Abstract 1000: Inactivation of notch1 signaling suppresses FGFR1 knockdown-dependent growth inhibition of MDA-MB-231 breast cancer cells
Bibliographic record
Abstract
Abstract Breast cancer is a very heterogeneous disease as an array of expressed genes can be detected in individual tumors with varying phenotypic cellular morphology. However, despite this heterogeneity, two main histological subgroups predominate, basal-like and luminal-like tumors. Ongoing efforts aim to identify and target additional genetic alterations in breast tumors. One of the widely known and clinical distinctive markers between these tumor phenotypes for example is the transmembrane protein E-cadherin. Factors involved in the repression of E-cadherin are also involved in breast cancer progression. We have recently (Bane et al., Breast Cancer Research and Treatment 117:183-191, 2009) identified a set of differentially expressed and potentially additional distinctive markers between basal- and luminal-like breast tumors that have suggested an important role for Notch and FGF signaling in the development and maintenance of these breast cancer phenotypes. Other studies have also demonstrated gene amplifications in Notch and FGF receptors that can predispose in breast cancer pathophysiology. In the present study we have determined that downregulation of FGFR1 in the basal breast cancer cell line MDA-MB-231 decreased cell proliferation and survival. Interestingly, when Notch1 was also concomitantly repressed with siRNA, normal MDA-MB-231 cell proliferation and survival was restored. The current findings suggest and define a novel interplay between FGFR and Notch signaling in breast cancer patients that may be associated with poor prognosis due to ongoing and sustained basal-like phenotype in breast tumors. 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 1000. doi:10.1158/1538-7445.AM2011-1000
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".