The role of mitochondrial proteases in leukemic cells and leukemic stem cells
Bibliographic record
Abstract
Abstract The biological function of most mitochondrial proteases has not been well characterized. Moreover, most of the available information on the normal function of these proteases has been derived from studies in model organisms. Recently, the mitochondrial proteases caseinolytic protease P (CLPP) and neurolysin (NLN) have been identified as therapeutic targets in acute myeloid leukemia (AML). Both proteases are overexpressed in approximately 40% of AML patients. Mechanistically, CLPP and NLN maintain the integrity of the mitochondrial respiratory chain: CLPP cleaves defective respiratory chain proteins, while NLN promotes the formation of respiratory chain supercomplexes. In this review, we highlight the functional consequences of inhibiting and activating mitochondrial proteases and discuss their potential as therapeutic targets in AML. Significance statement Acute myeloid leukemia (AML) is an aggressive hematological malignancy. Despite recent advances and new therapies for this disease, the prognosis for most patients with AML remains poor. Understanding the biology of this disease is important for developing new therapies. Recently, AML cells and stem cells have been shown to have unique mitochondrial properties, which can be therapeutically targeted. One of these properties is an increased reliance on the mitochondrial matrix proteases, caseinolytic protease P and neurolysin. This perspective discusses the effects of genetically and chemically dysregulating mitochondrial proteases in AML. Moreover, this study considers the potential of targeting mitochondrial proteases as a novel therapeutic strategy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".