Abstract A158: Rational development of synergistic therapies alongside BMI1 Inhibition for group 3 medulloblastoma
Bibliographic record
Abstract
Abstract Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Of its four distinct molecular subgroups, Group 3 MBs are associated with increased risk of recurrence, metastasis and overall poor patient outcome. In recent years, small molecule inhibitors that decrease BMI1 expression have shown to be efficacious against several types of malignant tumors including pediatric MB. Although in vivo studies provide a promising proof-of-concept for the therapeutic targeting of BMI1 in Group 3 MB, mice that receive treatment eventually succumb to their disease. These results suggest that additional mechanisms may underlie the maintenance of MB and underscore the main obstacle in treating a constantly evolving tumor. After initial preclinical validation of BMI1 inhibitor PTC-596, DNA barcoding clonal tracking technology was leveraged to profile in vivo clonal dynamics of Group 3 MB in response to the established chemoradiotherapy regimen alone and in combination with PTC-596. Comparison of clonal composition of tumors extracted from brains and spines post-treatment revealed the persistence of a small number of clones with the ability to escape therapy and drive subsequent tumor expansion. In order to better understand molecular susceptibilities of MB cells post-BMI1 inhibition, we undertook an in vitro genome-wide CRISPR/Cas9 screening to identify context-specific MB regulatory pathways that could be synergistically targeted along with BMI1. By comparing the results of the in vitro genome wide CRISPR/Cas9 screen to the essential genes in human neural stem cells (hNSCs), we identified several context specific regulators of mTOR, AKT and PLK1 pathways. Combination treatment alongside PTC-596 has demonstrated synergistic efficacy against MB cells with minimal toxicity to hNSCs in vitro and in preclinical in vivo studies. This study provides the foundation for clinical validation of small-molecule inhibitors synergistic with PTC-596 to improve the durability of remissions and extend survival of patients with treatment-refractory Group 3 MB. Citation Format: David Bakhshinyan, Stefan Custers, Ashley Adile, Kevin Brown, Maleeha Qazi, Chirayu Chokshi, Laura Escudero, Yujin Suk, Chitra Venugopal, Jason Moffat, Sheila Singh. Rational development of synergistic therapies alongside BMI1 Inhibition for group 3 medulloblastoma [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A158.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".