The IDH2 R172K mutation associated with angioimmunoblastic T-cell lymphoma produces 2HG in T cells and impacts lymphoid development
Bibliographic record
Abstract
Oncogenic isocitrate dehydrogenase (IDH)1 and IDH2 mutations at three hotspot arginine residues cause an enzymatic gain of function that leads to the production and accumulation of the metabolite 2-hydroxyglutarate (2HG), which contributes to the development of a number of malignancies. In the hematopoietic system, mutations in IDH1 at arginine (R) 132 and in IDH2 at R140 and R172 are commonly observed in acute myeloid leukemia, and elevated 2HG is observed in cells and serum. However, in angioimmunoblastic T-cell lymphoma (AITL), mutations are almost exclusively restricted to IDH2 R172, and levels of 2HG have not been comprehensively measured. In this study, we investigate the expression pattern of mutant IDH2 in the AITL tumor microenvironment and measure levels of 2HG in tissue and serum of AITL patients. We find that mutant IDH2 expression is restricted to the malignant T-cell component of AITL, and that 2HG is elevated in tumor tissue and serum of patients. We also investigate the differences between the three hotspot mutation sites in IDH1 and IDH2 using conditional knock-in mouse models. These studies show that in the lymphoid system, mutations in IDH2 at R172 produce high levels of 2HG compared with mutations at the other two sites and that lymphoid development is impaired in these animals. These data provide evidence that IDH2 R172 mutations may be the only variants present in AITL because of their capacity to produce significant amounts of the oncometabolite 2HG in the cell of origin of this disease.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".