Abstract 1323: Reciprocal regulation of Stat3 and caveolin-1 in normal fibroblasts and breast carcinoma lines
Bibliographic record
Abstract
Abstract Membrane tyrosine kinases known to activate the signal transducer and activator of transcription-3 (Stat3) concentrate in caveolae, where they are sequestered in an inactive state through binding to the main caveolae protein, caveolin-1 (cav1). We previously demonstrated that cell-to-cell adhesion can cause a dramatic increase in Stat3 activity in cultured cells. Therefore, to examine the effect of cav1 upon Stat3, experiments were conducted at several confluences. Our results indicate that cav-1 downregulation through expression of anti-sense or shRNA constructs or treatment of cells with the pharmacological inhibitor, methyl-cyclo-dextran which destroys caveolae, activates Stat3 as well as Erk1/2, at all densities. Conversely, cav1 overexpression downregulates Stat3 and induces growth retardation or apoptosis in NIH3T3 fibroblasts and in breast cancer lines. In all cases, apoptosis was inhibited by co-expression of the constitutively active form of Stat3, Stat3C. Taken together, these findings point to cav1 as an inhibitor of Stat3 activity. In addition, it was previously demonstrated that cav1 upregulates p53, although the exact mechanism is unclear. Since Stat3 is known to inhibit p53 transcription through promotor binding, these data also point to the possibility that cav1 upregulation may, in fact, activate p53 through Stat3 inhibition. Our results further demonstrate for the first time that, in a feedback loop, Stat3 inhibition results in a dramatic increase in cav1 levels, indicating that Stat3 also downregulates cav1 expression. The above findings reveal the presence of a potent, negative regulatory loop between cav1, p53 and Stat3 that plays a crucial role in cellular survival. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1323. doi:10.1158/1538-7445.AM2011-1323
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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 | 0.001 |
| 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".