Matrix metalloproteinase inhibition protects against junctophilin‐2 proteolysis during doxorubicin‐induced cardiotoxicity
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Treatment of cancer patients with anthracyclines is known to cause dose-dependent cardiotoxicity through several mechanisms including enhanced oxidative stress, ultimately resulting in defective excitation-contraction coupling. Loss of junctophilin-2 (JPH-2), which tethers transverse tubules (T-tubules) to the sarcoplasmic reticulum, is a feature of doxorubicin-induced cardiotoxicity, yet the protease involved in unclear. As activation of matrix metalloproteinase-2 (MMP-2) is known to contribute to doxorubicin-induced cardiotoxicity, we investigated here the role of MMP-2 in JPH-2 proteolysis and defective calcium transients in it. EXPERIMENTAL APPROACH: C57BL/6J mice were treated with doxorubicin for 4 weeks with or without the MMP inhibitor (doxycycline), MMP-2 preferring inhibitor (ONO-4817) or vehicle, and cardiac function was assessed using echocardiography. JPH-2 levels in ventricular extracts were measured. Calcium transients and JPH-2 levels were measured in neonatal rat ventricular cardiomyocytes treated with doxorubicin and ONO-4817. KEY RESULTS: Both MMP inhibitors attenuated doxorubicin-induced cardiac systolic and diastolic dysfunction. Doxorubicin treatment resulted in JPH-2 cleavage in mouse hearts as evidenced by the appearance of lower molecular weight products of 63 and 25 kDa, which was prevented by MMP inhibitors. Loss of JPH-2 and impaired calcium transients were observed in neonatal rat ventricular cardiomyocytes treated with doxorubicin, while ONO-4817 attenuated these changes. In silico analysis predicted cleavage sites between JPH-2 MORN repeats and within its unstructured region. CONCLUSIONS AND IMPLICATIONS: These results reveal that JPH-2 proteolysis is a consequence of MMP-2 activation and highlight the beneficial prophylactic action of two orally available MMP inhibitors in preventing doxorubicin-induced cardiotoxicity.
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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) | 0.001 | 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".