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Record W4405044220 · doi:10.1182/blood-2024-211364

Identification of DLK1 As a Novel Therapeutic Target in Down Syndrome Myeloid Leukemia

2024· article· en· W4405044220 on OpenAlexaff
Sonali P. Barwe, Meredith Tavenner, Patrick H. van Berkel, Aimy Sebastian, Rhonda E. Ries, Soheil Meshinchi, Johann Hitzler, Yana Pikman, Anders Kolb, Anilkumar Gopalakrishnapillai

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMyeloid leukemiaGATA1Bone marrowCancer researchLeukemiaMyeloidHaematopoiesisCD34BiologyTranscriptomeDecitabineMedicineGeneImmunologyGene expressionStem cellGeneticsDNA methylation

Abstract

fetched live from OpenAlex

The current standard-of-care for myeloid leukemia associated with Down syndrome (ML-DS) relies on cytotoxic chemotherapy. Although primary ML-DS has favorable prognosis, the 10-20% of patients who develop relapsed leukemia or have refractory disease show a 3-year event-free survival less than 21% (Raghuram et al., 2023). Novel treatment options are needed to improve outcome in these patients with relapsed or refractory disease. The genomic landscape of ML-DS has been characterized by multiple studies (Labuhn et al., 2019; Nikolaev et al., 2013; Sato et al., 2024; Yoshida et al., 2013). In addition to trisomy 21, ML-DS samples possess mutations in the major hematopoietic transcription factor GATA1 and co-operating mutations in three major classes of proteins - cohesin complex components, epigenetic modulators and signaling molecules. However, there are no studies on differential gene expression analysis in ML-DS samples compared to normal bone marrow cells. We have generated ML-DS patient-derived xenograft (PDX) models using primary bone marrow samples from patients with ML-DS (Barwe et al., 2019). We conducted transcriptome analysis using these PDX models (n=4) supplemented with an ML-DS cell line (CMK) to identify differentially expressed genes in ML-DS compared to CD34+ cells isolated from normal bone marrow specimens (n=4). Filtering the differentially expressed genes to shortlist cell surface resident proteins, DLK1 was revealed as one of the top ten targets overexpressed in ML-DS. Analysis of a larger dataset also showed that DLK1 is overexpressed in ML-DS. In this dataset, the mean DLK1 TPM scaled counts in ML-DS bone marrow samples (257.20±73.81, n=77) were significantly greater than the normal bone marrow specimens (2.23±0.24, n=68, p<0.0001). DLK1 expression on the cell surface of ML-DS cell and PDX lines was confirmed by flow cytometry. To determine the role of DLK1 in ML-DS, we generated CMK cells with CRISPR/Cas9 mediated DLK1 knockout. The percentage of EdU positive cells determined by flow cytometry was significantly reduced by 67% and 65% in two distinct knockout clones (P<0.01), indicating that DLK1 indcues ML-DS cell proliferation. When injected in NSG-SGM3 mice, the CMK cells with DLK1 knockout showed minimal engraftment with less than 0.1% human cells in bone marrow, while the mice injected with wild-type CMK cells showed 63% human cell population 5 weeks post cell injection (P<0.001, n=3 each). Consistent with low bone marrow load, the median survival of mice engrafted with DLK1 knockout cells was significantly longer than those with CMK wild-type cells (P<0.05, n=5 each). Thus, our results demonstrate that DLK1 knockout in ML-DS cells suppressed cell proliferation and delayed in vivoengraftment in the bone marrow. We used DLK1-targeting antibody drug conjugate (ADCT-701, referred to as DLK1-ADC) with a DNA intercalating agent pyrrolbenzodiazepine. Isotype control antibody (Iso-ADC) with the same payload was used as control. While DLK1-ADC failed to induce cell death in DLK1 knockout cells, the IC50 for CMK wild-type cells was 0.027 nM. CMK cells with shRNA mediated DLK1 knockdown showed increased IC50 (0.172 nM). Iso-ADC did not have a significant effect on cell viability in any of these lines within the tested concentration range. These results highlight the target-dependent specificity and efficacy of DLK1-ADC in inducing ML-DS cell death. DLK1-ADC also suppressed the viability and colony forming ability of CPCT-0010, a PDX model generated from a patient with refractory ML-DS. In this PDX model in vivo, DLK-1ADC showed a dose-dependent improvement in median survival by 17, 22.5 and 24 days respectively when treated with 0.25, 0.5 or 1 mg/Kg DLK1-ADC i.v. in comparison with Iso-ADC at the same dose (P<0.05). DLK1-ADC dosed twice at 1 mg/Kg also prolonged survival in three distinct PDX models generated using primary cells from patients with refractory ML-DS. Finally, DLK1-ADC, but not Iso-ADC cured 2 of 3 mice injected with a refractory ML-DS PDX model while the third mouse showed an 84-day prolongation of survival compared to that of mice treated with Iso-ADC. Thus, taken together, we have identified DLK1 as a novel therapeutic target for refractory ML-DS and show that targeting DLK1 may be a novel treatment option for patients with refractory ML-DS.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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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Citations0
Published2024
Admission routes1
Has abstractyes

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