Unraveling lipid metabolism for acute myeloid leukemia therapy
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of this review is to highlight the importance of lipids' intricate and interwoven role in mediating diverse acute myeloid leukemia (AML) processes, as well as potentially novel lipid targeting strategies. This review will focus on new studies of lipid metabolism in human leukemia, particularly highlighting work in leukemic stem cells (LSCs), where lipids were assessed directly as a metabolite. RECENT FINDINGS: Lipid metabolism is essential to support LSC function and AML survival through diverse mechanisms including supporting energy production, membrane composition, signaling pathways, and ferroptosis. Recent work has highlighted the role of lipid rewiring in metabolic plasticity which can underlie therapy response, the impact of cellular and genetic heterogeneity in AML on lipid metabolism, and the discovery of noncanonical roles of lipid related proteins in AML. SUMMARY: Recent findings around lipid metabolism clearly demonstrates their importance to our understanding and therapeutic targeting of AML. We have only begun to unravel the regulation and utilization of lipids in this disease. Further, understanding the layered dynamics of lipid homeostasis could provide novel opportunities to target lipid metabolism in AML and LSCs with the potential of improving outcomes for patients with AML.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".