Rearrangements in Nucleoporin Family of Genes in Childhood Acute Myeloid Leukemia: A Report from Children Oncology Group and NCI/COG Target AML Initiative
Bibliographic record
Abstract
Abstract Genetic alterations in the Nucleoporin (NUP) family of genes are involved in myeloid leukemogenesis and are associated with poor prognosis. We previously showed that NUP98-NSD1 is prevalent in acute myeloid leukemia (AML) and is highly associated with FLT3-ITD and dismal outcome. As genetic alterations in the NUP family are frequently cryptic by conventional karyotyping, their incidence has been underestimated. The COG/NCI TARGET AML initiative has performed comprehensive genome-wide characterization of diagnostic specimens from 200 pediatric AML cases in order to identify novel genetic lesions with prognostic and therapeutic significance. The interrogation of the whole genome and RNA sequencing data generated by this initiative identified numerous fusion transcripts involving the NUP family of genes, including NUP98-NSD1, NUP98-KDM5A, NUP98-HOXA9, NUP98-HMG3, NUP98-HOXD13, NUP98-PHF23, NUP98-BRWD3, CLINT-NUP98 and DEK-NUP214. All computationally identified NUP fusions were verified by orthogonal methodology and high-throughput screening assay was developed for frequency determination. The verified NUP fusions were screened in children treated on COG AAML0531 and AAML03P1 to define their prevalence, clinical characteristics and association with clinical outcome. The impact of NUP fusions was initially evaluated in patients with cytogenetically normal AML (CN-AML). NUP fusions were observed in 14.5% (35 of 242) patients: NUP98-NSD1 (N=21), DEK-NUP214 (N=3), NUP98-HMG3 (N=3), NUP98-HOXD13 (N=2), NUP98-PHF23 (N=2) and NUP98-KDM5A (N=4). The NUP fusions NUP98-BRWD3, NUP98-HOXA9 and CLINT-NUP98 were not found in CN-AML patients. Demographics and disease characteristics of CN-AML patients with and without NUP fusions were compared. Although patients of Asian descent comprised only 7% of the study population, they harbored significantly higher number of NUP fusions (29% vs 5%, P =0.002). Among those of Asian descent with CN-AML, 35% harbored a NUP fusion. We also noted an inverse association between NUP fusions and African-Americans where NUP fusions were not identified in any of African-American patients (P =0.031). NUP fusions were correlated with other common mutations in AML. NPM1 (9% vs 28%, P =0.007) and CEBPA (6% vs 19%, P =0.06) were rare in patients with NUP fusions, whereas FLT3/ITD (62% vs 34%, P =0.002) and WT1 (32% vs 8%, P <0.001) were significantly more prevalent in patients harboring NUP fusions. Patients with NUP fusions had a significantly lower complete remission (CR) rate (53% vs. 77%, P =0.004) and 5-year event free survival (EFS, 32% vs 53%, P =0.003) than those without N UP fusions. Given the high co-occurrence of NUP fusions and FLT3-ITD, we investigated the prevalence and clinical correlation of NUP fusions in all FLT3-ITD-positive patients. The prevalence of NUP fusions in FLT3-ITD patients was 26% (43 of 164). The CR rate was lower in patients co-expressing the NUP fusion and FLT3-ITD (40% vs 71%, P <0.001) than in those with FLT3-ITD alone. In addition, minimal residual disease (MRD) was more common in patients co-expressing NUP fusions and FLT3-ITD (68% vs 42%, P =0.008) than in those with FLT3-ITD alone. Finally, patients co-expressing FLT3-ITD and NUP fusions had a 5-year EFS of 28% vs 35% (P =0.093) for those with FLT3-ITD only. Next, we investigated the prevalence of NUP fusions in specific cytogenetic groups and found that NUP fusions were rare in patients with core binding factor and were not observed in patients with MLL rearrangements. In this study we report on the discovery, verification and frequency validation of NUP fusions, a new class of genetic alterations in AML. We demonstrate that NUP fusionsare common in pediatric patients and patients with CN-AML harboring NUP fusions have poor outcome and are more likely to have post-induction MRD than those without thesefusions. Furthermore, there is a high co-occurrence of FLT3-ITD and NUP fusions and patients harboring both genetic lesions have a lower CR rate and high post-induction MRD than those with FLT3-ITD alone. NUP fusions define a new subgroup of pediatric AML patients with an overall poor prognosis. AML harboring NUP fusions likely share similar mechanisms of leukemogenesis and targeting these genetic lesions will likely improve outcome in a significant subset of pediatric AML patients. Disclosures No relevant conflicts of interest to declare.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".