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Record W2808774077 · doi:10.1093/neuonc/noy059.497

MBRS-52. TARGETING PRUNE-1 IN A GEMM OF METASTATIC MEDULLOBLASTOMA: A POTENTIAL ROUTE OF INHIBITION FOR NEW FUTURE THERAPIES

2018· article· en· W2808774077 on OpenAlexaff
Veronica Ferrucci, Pasqualino De Antonellis, Francesco Paolo Pennino, Fatemeh Asadzadeh, Roberto Siciliano, Antonella Virgilio, Aldo Galeone, Lucia De Martino, Lucia Quaglietta, Maria Elena Errico, Vittoria Donofrio, Daniel Picard, Marc Remke, Louis Chesler, Fredrik J. Swartling, William A. Weiss, Michael D. Taylor, Giuseppe Cinalli, Massimo Zollo

Bibliographic record

VenueNeuro-Oncology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMechanisms of cancer metastasis
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedulloblastomaCancer researchIn vivoBiologyMetastasisPTENCancerSignal transductionCell biologyPI3K/AKT/mTOR pathwayGenetics

Abstract

fetched live from OpenAlex

Genetic modifications during development of paediatric Group3 Medulloblastoma (MBGroup3) are responsible for its highly metastatic properties and poor patient survival rates. We found PRUNE-1 to be highly expressed in metastatic MBGroup3, which is characterised by TGF-β signalling activation and OTX2 expression. The molecular mechanism was identified underlying the metastatic dissemination of those PRUNE-1-driven-MBGroup3. PRUNE-1, through its binding to NDPK-A (NME-1), enhances the canonical TGF-β pathway activation, upregulates OTX2 and SNAIL, and inhibits PTEN. We also identified a new non-toxic small molecule pyrimido-pyrimidine derivative (AA7.1) with the ability to enhance PRUNE-1 degradation and to impair tumour progression and metastases in vivo using orthotopic xenograft models with metastatic MBGroup3 cells. Using whole exome sequencing technology in primary human metastatic MB cells, we also defined new deleterious ‘non-synonymous homozygous’ gene variants with effects on immune cells activation/differentiation, as part of a protein network of relevance for metastatic processes (Ferrucci et al., Brain In Press, 2018). We developed a Genetically Engineered Mouse Model (GEMM) of PRUNE-1-driven-metastatic MB. This GEMM (MATH1-PRUNE-1/Cyclin-B2-LUC) was generated by overexpressing PRUNE-1 in the developing cerebellum (using MATH1 promoter) together with the Luciferase gene (under the control of Cyclin-B2 promoter) in a background TP53-/-, thus generating Medulloblastoma. Chemotherapeutic drugs for high-risk MB together with AA7.1 were tested in combination on medullospheres showing an impairment of cell index proliferation. In vivo, in xenografted studies, we showed tumour inhibition at both the primary and metastatic sites together with immunonomodulatory effects. Altogether these results are of importance for future targeted therapies of high risk metastatic MBGroup3.

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 score0.070
Threshold uncertainty score0.686

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)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.289
Teacher spread0.275 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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