PKM2 modulation regulates leukemia cell survival.
Bibliographic record
Abstract
Abstract Acute myeloid leukemia (AML) is characterized by an aberrant metabolic phenotype in which cells rely on aerobic glycolysis (AG) to fuel anabolic processes. Altered glycolytic genes such as pyruvate kinase (PK) are partially responsible for these metabolic changes and are therefore potential novel anti-AML targets. PK is the final rate limiting enzyme in glycolytic metabolism, catalyzing the transfer of an inorganic phosphate from phosphoenolpyruvate to adenosine diphosphate (ADP), yielding one molecule of adenosine triphosphate (ATP) and pyruvate. In AML, the tetrameric and high activity PKM1 isoform of PK is predominately replaced by the dimeric and low activity PKM2 isoform. This conversion toward PKM2 decreases pyruvate production to fuel the tricarboxylic acid (TCA) cycle and instead leads to an accumulation of upstream glycolytic intermediates that are diverted to anabolic pathways to sustain rapid proliferation. In addition to its metabolic role, dimeric PKM2 is a protein kinase and facilitates transcriptional regulation by accumulating in the nucleus and acting as a transcriptional co-activator. To first understand the role of PKM2, protein levels were profiled. PKM2 was significantly increased (70-fold, p<0.01) compared to PKM1 in AML cell lines and is elevated in patient-derived AML cells over normal cells; protein increases were correlated with reduced PKM2 enzymatic activity. To understand the functional role, lentiviral mediated transduction techniques created cell lines with reduced PKM2 (denoted hereafter as PKM2-/-). Genetic inhibition of PKM2 reduced PK activity, cell proliferation and clonogenic growth. Immunocompromised mice injected with PKM2-/- cells lived significantly longer than those injected with endogenous PKM2. Therefore, PKM2 is as a selective and reasonable target for AML therapy. A high throughput screen identified plumbagin (PLB) as a cytotoxic compound (IC50=1.40 – 2.73µM) with specific activity towards PKM2. PLB increases PKM2, but not PKM1, activity and selectively increases PK activity in patient-derived AML cells. To confirm the molecular target, immunoprecipitation and GC-MS analysis detected PLB only in PKM2-rich fractions; PKM2 protein's thermal stability also shifted in the presence of PLB, confirming a molecular interaction. In vitro, PLB selectively reduced viability and clonogenic growth of patient-derived AML cells with no effects on healthy hematopoietic cells. In vivo, treatment of PLB (2.5mg/kg, 3 times per week over five weeks) selectively reduced AML cell engraftment by approximately 85% with no changes in biotoxicity markers; no change in engraftment was noted when mice were injected with normal hematopoietic cells. To reconcile observations that decreased andincreased PKM2 activity imparted anti-AML phenotypes, a direct comparative approach was employed to determine the downstream impact of PKM2 modulation. In vitro studies confirmed that cell death following decreased and increased activity was attributed to disruption of the native oligomeric state that impaired dimeric PKM2 nuclear translocation. By decreasing nuclear translocation, there was a decrease in transcriptional regulation resulting in decreased expression of c-Myc, a well-established oncogenic transcription factor upregulated in AML linked to glutamine dependency and increased proliferation. Indeed, PKM2-/- and PLB-treated cells had reduced nuclear PKM2 accumulation (p<0.05), decreased c-Myc expression (p<0.05), reduced glutaminase (GLS-1) expression (p<0.5) and reduced glutamine uptake(p<0.05). In summary, activation or inhibition of PKM2, through reduced levels of dimeric protein, lead to selective leukemia cell death in vitro and in vivo. Understanding the mechanism by which similar cell fates arise from opposing cellular pathways highlights the pivotal role of PKM2 governing cancer cell survival, and supports PKM2 as a promising therapeutic target in AML as well as PLB as a novel and potent pharmacological agent.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".