Abstract 14257: Ribosome-Profiling Reveals Translational Control of SND1 as a Determinant of Endothelial Homeostasis in a hiPSC Model of Sunitinib-Induced Vascular Dysfunction
Bibliographic record
Abstract
Introduction: The advent of tyrosine kinase inhibitors in cancer therapies has contributed towards the lowered mortality rate from cancer deaths; however, resulting vascular toxicity from such drugs increases the risk for fatal heart disease in cancer survivors. Thus, a better understanding of the mechanisms related to adverse cardiovascular effects is needed to improve mortality rates in cancer survivors. Hypothesis: The objective of this study is to identify previously unrecognized molecular targets that are regulated at a translational level which may contribute to sunitinib-induced vascular toxicity. Methods and Results: A human induced pluripotent stem cell-derived endothelial cells (hiPSC-EC) model of sunitinib-induced vascular dysfunction was established. Ribosome profiling which allows the selective sequencing of translated RNA regions identified Staphylococcal nuclease domain-containing protein 1 (SND1) as a translationally-repressed gene caused by sunitinib exposure. Mechanistically, we identified that sunitinib repressed SND1 by inhibiting mTOR which in turn dephosphorylates 4E-BP. Double-knockdown of 4E-BP1/2 reversed sunitinib-induced repression of SND1. Loss-of-function studies revealed that SND1 inhibition led to endothelial dysfunction as measured by reduced cell viability, impaired angiogenic capability, and reduced wound healing; effects which were blunted in reciprocal SND1 gain-of-function studies in the presence of sunitinib treatment. Furthermore, our results revealed that SND1 transcriptionally regulates UBC13, an E2-conjugating enzyme that mediates K63-linked ubiquitination. Pharmacological inhibition of UBC13 also led to endothelial dysfunction similar to the detrimental effects of sunitinib or SND1 inhibition. Conclusions: Our study demonstrates that translational control of SND1 which acts through UBC13 is a previously unidentified mechanism that can potentially be manipulated for therapeutic benefits to reduce sunitinib-induced vascular toxicity.
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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) | 0.002 | 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".