HER2 expression defines unique requirements for flotillin and c-Src in EGFR signaling
Bibliographic record
Abstract
The epidermal growth factor receptor (EGFR) controls many cellular functions. Upon binding its ligand, the receptor undergoes dimerization, phosphorylation and activation of signals including the phosphoinositide-3-kinase (PI3K)-Akt pathway. Although some studies have indicated that EGFR signaling may be controlled by signal enrichment within various membrane rafts, such as flotillin nanodomains, others have found a limited effect of disruption of these nanodomains on EGFR signaling, suggesting that specific factors may define context-specific control of EGFR signaling. Ligand-bound EGFR can homodimerize or instead undergo heterodimerization with the related receptor HER2 (also known as ERBB2) when the latter is expressed. We examined how EGFR signaling in the presence of HER2 distinctly requires flotillin nanodomains. Induction of HER2 expression altered EGFR signaling duration, which is consistent with EGFR-HER2 heterodimer formation. EGFR and c-Src (also known as SRC) localized within plasma membrane structures demarked by flotillin-1 more prominently in HER2-expressing cells. Consistently, HER2-expressing cells, but not cells lacking HER2, were dependent on flotillin-1 and c-Src for EGFR signaling leading to Akt activation and cell proliferation. Hence, HER2 expression establishes a requirement for flotillin membrane rafts and c-Src in EGFR signaling.
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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) | 0.001 | 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 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".