In desmoid-type fibromatosis cells sorafenib induces ferroptosis and apoptosis, which are enhanced by autophagy inhibition
Bibliographic record
Abstract
INTRODUCTION: Desmoid-type fibromatosis (DTF) is a rare, soft tissue tumour. Sorafenib, a multikinase inhibitor, has demonstrated antitumour efficacy in DTF patients. Little is known about the underlying molecular mechanisms, which are crucial to know to further optimize systemic treatments. Here we investigated the molecular effects of sorafenib exposure on DTF and stromal cells, with an emphasis on cell death mechanisms. MATERIAL AND METHODS: DTF primary cell cultures, with known CTNNB1 status, and primary stromal cell cultures, derived from DTF tissue, were exposed to clinically relevant concentrations of sorafenib in the presence or absence of inhibitors of ferroptosis, apoptosis and autophagy. Cell viability was determined after 24 and 48 h using MTT assays. Annexin V/PI staining, lipid peroxidation analysis and immunoblotting were performed to assess apoptosis, ferroptosis and autophagy. RESULTS: Exposure to sorafenib caused a significant, concentration- and time-dependent decrease in cell viability in all primary DTF and stromal cell cultures. Inhibitors of ferroptosis and apoptosis protected against sorafenib-mediated cytotoxicity implicating that both cell death mechanisms are activated. Annexin V/PI stainings and lipid peroxidation analyses confirmed induction of apoptosis and ferroptosis, respectively. Autophagy inhibition enhanced the cytotoxic effect of sorafenib and led to a stronger induction of apoptosis and ferroptosis. CONCLUSION: This study identified ferroptosis and apoptosis as mechanisms for the sorafenib induced cell death in DTF cells as well as stromal cells. Furthermore, autophagy inhibition enhanced the cytotoxic effects of sorafenib. Knowledge of the mechanisms by which sorafenib affects DTF at a cellular level may help to optimize its clinical efficacy and mitigate toxic effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".