Abstract LB-214: Common genomic alterations in malignant peripheral nerve sheath tumors augment Aurora A activity and sensitize tumors to aurora kinase inhibitors.
Bibliographic record
Abstract
Abstract Malignant peripheral nerve sheath tumours (MPNST) are rare, hereditary, cancers associated with mutations in the neurofibromin 1 gene 1. MPNSTs are often resistant to chemotherapies and have high rates of disease recurrence, highlighting the lack of effective treatment options for this cancer. Aurora kinase A inhibitors (AKIs) have shown promise against MPNST cell lines 2. We expanded this study by testing AKI in human MPNST xenotransplant mice models. Treatment resulted in stabilized disease with tumor cells undergoing senescence and endoreduplication. Aurora kinase A (AURKA) is an emerging target in cancer, however, targeted therapies can often fail in the clinic due to insufficient knowledge about factors that determine tumor response. Therefore, we utilized three MPNST cell lines and profiled them for the expression and activity of AURKA as well as their responses to AKIs. The most proliferative lines, S462 and 2884, express equivalent levels of AURKA, however, S462 cells were more sensitive to kinase inhibition. Both cell lines experienced apoptosis, senescence and endoreduplication in response to AKI treatment. AURKA activity is regulated by a co-activator, the Targeting Protein for XKlp2 (TPX2) and a molecular brake, the Receptor for Hyaluronan Mediated Motility (RHAMM)3. Interestingly, published analysis of copy number variation has identified hemizygous loss of the RHAMM gene in half of the examined high-grade MPNST, but not in benign or low grade tumors 4. We proposed that MPNSTs with RHAMM deletions are oncogene addicted to AURKA activity and are therefore, particularly susceptible to AKI. We profiled our MPNST lines for RHAMM and TPX2 expression and found that S462 cells express significantly more TPX2 and less RHAMM compared to 2884 cells. Furthermore, S462 cells had increased kinase. To determine whether levels of these molecular regulators could affect AKI efficacy we depleted RHAMM and TPX2 in 2884 and S462 cells respectively. While cells with reduced TPX2 have unchanged responses to AKIs, RHAMM depleted cells have a 2 fold reduction in IC-50s. We also looked at the effect of AKI against a population of MPNST tumor-initiating cells (TICs) from the S462 line. Compared to adherent cells, S462 TICs have elevated AURKA activity and their ability to self-renew in vitro is arrested by AKI. Indeed, the altered levels of kinase activity in the RHAMM and TPX2 depletion lines correlated with their ability to form and maintain sphere culture. In addition, we find that AKI treated S462 TICs differentiated into terminal neurons. All in all, these data indicate AURKA as a rational therapy for aggressive MPNSTs with RHAMM serving as a biomarker for AKI efficacy. Citation Format: Pooja Mohan, Joan Castellsague, Jihong Jiang, Kristi Allen, Helen Chen, Oksana Nemirovsky, Melanie Spyra, Kaiji Hu, Lan Kluwe, Miguel Pujana, Alberto Villanueva, Victor Mautner, Sandra Dunn, Jonathan Keats, Conxi Lazaro, Christopher Maxwell. Common genomic alterations in malignant peripheral nerve sheath tumors augment Aurora A activity and sensitize tumors to aurora kinase inhibitors. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-214. doi:10.1158/1538-7445.AM2013-LB-214
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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) | 0.003 | 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".