Abstract 3784: The metabolic enzyme Hexokinase 2 localizes to the nucleus and regulates stemness in AML through a kinase independent mechanism
Bibliographic record
Abstract
Abstract Leukemia stem cells are responsible for the initiation and recurrence of AML. Cell differentiation requires the coordination of metabolic state and gene expression programs. It is known that metabolic intermediates can serve as cofactors in epigenetic modifications in the nucleus. Whether metabolic enzymes can directly localize to the nucleus, influence gene expression and regulate stemness in AML is unknown. To identify mitochondrial metabolic enzymes that localize to the nucleus of stem cells we analyzed stem and bulk fractions of 8227 leukemia cells, which are arranged in a hierarchy with functionally defined stem cells in the CD34+CD38- fraction. Hexokinase 2 (HK2) was detected in the nuclear fraction of 8227 cells and nuclear HK2 was increased in 8227 stem cells compared to bulk cells. Conversely, the metabolic enzymes aconitase, citrate synthesase, enolase, fumarase, GAPDH, glucose-6-phosphate isomerase, phosphofructokinase, pyruvate kinase and succinate dehydrogenase A were not detectable in the nuclear fraction of either stem or bulk cells. We confirmed that HK2 was present in the nuclear fraction of OCI-AML2, NB4, HL60 and TEX AML cell lines and 7/9 primary patient samples. To determine whether nuclear HK2 was functionally important for AML stem cells, we overexpressed HK2 tagged with a nuclear localizing sequence (PAAKRVKLD). Over-expression of nuclear localized HK2 enhanced clonogenic growth and engraftment into immune deficient mice. Likewise, over-expression of nuclear localized HK2 blocked differentiation after treatment with all-trans retinoic acid (ATRA). Next, we investigated whether the kinase activity of HK2 was necessary for its nuclear effects on AML stemness and differentiation. We generated a kinase dead mutant of HK2 (D209A, D657A) tagged with a nuclear localizing signal (PAAKRVKLD). Over-expression of nuclear-localized kinase dead HK2 exerted a similar phenotype to overexpressed nuclear HK2 without manipulation of the kinase domain as it enhanced clonogenic growth and blocked cell differentiation after ATRA treatment. To understand the mechanism by which nuclear HK2 influenced AML stemness, we identified proteins that interacted with nuclear HK2 using proximity-dependent biotin labeling (BioID) and mass spectrometry. Proteins involved in DNA damage repair and chromatin remodeling were identified, including exonuclease 3′-5′ domain-containing 2 (EXD2), sirtuin 1 (SIRT1), E3 ubiquitin-protein ligase (URB5) and tyrosyl-DNA phosphodiesterase 2 (TDP2). Thus, our data suggest that nuclear HK2 influences DNA repair, which has been linked to stemness and differentiation. In support of this hypothesis, we identified a PAR binding motif in HK2 and over-expression of nuclear HK2 conferred resistance to the PARP inhibitor, olaparib. In summary, HK2 localizes to the nucleus in AML stem cells and maintains stemness. These effects are independent of its kinase activity. Rather, HK2 may regulate DNA damage repair through a PAR dependent mechanism. Thus, we have identified a new role for metabolic enzymes in the regulation of stemness and differentiation. Citation Format: Grace Egan, Geethu E. Thomas, Parasvi S. Patel, Jordan Chin, Aaron Botham, Rose Hurren, Neil MacLean, Razq Hakem, Aaron D. Schimmer. The metabolic enzyme Hexokinase 2 localizes to the nucleus and regulates stemness in AML through a kinase independent mechanism [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3784.
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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 | 0.000 | 0.000 |
| 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) | 0.004 | 0.001 |
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.
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".