Somatic gene mutation patterns and burden influence outcomes with enasidenib in relapsed/refractory IDH2-mutated AML
Bibliographic record
Abstract
Limited treatment options are available for patients with relapsed/refractory acute myeloid leukemia (R/R AML). We recently reported results from the phase 3 IDHENTIFY trial (NCT02577406) showing improved response rates and event-free survival with enasidenib monotherapy compared with conventional care regimens (CCR) in heavily pretreated, older patients with late-stage R/R AML bearing IDH2 mutations. Here we investigated the prognostic impact of mutational burden and different co-mutation patterns at study entry within the predominant IDH2 variant subclasses, IDH2 -R140 and IDH2- R172. The prognostic relevance of these variants is well documented in newly diagnosed AML, but data are lacking in R/R AML. In this large R/R AML patient cohort, targeted next-generation sequencing at baseline (screening) revealed distinct co-mutation patterns and mutational burden between subgroups bearing different IDH2 variants: variant IDH2 -R140 was associated with greater mutational burden and was enriched predominantly with poor-risk mutations, including FLT3 , RUNX1 , and NRAS , while variant IDH2 -R172 was associated with lower mutational burden and was preferentially co-mutated with DNMT3A . In multivariable analyses, RAS and RTK pathway mutations were significantly associated with decreased overall survival, after adjusting for treatment arm, IDH2 variant, and mutational burden. Importantly, enasidenib-mediated survival benefit was more pronounced in patients with IDH2 -R172 variants. • Co-mutation profile and mutational burden are distinct for R140/R172 IDH2 variants in IDHENTIFY. • Most common co-mutations were SRSF2 / RUNX1 (R140 cohort) and DNMT3A (R172 cohort). • Survival benefit with enasidenib was more pronounced in IDH2 -R172 variant R/R AML. • RAS/RTK pathway mutations were significantly associated with decreased OS.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".