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Record W2028650359 · doi:10.1172/jci42391

Prkar1a is an osteosarcoma tumor suppressor that defines a molecular subclass in mice

2010· article· en· W2028650359 on OpenAlexafffund
Sam D. Molyneux, Marco A. Di Grappa, Alexander G. Beristain, Trevor D. McKee, Daniel Wai, Jana Paděrová, Meenakshi Kashyap, Pingzhao Hu, Tamara Maiuri, Swami Narala, Vuk Stambolic, Jeremy A. Squire, Josef Penninger, Otto Sánchez, Timothy J. Triche, Geoffrey A. Wood, Lawrence S. Kirschner, Rama Khokha

Bibliographic record

VenueJournal of Clinical Investigation · 2010
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenOntario Institute for Cancer Research
FundersNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of HealthUniversity of Toronto
KeywordsSubclassBiologyCarcinogenesisOsteosarcomaSuppressorCancer researchGeneCancerGeneticsAntibody

Abstract

fetched live from OpenAlex

Some cancers have been stratified into subclasses based on their unique involvement of specific signaling pathways. The mapping of human cancer genomes is revealing a vast number of somatic alterations; however, the identification of clinically relevant molecular tumor subclasses and their respective driver genes presents challenges. This information is key to developing more targeted and personalized cancer therapies. Here, we generate a new mouse model of genomically unstable osteosarcoma (OSA) that phenocopies the human disease. Integrative oncogenomics pinpointed cAMP-dependent protein kinase type I, alpha regulatory subunit (Prkar1a) gene deletions at 11qE1 as a recurrent genetic trait for a molecularly distinct subclass of mouse OSA featuring RANKL overexpression. Using mouse genetics, we established that Prkar1a is a bone tumor suppressor gene capable of directing subclass development and driving RANKL overexpression during OSA tumorigenesis. Finally, we uncovered evidence for a PRKAR1A-low subset of human OSA with distinct clinical behavior. Thus, tumor subclasses develop in mice and can potentially provide information toward the molecular stratification of human cancers.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.093
GPT teacher head0.384
Teacher spread0.291 · 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 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

Citations101
Published2010
Admission routes2
Has abstractyes

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