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Record W2559527154 · doi:10.1158/0008-5472.can-16-1502

A Metastatic Mouse Model Identifies Genes That Regulate Neuroblastoma Metastasis

2016· article· en· W2559527154 on OpenAlexafffund
Bo Kyung A. Seong, Kelly E. Fathers, Robin Hallett, Christina K. Yung, Lincoln Stein, Samar Mouaaz, Lynn Kee, Cynthia Hawkins, Meredith S. Irwin, David R. Kaplan

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsAmgen (Canada)Hospital for Sick ChildrenOntario Institute for Cancer ResearchUniversity of Toronto
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsNeuroblastomaMetastasisCancer researchBiologyIn vivoGene expression profilingPrimary tumorCancerPediatric cancerGene signatureMedicineGene expressionGeneCell cultureGenetics

Abstract

fetched live from OpenAlex

Metastatic relapse is the major cause of death in pediatric neuroblastoma, where there remains a lack of therapies to target this stage of disease. To understand the molecular mechanisms mediating neuroblastoma metastasis, we developed a mouse model using intracardiac injection and in vivo selection to isolate malignant cell subpopulations with a higher propensity for metastasis to bone and the central nervous system. Gene expression profiling revealed primary and metastatic cells as two distinct cell populations defined by differential expression of 412 genes and of multiple pathways, including CADM1, SPHK1, and YAP/TAZ, whose expression independently predicted survival. In the metastatic subpopulations, a gene signature was defined (MET-75) that predicted survival of neuroblastoma patients with metastatic disease. Mechanistic investigations demonstrated causal roles for CADM1, SPHK1, and YAP/TAZ in mediating metastatic phenotypes in vitro and in vivo Notably, pharmacologic targeting of SPHK1 or YAP/TAZ was sufficient to inhibit neuroblastoma metastasis in vivo Overall, we identify gene expression signatures and candidate therapeutics that could improve the treatment of metastatic neuroblastoma. Cancer Res; 77(3); 696-706. ©2017 AACR.

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)0.001
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 score0.063
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.176
GPT teacher head0.428
Teacher spread0.252 · 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

Citations39
Published2016
Admission routes2
Has abstractyes

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