CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify <i>KDM3B</i> as a Genotype-specific Vulnerability in <i>IDH2</i> - and <i>TET2</i> -mutant Cells
Bibliographic record
Abstract
Clonal hematopoiesis (CH) is a common premalignant state in the blood and confers an increased risk of blood cancers and all-cause mortality. Identification of therapeutic targets in CH has been hindered by the lack of an ex vivo platform amenable for studying primary hematopoietic stem and progenitor cells (HSPCs). Here, we utilize an ex vivo co-culture system of HSPCs with bone marrow endothelial cells to perform CRISPR/Cas9 screens in mutant HSPCs. Our data reveal that loss of the histone demethylase family members Kdm3b and Jmjd1c specifically reduces the fitness of Idh2- and Tet2-mutant HSPCs. Kdm3b loss in mutant cells leads to decreased expression of critical cytokine receptors including Mpl, rendering mutant HSPCs preferentially susceptible to inhibition of downstream JAK2 signaling. Our study nominates an epigenetic regulator and an epigenetically regulated receptor signaling pathway as genotype-specific therapeutic targets and provides a scalable platform to identify genetic dependencies in mutant HSPCs. Significance: Given the broad prevalence, comorbidities, and risk of malignant transformation associated with CH, there is an unmet need to identify therapeutic targets. We develop an ex vivo platform to perform CRISPR/Cas9 screens in primary HSPCs. We identify KDM3B and downstream signaling components as genotype-specific dependencies in CH and myeloid malignancies. See related commentary by Khabusheva and Goodell, p. 1768.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".