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Record W2084296747 · doi:10.1158/1538-7445.am2012-347

Abstract 347: The role of the epithelial-mesenchymal transition in the maintenance of stemness in neural and glioma stem cells

2012· article· en· W2084296747 on OpenAlexaff
Nestor A. Fernandez, Megan Wu, Sunit Das

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsNogginCancer researchStem cellBiologyGliomaEpithelial–mesenchymal transitionMesenchymal stem cellNeural stem cellCancer stem cellContext (archaeology)Cell biologyBone morphogenetic proteinCancerGeneticsMetastasis

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.024
GPT teacher head0.319
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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