Abstract B017: Aberrant translation of microproteins as a source of new cancer dependencies in medulloblastoma
Bibliographic record
Abstract
Abstract A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation.Dysregulation of ribosome activity not only influences known protein-coding genes, but also unannotated small open reading frames (sORFs) as well.We have recently shown that sORFs may produce functional microproteins in medulloblastoma.Here, we performed an integrative analysis of medulloblastoma patient samples and cell lines.We used ribosome profiling, RNAseq, and mass spectrometry to delineate dysregulation of microprotein production.We employed cell models of MYC overexpression to determine the role of MYC in selective translation of microproteins in medulloblastoma, finding specific associations with upstream open reading frames (uORFs) located in gene leader sequences.We then designed a step-wise approach to define functional microproteins in medulloblastoma through the use of CRISPR/Cas9 screens, saturation mutagenesis, and base editing.We observed distinctive signatures of microprotein bioactivity based on the molecular drivers of medulloblastoma according to disease subtypes.In the Group 3 subtype, we observed an enrichment for bioactive uORFs relative to other disease settings.We then characterized several key microprotein dependencies resulting from uORFs including a molecular mechanism for one candidate, ASNSD1-uORF, in mediating protein-RNA dyssynchrony in Group 3 medulloblastoma.Protein-RNA dyssynchrony is the divergent regulation of protein abundance from RNA abundance, and is a hallmark of Group 3 medulloblastoma.We probed the clinical and therapeutic implications of protein-RNA dyssynchrony and determined that this process may be associated with patterns of drug sensitivity and resistance in medulloblastoma.With this insight, we have now used ASNSD1-uORF to stratify medulloblastoma resistance patterns to inhibitors of RNA transcription.We determine that an interplay between RNA translational control and RNA transcriptional control, while driving resistance in some settings, may also reveal additional drug targets, such as cyclin-dependent kinases.Our findings underscore the fundamental importance of sORF translation in medulloblastoma and provide a rationale to include these ORFs in future studies seeking to define new cancer targets and therapeutic insights. Citation Format: John Prensner, Pratiti Bandopadhayay, Soumik Saha, Leslie Lupien, Seung H. Choi. Aberrant translation of microproteins as a source of new cancer dependencies in medulloblastoma [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 B017.
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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) | 0.002 | 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".