A Novel Mechanism Underlying the Inhibitory Effects of Trastuzumab on the Growth of HER2-Positive Breast Cancer Cells
Bibliographic record
Abstract
To improve the efficacy of trastuzumab, it is essential to understand its mechanism of action. One of the significant issues that makes it difficult to determine the precise mechanism of trastuzumab action is the formation of various HER receptor dimers in HER2-positive breast cancer cells. So far, studies have focused on the role of HER2-HER3 heterodimers, and little is known regarding EGFR-HER2 heterodimers. Here, we study the role of trastuzumab on the cell signaling and cell proliferation mediated by EGFR-HER2 heterodimers in BT474 and SRBR3 cells. EGF stimulates the formation of both EGFR homodimer and EGFR-HER2 heterodimer. Trastuzumab only binds to HER2, not EGFR. Therefore, any effects of trastuzumab on EGF-induced activation of EGFR, HER2, and downstream signaling proteins, as well as cell proliferation, are through its effects on EGFR-HER2 heterodimers. We show that trastuzumab inhibits EGF-induced cell proliferation and cell cycle progression in BT474 and SKBR3 cells. Interestingly trastuzumab strongly inhibits EGF-induced Akt phosphorylation and slightly inhibits EGF-induced Erk activation, in both BT474 and SKBR3 cells. These data suggest the presence of a novel mechanism that allows trastuzumab to inhibit EGR-induced Akt activation and cell proliferation, without blocking EGF-induced EGFR-HER2 heterodimerization and activation. We show that trastuzumab inhibits EGF-induced lipid raft localization of the EGFR-HER2 heterodimer. Disruption of the lipid raft with MβCD blocks HER2-mediated AKT activation in a similar way to trastuzumab. MβCD and trastuzumab synergically inhibit AKT activation. We conclude that trastuzumab inhibits EGF-induced lipid raft localization of EGFR-HER2 heterodimer, which leads to the inhibition of Akt phosphorylation and cell proliferation, without blocking the formation and phosphorylation of the EGFR-HER2 heterodimer.
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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 | 0.000 |
| 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) | 0.001 | 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".