Inhibition of tumor promoting signals by activation of SSTR2 and opioid receptors in human breast cancer cells
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Somatostatin receptors (SSTRs) and opioid receptors (ORs) belong to the superfamily of G-protein coupled receptors and function as negative regulators of cell proliferation in breast cancer. In the present study, we determined the changes in SSTR subtype 2 (SSTR2) and μ, δ and κ-ORs expression, signaling cascades and apoptosis in three different breast cancer cells namely MCF-7, MDA-MB231 and T47D. METHODS: Immunocytochemistry and western blot analysis were employed to study the colocalization and changes in MAPKs (ERK1/2 and p38), cell survival pathway (PI3K/AKT) and tumor suppressor proteins (PTEN and p53) in breast cancer cell lines. The nature of cell death upon activation of SSTR2 or OR was analysed using flow cytometry analysis. RESULTS: The activation of SSTR2 and ORs modulate MAPKs (ERK1/2 and p38) in cell dependent and possibly estrogen receptor (ER) dependent manner. The activation of tumor suppressor proteins phosphatase and tensin homolog (PTEN) and p53 antagonized the PI3K/AKT cell survival pathway. Flow cytometry analyses reveal increased necrosis as opposed to apoptosis in MCF-7 and T47D cells when compared to ER negative MDA-MB231 cells. Furthermore, receptor and agonist dependent expression of ORs in SSTR2 immunoprecipitate suggest that SSTR2 and ORs might interact as heterodimers and inhibit epidermal growth factor receptor phosphorylation. CONCLUSION: Taken together, findings indicate a new role for SSTR2/ORs in modulation of signaling pathways involved in cancer progression and provide novel therapeutic approaches in breast cancer treatment.
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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 | 0.000 | 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 | 0.000 |
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 it