Abstract 347: The role of the epithelial-mesenchymal transition in the maintenance of stemness in neural and glioma stem cells
Bibliographic record
Abstract
Abstract Despite advances in treatment, Glioblastoma multiforme (GBM) continues to carry a horrible prognosis with an average overall survival of only 14 months [Stupp et al, 2005]. GBMs are heterogeneous tumors that contain a subpopulation of stem-cell like cells called glioblastoma stem cells (GSCs). GSCs appear to be chemotherapy- and radiation-resistant and are thought to be responsible for GBM progression [Kang et al, 2007; Bao et al, 2006]. More effective GBM therapies must target GSCs, underscoring the importance of understanding GSC biology. Our study examines the epithelial-mesenchymal transition (EMT) and its converse, the mesenchymal-epithelial transition (MET), in the context of GSCs and neural stem cells (NSCs). We hypothesize that the zinc-finger enhancer binding transcription factor (ZEB)/miR-200 feedback loop is relevant in the context of GSCs and is modulated by TGF-β and BMP. We have found that ZEB1 and miR-200 define divergent glioma cell populations: qRT-PCR shows differential expression of ZEB1 and miR-200 in mature human astrocytes, human fetal NSC, and human GSCs (GliNS1). In GSCs, BMP antagonism (noggin) or TGF-β stimulation results in increased ZEB1 expression. Conversely, BMP4 stimulation increases miR-200b/c, while noggin or TGF-β treatment decrease miR-200b/c expression. BrdU proliferation studies show increased proliferation with TGF-β stimulation and decreased proliferation with BMP treatment in three GSC lines. TGF-β signaling also confers an invasive phenotype in GSCs while BMP4 treatment decreases invasion, suggesting a role for TGF-β and BMP parallel to that seen in EMT and MET. Western blot analysis reveals that treatment of GSCs with TGF-β induces phosphorylation of Stat3, which has been shown to be a driver of EMT [Carro MS, 2010]. Interestingly, BMP and TGF-β treatment does not change Sox2 protein expression, suggesting that the GliNS1 GSCs retain their stem cell identity. However, Bmi1 increases with BMP stimulation and decreases with TGF-β treatment, while ID1 increases with BMP treatment, suggesting that the stem-ness in GSCs is modulated by these cytokines. In conclusion, BMP and TGF-β control the ZEB1/miR-200 feedback loop in GSCs and affect cell proliferation and invasive capability. We are continuing studies to determine the relevance of TGF-β and BMP signaling to patients with GBM. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 347. doi:1538-7445.AM2012-347
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".