An epigenetic increase in mitochondrial fission by MiD49 and MiD51 regulates the cell cycle in cancer: <i>Diagnostic and therapeutic implications</i>
Bibliographic record
Abstract
Abstract Excessive proliferation and apoptosis‐resistance are hallmarks of cancer. Increased dynamin‐related protein 1 (Drp1)‐mediated mitochondrial fission is one of the mediators of this phenotype. Mitochondrial fission that accompanies the nuclear division is called mitotic fission and occurs when activated Drp1 binds partner proteins on the outer mitochondrial membrane. We examine the role of Drp1‐binding partners, mitochondrial dynamics protein of 49 and 51 kDa (MiD49 and MiD51), as drivers of cell proliferation and apoptosis‐resistance in non‐small cell lung cancer (NSCLC) and invasive breast carcinoma (IBC). We also evaluate whether inhibiting MiDs can be therapeutically exploited to regress cancer. We show that MiD levels are pathologically elevated in NSCLC and IBC by an epigenetic mechanism (decreased microRNA‐34a‐3p expression). MiDs silencing causes cell cycle arrest through (a) increased expression of cell cycle inhibitors, p27 Kip1 and p21 Waf1 , (b) inhibition of Drp1, and (c) inhibition of the Akt‐mTOR‐p70S6K pathway. Silencing MiDs leads to mitochondrial fusion, cell cycle arrest, increased apoptosis, and tumor regression in a xenotransplant NSCLC model. There are positive correlations between MiD expression and tumor size and grade in breast cancer patients and inverse correlations with survival in NSCLC patients. The microRNA‐34a‐3p‐MiDs axis is important to cancer pathogenesis and constitutes a new therapeutic target.
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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) | 0.002 | 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 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".