Abstract 3173: The role of the Src/Stat3 axis in autocrine HGF signalling in invasive human breast cancer
Bibliographic record
Abstract
Abstract Recent studies have shown that the proto-oncogene Met is frequently over-expressed in breast cancers, particularly the highly aggressive basal-like subtype. The Elliott lab has previously shown co-expression of HGF and Met in invasive human breast cancers, but not in normal breast epithelium (CJPP 80:91-102, 2002), and a novel activating role of Src and Stat3 on HGF transcription and transformation of breast epithelial cells (Oncogene 25:2773-84, 2006). Together, these findings suggest that the Src/Stat3 axis promotes autocrine HGF/Met signalling, and thereby contributes to invasion and metastasis in breast cancer. To assess the role of Src/Stat3 activation and autocrine HGF/Met signaling in breast metastasis, we have used the human breast carcinoma cell line MDA-MB-231, which exhibits basal-like characteristics. To directly assess the role of Src, we have expressed an activated Src mutant in MDA-MB-231 cells (MDA-Src). Using western blotting analysis, we observed increased levels of active Stat3 (pY705) and Met (pY1234/1235), as well as increased total Stat3, HGF and Met proteins in MDA-Src cells, compared to MDA-MB-231 cells. This finding supports a role of Src in activation of Stat3 and HGF/Met signalling in MDA-MB-231 cells. Treatment of the above cell lines with Dasatinib, an ATP-competitive inhibitor of Src family kinases, resulted in a decrease in the activity of Src and Met, while the levels of activated Stat3 (pY705) and HGF protein were unchanged. In contrast, treatment with CPA7, an inhibitor of Stat3-mediated gene transcription, produced a marked decrease in total HGF protein in addition to decreased Src and Met activity. These results suggest that Src inhibition alone is not sufficient to inhibit the Stat3-dependent expression of HGF in MDA-MB-231 cells, and that inhibition of Stat3 gene transcription rather than its activation is key to the inhibition of the HGF/Met autocrine loop. We are currently performing immunohistochemical analyses of Src/Stat3 and HGF/Met expression on a cohort of human breast cancer tissues (n=59). Preliminary results have shown increased expression and nuclear localization of active Stat3 in breast tumours compared to normal mammoplasty tissues, which is concurrent with HGF expression. These findings implicate a role of the Src/Stat3 axis in regulating autocrine HGF/Met signaling in a human breast cancer cell line model, and may lead to a predictive marker for targeting of breast cancer subtypes which may exploit this pathway. (Supported by CBCRA and CIHR). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3173.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".