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Record W2538756717 · doi:10.1038/onc.2016.235

CD133+ brain tumor-initiating cells are dependent on STAT3 signaling to drive medulloblastoma recurrence

2016· article· en· W2538756717 on OpenAlexafffund
Neha Garg, David Bakhshinyan, Chitra Venugopal, Sujeivan Mahendram, David A. Rosa, Thusyanth Vijayakumar, Branavan Manoranjan, Robin Hallett, Nicole McFarlane, Kathleen H. Delaney, Jacek M. Kwiecień, Carolynn C. Arpin, P-S Lai, Rodolfo F. Gómez‐Biagi, Ahmed M. Ali, Elvin D. de Araujo, Olufemi Ajani, John A. Hassell, Patrick T. Gunning, Sheila K. Singh

Bibliographic record

VenueOncogene · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of TorontoMcMaster University
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health ResearchAlberta InnovatesStem Cell NetworkMcMaster University
KeywordsMedulloblastomaSTAT3BiologyCarcinogenesisCancer researchRadiation therapyMetastasisChemotherapyBrain tumorTumor initiationBrain metastasisIn vivoSignal transductionOncologyInternal medicineCancerMedicinePathologyGenetics

Abstract

fetched live from OpenAlex

Medulloblastoma (MB), the most common malignant paediatric brain tumor, is currently treated using a combination of surgery, craniospinal radiotherapy and chemotherapy. Owing to MB stem cells (MBSCs), a subset of MB patients remains untreatable despite standard therapy. CD133 is used to identify MBSCs although its functional role in tumorigenesis has yet to be determined. In this work, we showed enrichment of CD133 in Group 3 MB is associated with increased rate of metastasis and poor clinical outcome. The signal transducers and activators of transcription-3 (STAT3) pathway are selectively activated in CD133 + MBSCs and promote tumorigenesis through regulation of c-MYC, a key genetic driver of Group 3 MB. We screened compound libraries for STAT3 inhibitors and treatment with the selected STAT3 inhibitors resulted in tumor size reduction in vivo . We propose that inhibition of STAT3 signaling in MBSCs may represent a potential therapeutic strategy to treat patients with recurrent MB.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.025
GPT teacher head0.290
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations66
Published2016
Admission routes2
Has abstractyes

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