Dissociation of Epidermal Growth Factor Receptor and ErbB2 Heterodimers in the Presence of Somatostatin Receptor 5 Modulate Signaling Pathways
Bibliographic record
Abstract
Epidermal growth factor through the stimulation of epidermal growth factor receptor (EGFR) plays a critical role in the activation of MAPKs and phosphatidylinositol-3-protein kinase/AKT cell survival pathways attributed in many pathological conditions. At the cellular level, such functions involve EGFR overactivation and phosphorylation. In the present study, we describe that human embryonic kidney-293 cells transfected with somatostatin (SST) receptor 5 (SSTR5) exhibit inhibition of EGFR phosphorylation and modulate MAPK and phosphatidylinositol-3-protein kinase/AKT cell survival signaling. Furthermore, suppression of EGFR by using small interference RNA and an antagonist (AG1478) potentiates the SST effect via activation of SSTR5 on signaling molecules. In wild-type human embryonic kidney-293 cells, EGFR/ErbB2 exists as constitutive heterodimers. The presence of SSTR5 leads to the dissociation of the heteromeric complex of EGFR/ErbB2 and display preferential heterodimerization between SSTR5 and EGFR in an agonist-dependent manner. These findings highlight a new undiscovered mechanism and potential role of SSTR5 to attenuate the EGFR-mediated signaling pathways involved in tumorigenesis. Our data indicate that the activation and/or overexpression of SST receptors along with the inhibition of EGFR will serve as an important therapeutic approach in the treatment of ErbB-positive tumors.
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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".