The E3 ubiquitin ligase Herc1 modulates the response to nucleoside analogs in acute myeloid leukemia
Bibliographic record
Abstract
ABSTRACT: For several decades, induction therapy with nucleoside analogs, in particular cytarabine (Ara-C) and, to a lesser extent, fludarabine, has been the standard of care for patients diagnosed with acute myeloid leukemia (AML). However, the antitumor efficacy of nucleoside analogs is often limited by intrinsic and acquired drug resistance, thereby leading to poor therapeutic response and suboptimal clinical outcomes. In this study, we used genome-wide CRISPR-based pharmacogenomic screening to map the genetic factors that modulate the response to nucleoside analogs in AML and identified the E3 ubiquitin ligase, Herc1, as a key modulator of Ara-C response in mouse AML models driven by the KMT2A/MLLT3 fusion or by the constitutive coexpression of Hoxa9 and Meis1, both in vitro and in vivo. Loss of HERC1 enhanced nucleoside analog-induced cell death in both murine and human AML cell lines by compromising cell cycle progression. In-depth proteomic analysis and subsequent validation identified deoxycytidine kinase as a novel target of Herc1 in both mouse AML models. We observed that HERC1 is overexpressed in AML when compared with other cancer types and that higher HERC1 expression was associated with shorter overall survival in patients with AML in the The Cancer Gene Atlas program (TCGA) and BEAT-AML cohorts. Collectively, this study highlights the importance of HERC1 in the response of AML cells to nucleoside analogs, thereby establishing this E3 ubiquitin ligase as a novel predictive biomarker and potential therapeutic target for the treatment of AML.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".