Abstract P2079: Rbl2 Regulates Cardiac Sensitivity To AnthracyclineChemotherapy
Bibliographic record
Abstract
Anthracycline chemotherapies cause heart failure in a subset of cancer patients. Emerging evidence suggests that genetic factors might contribute to the interindividual variations in cardiac sensitivity to anthracyclines. We previously reported that the anthracycline doxorubicin (DOX) induces cardiotoxicity through activation of cyclin-dependent kinase 2 (CDK2). The aim of this study was to determine whether retinoblastoma-like 2 (RBL2/p130), an emerging CDK2 inhibitor, regulates CDK2 activity and anthracycline sensitivity in the heart. Here, we showed that loss of endogenous Rbl2 increased basal cardiac CDK2 activity. Mice lacking Rbl2 were more sensitive to DOX-induced cardiotoxicity, as evidenced by rapid deterioration of heart function and loss of heart mass. Disruption of Rbl2 exacerbated DOX-induced mitochondrial damage and cardiomyocyte apoptosis. Mechanistically, Rbl2 deficiency enhanced CDK2-dependent activation of forkhead box O1 (FOXO1), leading to upregulation of the pro-apoptotic protein Bim. Inhibition of CDK2 desensitized Rbl2-depleted cardiomyocytes to DOX. In wild-type cardiomyocytes, DOX exposure induced Rbl2 expression in a FOXO1-dependent manner. Importantly, human RBL2 gene single nucleotide polymorphism (rs17800727) was also associated with anthracycline cardiotoxicity in childhood cancer survivors. In conclusion, loss of Rbl2 provokes cardiac CDK2 activation, resulting in increased sensitivity to DOX-induced cardiotoxicity. Rbl2 is an endogenous CDK2 inhibitor in the heart and represses FOXO1-mediated pro-apoptotic gene expression. Our findings suggest that RBL2 could be used as a biomarker to predict the risk of cardiotoxicity in individual patient prior to initiation of anthracycline-based chemotherapy.
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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) | 0.005 | 0.002 |
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".