Variation in RARG increases susceptibility to doxorubicin-induced cardiotoxicity in patient specific induced pluripotent stem cell-derived cardiomyocytes
Bibliographic record
Abstract
Doxorubicin is a potent anticancer drug used to treat a variety of cancer types. However, its use is limited by doxorubicin-induced cardiotoxicity (DIC). A missense variant in the RARG gene (S427L; rs2229774) has been implicated in susceptibility to DIC in a genome wide association study. The goal of this study was to investigate the functional role of this RARG variant in DIC. We used induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) from patients treated with doxorubicin. iPSC-CMs from individuals who experienced DIC (cases) showed significantly greater sensitivity to doxorubicin compared to iPSC-CMs from doxorubicin-treated individuals who did not develop DIC (controls) in cell viability and optical mapping experiments. Using CRISPR/Cas9, we generated isogenic cell lines that differed only at the RARG locus. Genetic correction of RARG-S427L to wild type resulted in reduced doxorubicin-induced double stranded DNA breaks, reactive oxygen species production, and cell death. Conversely, introduction of RARG-S427L increased susceptibility to doxorubicin. Finally, genetic disruption of the RARG gene resulted in protection from cell death due to doxorubicin treatment. Our findings suggest that the presence of RARG-S427L increases sensitivity to DIC, establishing a direct, causal role for this variant in DIC.
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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) | 0.003 | 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".