Meeting abstracts from the 2024 UCD School of Medicine Summer Student Research Awards (SSRA 2024)
Bibliographic record
Abstract
Acute Myeloid Leukaemia (AML) involves deviations from normal haematopoiesis due to genetic or epigenetic dysregulation.Polycomb Repressive Complex 2 (PRC2), an epigenetic modulator involved in histone trimethylation, is altered in 15% of AML cases, resulting in highly chemoresistant leukaemia with poor prognosis [1].AML cells also exhibit distinct metabolic profiles, including increased dependencies on specific amino acids (AAs).This study investigates the effect of PRC2 loss-of-function on AA metabolism in AML cell lines and aims to identify specific AA dependencies that could highlight novel therapeutic targets in EZH2-mutated AML.We subjected PRC2 haploinsufficient AML cell lines to AA depletion and analyzed them using trypan blue exclusion, alamar blue assays, cell cycle analysis via propidium iodide, and western blotting for apoptotic markers.Compared to wild-type cells, EZH2 loss-of-function cells maintained higher viability, particularly under cysteine depletion.In glutamine depletion, cell cycle analysis showed that most EZH2 lossof-function cells transitioned to and remained in the S phase.These results suggest that EZH2 haploinsufficient cells exhibit enhanced adaptability to specific AA depletions, leading to higher viability.The higher viability in AA depletion may be linked to S-phase progression and arrest, allowing for cell death avoidance.This can potentially translate to a selective advantage in vivo, where EZH2 haploinsufficient cells are more capable of surviving in stressful environments.Additionally, cell cycle S-phase arrest may present a potential targetable vulnerability for treatments affecting DNA replication.Further investigation into changes in AA metabolic pathways caused by EZH2 loss in AML cells is strongly encouraged.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.733 | 0.499 |
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".