Abstract 6028: Cancer-selective metabolic vulnerabilities in MYC-amplified medulloblastoma
Bibliographic record
Abstract
Abstract [Background] Medulloblastoma (MB) is the most frequently diagnosed malignant pediatric brain tumor. Multiple integrated genomic analyses have been used to stratify MB into four molecular subgroups, each unique in its gene expression profile, clinical characteristics, and prognosis. MYC-driven group 3 MB (G3MB) tumors are poorly understood entities, defined by metastasis down the leptomeninges, disease recurrence and particularly poor survival. There is hence an urgent need for a more thorough molecular understanding of G3MB, particularly at recurrence, in order to develop more effective therapeutic modalities that will improve the durability of remission. [Methods] We previously developed a therapy-adapted mouse model of G3MB disease progression from xenoengraftment through treatment-induced minimal residual disease until eventual relapse in the brain and spine compartments. Temporal transcriptomic profiling of tumor tissue at each stage revealed an enrichment of several metabolic pathways at recurrence. Here we mapped further functional insight into the G3MB metabologenomic landscape by performing a genome-wide loss-of-function CRISPR-Cas9 genetic screen in patient-derived G3MB cells, which we cross-referenced with screens performed in human neural stem cells (NSCs), the proposed cell- of-origin for G3MB. [Results] By examining G3MB context-specific gene ontologies, we discovered differential essentiality of several metabolic processes exclusively in G3MB. In tandem, mass spectrometry-based global metabolomic profiling shows dysregulation of several metabolic pathways in in G3MB tumor cells in comparison to NSC, including the enrichment of de novo pyrimidine biosynthesis and depletion of salvage pyrimidine intermediates. We investigated a lead hit from our screen, DHODH (dihydroorotate dehydrogenase), which facilitates de novo pyrimidine biosynthesis. Our data demonstrate that genetic or pharmacological inhibition of DHODH selectively targets G3MB brain tumor initiating cell (BTIC) activity while sparing normal NSC, by disrupting hallmark MYC activity. We further show that MYC-amplified G3MB tumors harbor subgroup-specific transcriptomic signatures that delineate enrichment of de novo pyrimidine biosynthesis. [Significance] Despite clear evidence favoring an altered metabolic landscape in MYC-driven cancers, there have been only a few reports into the role of metabolic reprogramming in MYC-amplified G3MB. Given the paucity of treatment options for patients with recurrent G3MB, this study has the potential for a significant impact on the field of pediatric oncology. Translation of therapies that target unique metabolic vulnerabilities exclusive to G3MB may lead to more durable cures and radical improvements in quality of life for survivors. Citation Format: William D. Gwynne, Yujin Suk Suk, Stefan Custers, Nicholas Mikolajewicz, Jeremy K. Chan, Zsolt Zador, Shawn C. Chafe, Kui Zhai, Laura Escudero, Cunjie Zhang, Olga Zaslaver, Chirayu Chokshi, Muhammad Vaseem Shaikh, David Bakhshinyan, Ian Burns, Iqra Chaudhry, Omri Nachmani, Daniel Mobilio, William T. Maich, Patricia Mero, Kevin R. Brown, Andrew T. Quaile, Chitra Venugopal, Jason Moffat, J Rafael Montenegro-Burke, Sheila K. Singh. Cancer-selective metabolic vulnerabilities in MYC-amplified medulloblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6028.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".