IDH2 R172 mutations define a unique subgroup of patients with angioimmunoblastic T-cell lymphoma
Bibliographic record
Abstract
Angioimmunoblastic T-cell lymphoma (AITL) is a common subtype of peripheral T-cell lymphoma (PTCL) with a poor prognosis. We performed targeted resequencing on 92 cases of PTCL and identified frequent mutations affecting RHOA, TET2, DNMT3A, and isocitrate dehydrogenase 2 (IDH2). Although IDH2 mutations are largely confined to AITL, mutations of the other 3 can be found in other types of PTCL, although at lower frequencies. These findings indicate a key role of epigenetic regulation in the pathogenesis of AITL. However, the epigenetic alterations induced by these mutations and their role in AITL pathogenesis are still largely unknown. We correlated mutational status with gene expression and global DNA methylation changes in AITL. Strikingly, AITL cases with IDH2(R172) mutations demonstrated a distinct gene expression signature characterized by downregulation of genes associated with TH1 differentiation (eg, STAT1 and IFNG) and a striking enrichment of an interleukin 12-induced gene signature. Ectopic expression of IDH2(R172K) in the Jurkat cell line and CD4(+) T cells led to markedly increased levels of 2-hydroxyglutarate, histone-3 lysine methylation, and 5-methylcytosine and a decrease of 5-hydroxymethylcytosine. Correspondingly, clinical samples with IDH2 mutations displayed a prominent increase in H3K27me3 and DNA hypermethylation of gene promoters. Integrative analysis of gene expression and promoter methylation revealed recurrently hypermethylated genes involved in T-cell receptor signaling and T-cell differentiation that likely contribute to lymphomagenesis in AITL.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".