MFF Regulation of Mitochondrial Cell Death Is a Therapeutic Target in Cancer
Bibliographic record
Abstract
Abstract The regulators of mitochondrial cell death in cancer have remained elusive, hampering the development of new therapies. Here, we showed that protein isoforms of mitochondrial fission factor (MFF1 and MFF2), a molecule that controls mitochondrial size and shape, that is, mitochondrial dynamics, were overexpressed in patients with non–small cell lung cancer and formed homo- and heterodimeric complexes with the voltage-dependent anion channel-1 (VDAC1), a key regulator of mitochondrial outer membrane permeability. MFF inserted into the interior hole of the VDAC1 ring using Arg225, Arg236, and Gln241 as key contact sites. A cell-permeable MFF Ser223-Leu243 d-enantiomeric peptidomimetic disrupted the MFF–VDAC1 complex, acutely depolarized mitochondria, and triggered cell death in heterogeneous tumor types, including drug-resistant melanoma, but had no effect on normal cells. In preclinical models, treatment with the MFF peptidomimetic was well-tolerated and demonstrated anticancer activity in patient-derived xenografts, primary breast and lung adenocarcinoma 3D organoids, and glioblastoma neurospheres. These data identify the MFF–VDAC1 complex as a novel regulator of mitochondrial cell death and an actionable therapeutic target in cancer. Significance: These findings describe mitochondrial fission regulation using a peptidomimetic agent that disturbs the MFF–VDAC complex and displays anticancer activity in multiple tumor models. See related commentary by Rao, p. 6074
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".