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Record W2984527456 · doi:10.1182/blood-2019-123709

Targeted Inhibition of the NUP98-NSD1 Fusion Oncogene in AML

2019· article· en· W2984527456 on OpenAlexaff
Sagarajit Mohanty, Nidhi Jyotsana, Amit Sharma, Basem Othman, Arnold Kloos, Madhvi Mandhania, Renate Schottmann, Euan Ramsay, H.-P. Vornlocher, Arnold Ganser, Felicitas Thol, Michael Heuser

Bibliographic record

VenueBlood · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsPrecision Nanosystems (Canada)
Fundersnot available
KeywordsCancer researchSuraminTransplantationMedicineChemistryMolecular biologyBiologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

Background: NUP98-NSD1 positive AML is a poor prognostic subgroup within pediatric and adult AML (Thol et al., 2013). However, targeted therapeutics for these AML patients are not available to date. As a result of the NUP98-NSD1 fusion, NSD1 causes H3K36 hypermethylation of HOXA genes, which contributes to myeloid progenitor cell immortalization and results in AML (Wang et al., 2007). Therefore, we hypothesized that inhibition of the methyltransferase activity of NSD1 could be an effective treatment strategy for NUP98-NSD1 AML patients. Here, we assessed the efficacy of NSD1 inhibitor suramin and NUP98-NSD1-directed siRNA-containing lipid nanoparticles (LNP) in a preclinical patient-derived xenograft (PDX) model of NUP98-NSD1 leukemia. Methods: A NUP98-NSD1 positive AML patient was screened through nested PCR and Sanger sequencing. Bone marrow cells from this patient were serially transplanted into NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ) mice to establish a NUP98-NSD1 PDX model. During serial transplantations, an alternative NUP98-NSD1 fusion gene appeared. Flow-cytometry was used to check the engraftment and immunophenotype of engrafted cells. Effective siRNAs against each of the two fusion genes were developed. The microfluidic mixing technology, Nanoassemblr was used to package siRNA into LNPs and the Zetasizer was used to characterize them. Fifteen days after transplantation, suramin and solvent treatment were initiated in 9 mice per group with 10 mg/kg suramin (2 days/week for 10 weeks). For LNP treatment, treatment was initiated 3 weeks after transplantation with a once daily dose of 2.5 mg/kg on days 1-3 and then every third day thereafter for a total of 17 injections. Results: Besides the NUP98-NSD1 translocation, our patient had a FLT3-ITD mutation and a normal karyotype. In our PDX model, the engraftment of human leukemia cells reached up to 90% after ten weeks of transplantation. In successive transplantations up to the 6th generation, the NUP98-NSD1 fusion was confirmed in leukemic cells, supporting the importance of the fusion for leukemia development and stability of the model. In later transplantations, a minor clone of NUP98-NSD1 was identified. A high blast count, high WBC count, increased spleen weight, and a low hemoglobin and platelet count at death demonstrated the development of acute leukemia. High expression of myeloid markers (e.g. CD33, 99%, N=9) and negligible expression of lymphoid markers (CD3, 2%; CD19, 2%; N=9) confirmed acute myeloid leukemia. In the suramin treatment study, the mean human leukemic cell engraftment was similar between the control and treatment groups at the start of treatment (0.51%, N=9 and 0.71%, N=9, respectively), but was lower in suramin treated mice after 4 and 8 weeks of treatment (4 weeks: CTRL, 4,8%; suramin, 2,66%, P=0.1; 8 weeks: CTRL, 87,3%; suramin: 66,5%, P=0.016). No significant effect was seen on the immunophenotype of suramin and control treated leukemia cells. Suramin treatment significantly prolonged the median survival of mice compared to control mice (126 vs 114 days after transplantation, P=0.008). To establish the siRNA-LNP treatment, we identified one siRNA against each NUP98-NSD1 clone that reduced expression levels by 78% and 89.5% in the major and minor clones, respectively. The effective siRNAs were modified to increase their in vivo stability and were packaged into LNPs and used in vivo. We started the treatment when the engraftment was similar in both control LNP and NUP98-NSD1 LNP groups (0.93%, N=7 and 1.25%, N=6, respectively). After 3 weeks of treatment, LNP uptake was 99.3% and 99.2% in the CTRL LNP and NUP98-NSD1 LNP groups, respectively. The mean engraftment was lower in NUP98-NSD1 LNP mice after 5 and 8 weeks of treatment (5 weeks: CTRL LNP, 15%; NUP98-NSD1 LNP, 4.6%, P= 0.08; 8 weeks: CTRL LNP, 94.8%; NUP98-NSD1 LNP, 55.83%, P=0.007). Importantly, the NUP98-NSD1 siRNA-LNP treated mice showed a significant survival benefit compared to CTRL siRNA-LNP treated mice (106 vs 82 days after transplantation, P=0.02). Conclusions: In summary, our findings demonstrate that targeted inhibition of NUP98-NSD1 either through siRNA-LNP or suramin delays leukemia development in vivo and prolongs the survival of mice carrying a NUP98-NSD1 positive AML. Our results provide the rationale for the evaluation of NSD1 methyltransferase inhibitors and siRNA-LNP formulations in NUP98-NSD1 positive AML. Disclosures Heuser: Bayer Pharma AG, Berlin: Research Funding; Synimmune: Research Funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.258
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations3
Published2019
Admission routes1
Has abstractyes

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