Modulation of p300 acetylation to protect against doxorubicin-induced cardiotoxicity
Bibliographic record
Abstract
Abstract Background Doxorubicin (DOX) is a widely-used anti-neoplastic agent, but the most common adverse reaction to its use is cardiotoxicity(1). DOX acts by producing reactive oxygen species (ROSs) that cause DNA damage(1,2), which activates various proteins, including the tumour suppressor p53 and the acetyltransferase p300. When activated, p300 acetylates and increases the activity of p53 which leads to increased apoptotic activity(3). Cardiotoxicity results because the heart has limited mechanisms to dispose of ROSs(4), and because cardiomyocytes have a low turnover rate(5). Purpose We examined the p300 inhibitor Theracurmin (THR)(6,7) as a candidate to prevent DOX cardiotoxicity using an in-vivo mouse model, and sought to elucidate the underlying molecular mechanisms using in-vitro studies. Methods C57BL/6 mice were pre-treated with THR or vehicle (as control), then administered DOX or vehicle. Cardiac function was evaluated by echocardiography and cardiac catheterization. In vitro studies used cardiac fibroblasts (FBs) and cardiac endothelial cells (ECs) pre-treated with THR, then with DOX, as in the animal studies. Western blotting and rt-qPCR was used to quantify protein and mRNA levels of genes in the p53-p300 pathway or related to apoptosis, oxidative stress, and cell cycle control. Results DOX-treated mice showed significant decreases in left ventricular (LV) ejection fraction (LVEF, p=0.0004), fractional shortening (FS, p=0.0012), and a significant increase in end-systolic volume (ESV, p=0.0004). We also showed a significant decrease in anterior (LVAW;d, p=0.005) and posterior (LVPW;d, p=0.005) wall thickness of the LV in these mice. However, when mice were pre-treated with THR prior to DOX administration, we saw significant increases in LVEF (p=0.045) and LVPW;d (p=0.015), and a significant decrease in ESV (p=0.0047) compared to those that were not pre-treated. In-vitro analyses demonstrated a significant increase in cleaved caspase 3 protein expression in DOX-treated ECs (p=0.007), that was not prevented by THR pre-treatment. In DOX-treated FBs, we saw a reduction in AKT mRNA (p=0.017) and increases in BAX 9p=0.008), P21 (p=0.0001), and GADD45 (0.037) mRNA expression. In DOX-treated ECs, we also saw significant increases in BAX (p=0.015) and P21 (p=0.011) mRNA expression. These changes in mRNA expression were not reversed with THR pre-treatment in either cell type. Conclusion THR pre-treatment successfully mitigated functional deficits and structural deficits associated with DOX cardiotoxicity. In-vitro studies show that THR pre-treatment was not sufficient to significantly prevent changes in key molecular targets associated with apoptosis. Further studies are required to elucidate the mechanism behind the observed functional changes.Abstract OverviewAbstract Results
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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".