Abstract A019 Genetic and epigenetic characterization of <i>NUP98</i>-rearranged leukemia
Bibliographic record
Abstract
Abstract Introduction Pediatric acute myeloid leukemia (AML) with NUP98 rearrangements (NUP98r) is associated with dismal prognoses. NUP98 fusion partners are linked with specific AML subtypes, such as NUP98::NSD1 with myeloblastic AML and NUP98::KDM5A with acute megakaryocytic leukemia (AMKL). Although mostly present in AML, various NUP98r are also found in other malignancies such as T-cell acute lymphoblastic leukemia (T-ALL) and myelodysplastic syndrome (MDS). Despite genomic studies showing associations between FLT3 internal tandem duplications (FLT3-ITD) and WT1 mutations with NUP98::NSD1 AML, the genome-wide mutational status of NUP98r leukemias is to be elucidated. Also, experimental models showed that NUP98 fusion oncoproteins (FOs) regulate gene expression by binding to genomic loci such as HOX genes or MEIS1; however, how different partners contribute to specific diseases remains unstudied. Methods We established a pediatric NUP98r leukemia cohort consisting of 185 samples from 177 cases from our institute, public databases, or collaborators. AML is the dominant disease (n=154), whereas it also included T-ALL (n=18), therapy-related myeloid neoplasms (t-MN, n=4), and MDS (n=1). RNA-sequencing (RNA-seq) data was obtained for all samples, and whole-genome/exome sequencing (WGS/WES) data was obtained from 94 samples. Fusion genes were called from RNA-seq. Somatic alterations were called from both WGS/WES and RNA-seq. The epigenetic status and NUP98 FO-binding of 14 cases were studied using CUT&RUN with antibodies against the N-terminal NUP98, H3K27ac, H3K4me, and K3H27ac. Results Among 177 cases, NUP98::NSD1 was most prevalent (n=92) followed by NUP98::KDM5A (n=45). This cohort also included 11 cases with NUP98::RAP1GDS1 enriched in T-ALL and immature AML, rarely reported in previous NUP98r studies. Genomic profiling confirmed known associations with NUP98::NSD1 AML with FLT3-ITD or WT1, along with novel associations represented by NOTCH1, CCND3, and NRAS mutations with NUP98r T-ALL. Transcriptional analyses with other AML subtypes (n=821) showed NUP98r cases are distributed in five large clusters, where fusions and mutations were associated with specific clusters but not exclusively, suggesting that fusion partners, cooperating alterations, and differentiation states contribute to the disease phenotypes. Epigenetic profiling of 14 cases (NSD1: n=5, KDM5A: n=6, RAP1GDS1: n=3) showed that H3K27ac patterns reflect disease types while H3K27me3 and NUP98-FO binding patterns are intrinsic to fusion partners. NUP98 FOs bound to genes commonly expressed in NUP98r leukemia such as HOXA-B genes or ETV6, whereas NUP98-FOs bound to differentiation-related genes depending on the leukemia subtype (e.g., NUP98::KDM5A binding to the GFI1B loci in AMKL). Conclusion These data suggest that NUP98 FOs specify disease types by directly regulating differentiation-related genes. Further investigation by introducing somatic mutations (e.g., WT1 mutations, RB1 loss) in NUP98r models would reveal its contribution to gene regulation and disease types. Citation Format: Masayuki Umeda, Nicole Michmerhuizen, Ryan Hiltenbrand, Juan M. Barajas, Michael P. Walsh, Guangchun Song, Jing Ma, Tamara Westover, Cristina Mecucci, Danika Di Giacomo, Franco Locatelli, Riccardo Masetti, Salvatore Bertuccio, Martina Pigazzi, Ilaria Iacobucci, Charles G. Mullighan, Jeffery M. Klco. Genetic and epigenetic characterization of NUP98-rearranged leukemia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A019.
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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 | 0.000 | 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) | 0.003 | 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".