Colocalization of somatostatin receptors and epidermal growth factor receptors in breast cancer cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Somatostatin receptor (SSTR) expression is positively correlated with tumor size and inversely correlated with epidermal growth factor receptor (ErbB) levels and tumor differentiation. In the present study, we compared SSTR1-5 and ErbB1-4 mRNA and protein expression in two breast cancer cell lines: MCF-7 (ER+) and MDA-MB-231 (ERalpha-). RESULTS: All five SSTRs and four ErbBs were variably expressed as both cell surface and cytoplasmic proteins. In both cell lines, SSTR4 and SSTR1 were highly expressed, followed by SSTR2 and SSTR5 with SSTR3 being the least expressed subtype, at the protein level. ErbBs were variably expressed with ErbB1 as the predominant subtype in both cell lines. ErbB1 is followed by ErbB3, ErbB2 and ErbB4 in MCF-7 at both the protein and mRNA levels. In MDA-MB-231 cells, ErbB1 is followed by ErbB2, ErbB4 and ErbB3. Our results indicate significant correlations at the level of mRNA and protein expression in a cell and receptor-specific manner. Using indirect immunofluorescence, we found that, in MCF-7 cells, SSTR5 was the most prominent subtype coexpressed with ErbBs followed by SSTR3, SSTR4, SSTR1 and SSTR2, respectively. In MDA-MB-231 cells, SSTR1 colocalized strongly with ErbBs followed by SSTR5, SSTR4, SSTR3 and SSTR2. ErbBs displayed higher levels of colocalization amongst themselves in MCF-7 cells than in MDA-MB-231 cells. CONCLUSION: These findings may explain the poor response to endocrine therapy in ER-cancer. Differential distribution of SSTR subtypes with ErbBs in breast cancer cells in a receptor-specific manner may be considered as a novel diagnosis for breast tumors.
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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) | 0.003 | 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