Coexpression of human somatostatin receptor-2 (SSTR2) and SSTR3 modulates antiproliferative signaling and apoptosis
Bibliographic record
Abstract
BACKGROUND: Somatostatin (SST) via five Gi coupled receptors namely SSTR1-5 is known to inhibit cell proliferation by cytostatic and cytotoxic mechanisms. Heterodimerization plays a crucial role in modulating the signal transduction pathways of SSTR subtypes. In the present study, we investigated human SSTR2/SSTR3 heterodimerization, internalization, MAPK signaling, cell proliferation and apoptosis in HEK-293 cells in response to SST and specific agonists for SSTR2 and SSTR3. RESULTS: Although in basal conditions, SSTR2 and SSTR3 colocalize at the plasma membrane and exhibit heterodimerization, the cell surface distribution of both receptors decreased upon agonist activation and was accompanied by a parallel increase in intracellular colocalization. Receptors activation by SST and specific agonists significantly decreased cAMP levels in cotransfected cells in comparison to control. Agonist-mediated modulation of pERK1/2 was time and concentration-dependent, and pronounced in serum-deprived conditions. pERK1/2 was inhibited in response to SST; conversely receptor-specific agonist treatment caused inhibition at lower concentration and activation at higher concentration. Strikingly, ERK1/2 phosphorylation was sustained upon prolonged treatment with SST but not with receptor-specific agonists. On the other hand, SST and receptor-specific agonists modulated p38 phosphorylation time-dependently. The receptor activation in cotransfected cells exhibits Gi-dependent inhibition of cell proliferation attributed to increased PARP-1 expression and TUNEL staining, whereas induction of p21 and p27Kip1 suggests a cytostatic effect. CONCLUSION: Our study provides new insights in SSTR2/SSTR3 mediated signaling which might help in better understanding of the molecular interactions involving SSTRs in tumor biology.
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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) | 0.002 | 0.001 |
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".