Abstract A16: Multi-omic analyses in genetically engineered mice reveal distinct and opposite effects of leukemogenic Idh and Tet2 mutations in hematopoietic stem and progenitor cells
Bibliographic record
Abstract
Abstract Mutations in IDH1, IDH2, and TET2 are recurrently observed in myeloid neoplasms. IDH1 and IDH2 encode isocitrate dehydrogenase isoforms, which normally catalyze the conversion of isocitrate to α-ketoglutarate (α-KG). Oncogenic IDH1/2 mutations confer neomorphic activity, leading to the production of D-2-hydroxyglutarate (D-2-HG), a potent inhibitor of α-KG-dependent enzymes which include the TET methylcytosine dioxygenases. Given their mutual exclusivity in myeloid neoplasms, IDH1, IDH2, and TET2 mutations may converge on a common oncogenic mechanism. Contrary to this expectation, we observed that they have distinct, and even opposite, effects on hematopoietic stem and progenitor cells in genetically engineered mice. Endogenous Idh2R172K caused much higher D-2-HG production compared to Idh1R132H and Idh2R140Q. This led to profound alterations in hematopoietic progenitor differentiation and to the development of myelodysplastic syndrome-like disease, with shorter survival compared to Tet2−/- mice. Epigenetic and single-cell transcriptomic analyses revealed that Idh2R172K and Tet2 loss-of-function have divergent and opposite effects on the expression and activity of key hematopoietic and leukemogenic regulators. Notably, chromatin accessibility and transcriptional deregulation in Idh2R172K cells were partially disconnected from DNA methylation alterations. These results highlight unanticipated divergent effects of IDH1/2 and TET2 mutations, which may inform the development of genotype-specific therapies. Citation Format: Jerome Fortin, Ming-Feng Chiang, Cem Meydan, Jonathan Foox, Parameswaran Ramachandran, Julie Leca, Francois Lemonnier, Wanda Y. Li, Miki S. Gams, Takashi Sakamoto, Mandy Chu, Chantal Tobin, Eric Laugesen, Troy M. Robinson, Annick You-Ten, Daniel J. Butler, Thorsten Berger, Mark D. Minden, Ross L. Levine, Cynthia J. Guidos, Ari M. Melnick, Christopher E. Mason, Tak W. Mak. Multi-omic analyses in genetically engineered mice reveal distinct and opposite effects of leukemogenic Idh and Tet2 mutations in hematopoietic stem and progenitor cells [abstract]. In: Proceedings of the AACR Special Conference: Acute Myeloid Leukemia and Myelodysplastic Syndrome; 2023 Jan 23-25; Austin, TX. Philadelphia (PA): AACR; Blood Cancer Discov 2023;4(3_Suppl):Abstract nr A16.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".