Role of renin-angiotensin system antagonists in the prevention of bevacizumab- and sunitinib-mediated cardiac dysfunction
Bibliographic record
Abstract
Although anticancer systemic therapy agents clearly lead to improved survival in patients with cancer, these can come at the cost of serious complications including cardiotoxicity. Two types of targeted systemic therapies currently in use for colorectal cancer (CRC) and renal cell cancer (RCC), respectively, include the vascular endothelial growth factor inhibitor bevacizumab (BVZ) and the tyrosine kinase inhibitor sunitinib (SNT). Despite the beneficial effects of BVZ and SNT in improving clinical outcomes in the settings of CRC and RCC, there is an increased risk of cardiac dysfunction. The aim of the present study was to determine whether prophylactic administration of renin-angiotensin system (RAS) inhibitors would attenuate the cardiotoxic side effects of BVZ or SNT in a chronic in vivo murine model. A total of 194 wild-type C57Bl/6 male mice received: 1) 0.9% saline, 2) BVZ (10 mg·kg−1·wk−1), or 3) SNT (40 mg·kg−1·day−1) for 4 wk. Within each arm, mice received daily prophylactic treatment with hydralazine (0.05 mg/ml), aliskiren (50 mg/kg), perindopril (4 mg/kg), or valsartan (2 mg/kg). Although hydralazine effectively lowered blood pressure in BVZ- or SNT-treated mice, it did not prevent left ventricular systolic dysfunction. Prophylactic administration of aliskiren, perindopril, or valsartan prevented adverse cardiovascular remodeling in mice treated with either BVZ or SNT. The addition of RAS antagonists also downregulated expression of phosphorylated p38 and Bcl-2-like 19-kDa interacting protein 3 in SNT-treated mice. In our chronic in vivo murine model, RAS antagonists partially attenuated the development of BVZ- or SNT-mediated cardiac dysfunction. Future clinical studies are warranted to investigate the cardioprotective effects of prophylactic treatment with RAS inhibitors in the settings of CRC and RCC. NEW & NOTEWORTHY In the evolving field of cardio-oncology, bevacizumab and sunitinib improve clinical outcomes in the settings of metastatic colorectal cancer and renal cell cancer, respectively. These anticancer drugs, however, are associated with an increased risk of cardiotoxicity. The prophylactic administration of renin-angiotensin system antagonists is partially cardioprotective against bevacizumab- and sunitinib-mediated cardiac dysfunction.
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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) | 0.001 | 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".