The small GTPase ADP-Ribosylation Factor 1 mediates the sensitivity of triple negative breast cancer cells to EGFR tyrosine kinase inhibitors
Bibliographic record
Abstract
The clinical use of EGFR-targeted therapy, in triple negative breast cancer patients, has been limited by the development of resistance to these drugs. Although activated signaling molecules contribute to this process, the molecular mechanisms remain relatively unknown. We have previously reported that the small GTPase ADP-Ribosylation Factor 1 (ARF1) is highly expressed in invasive breast cancer cells and acts as a molecular switch to activate EGF-mediated responses. In this study, we aimed at defining whether the high expression of ARF1 limits sensitivity of these tumor cells to EGFR inhibitors, such as gefitinib. Here, we show that the knock down of ARF1 expression or activity decreased the dose and latency time required by tyrosine kinase inhibitors to induce cell death. This may be explained by the observation that the depletion of ARF1 suppressed gefitinib-mediated activation of key mediators of survival such as ERK1/2, AKT and Src, while enhancing cascades leading to apoptosis such as the p38MAPK and JNK pathways, modifying the Bax/Bcl2 ratio and cytochrome c release. In addition, inhibiting ARF1 expression and activation also results in an increase in gefitinib-mediated EGFR internalization and degradation further limiting the ability of this receptor to promote its effects. Interestingly, we observed that gefitinib treatment resulted in the enhanced activation of ARF1 by promoting its recruitment to the receptor AXL, an important mediator of EGFR inhibition suggesting that ARF1 may promote its pro-survival effects by coupling to alternative mitogenic receptors in conditions where the EGFR is inhibited. Together our results uncover a new role for ARF1 in mediating the sensitivity to EGFR inhibition and thus suggest that limiting the activation of this GTPase could improve the therapeutic efficacy of EGFR inhibitors.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".