Non-mitogenic FGF2 protects cardiomyocytes from acute doxorubicin-induced toxicity independently of the protein kinase CK2/heme oxygenase-1 pathway
Bibliographic record
Abstract
Doxorubicin (Dox)-induced cardiotoxicity, a limiting factor in the use of Dox to treat cancer, can be mitigated by the mitogenic factor FGF2 in vitro, via a heme oxygenase 1 (HO-1)-dependent pathway. HO-1 upregulation was reported to require protein kinase CK2 activity. We show that a mutant non-mitogenic FGF2 (S117A-FGF2), which does not activate CK2, is cardioprotective against acute cardiac ischemic injury. We now investigate the potential of S117A-FGF2 to protect cardiomyocytes against acute Dox injury and decrease Dox-induced upregulation of oxidized phospholipids. The roles of CK2 and HO-1 in cardiomyocyte protection are also addressed.Rat neonatal cardiomyocyte cultures were used as an established in vitro model of acute Dox toxicity. Pretreatment with S117A-FGF2 protected against Dox-induced: oxidative stress; upregulation of fragmented and non-fragmented oxidized phosphatidylcholine species, measured by LC/MS/MS; and cardiomyocyte injury and cell death measured by LDH release and a live-dead assay. CK2 inhibitors (TBB and Ellagic acid), did not affect protection by S117A-FGF2 but prevented protection by mitogenic FGF2. Furthermore, protection by S117A-FGF2, unlike that of FGF2, was not prevented by HO-1 inhibitors and S117A-FGF2 did not upregulate HO-1. Protection by S117A-FGF2 required the activity of FGF receptor 1 and ERK.We conclude that mitogenic and non-mitogenic FGF2 protect from acute Dox toxicity by common (FGFR1) and distinct, CK2/HO-1- dependent or CK2/HO-1-independent (respectively), pathways. Non-mitogenic FGF2 merits further consideration as a preventative treatment against Dox 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 | 0.000 |
| 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".