall, we have demonstrated the development of a clinically relevant model of MPNST resistance and a potential switch between RAS and YAP signaling that promotes resistance to MEK or AKT inhibition. Citation Format: Lauren McGee, Curt Essenburg, Lisa Turner, Angela Hirbe, Anwesha Dey, Jason Zbieg, Carrie Graveel, Matt Steensma. YAP signaling promotes resistance to MEK and AKT inhibition in NF1-related MPNSTs [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A018.
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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) | 0.004 | 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".