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Record W2943704702 · doi:10.1172/jci.insight.127232

Intracellular cholesterol biosynthesis in enchondroma and chondrosarcoma

2019· article· en· W2943704702 on OpenAlexaff
Hongyuan Zhang, Qingxia Wei, Hidetoshi Tsushima, Vijitha Puviindran, Yuning J. Tang, Sinthu Pathmanapan, Raymond Poon, Eyal Ramu, Mushriq Al‐Jazrawe, Jay S. Wunder, Benjamin A. Alman

Bibliographic record

VenueJCI Insight · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalHospital for Sick Children
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institutes of Health
KeywordsEnchondromaChondrosarcomaIntracellularIDH1Isocitrate dehydrogenaseCancer researchCholesterolChemistryBiochemistryMutantCell biologyBiologyGenePathologyMedicineEnzyme

Abstract

fetched live from OpenAlex

Enchondroma and chondrosarcoma are the most common benign and malignant cartilaginous neoplasms. Mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2) are present in the majority of these tumors. We performed RNA-seq analysis on chondrocytes from Col2a1Cre;Idh1LSL/+ animals and found that genes implied in cholesterol synthesis pathway were significantly upregulated in the mutant chondrocytes. We examined the phenotypic effect of inhibiting intracellular cholesterol biosynthesis on enchondroma formation by conditionally deleting SCAP (sterol regulatory element-binding protein cleavage-activating protein), a protein activating intracellular cholesterol synthesis, in IDH1 mutant mice. We found fewer enchondromas in animals lacking SCAP. Furthermore, in chondrosarcomas, pharmacological inhibition of intracellular cholesterol synthesis significantly reduced chondrosarcoma cell viability in vitro and suppressed tumor growth in vivo. Taken together, these data suggest that intracellular cholesterol synthesis is a potential therapeutic target for enchondromas and chondrosarcomas.

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 score0.076
Threshold uncertainty score0.732

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 head0.005
GPT teacher head0.222
Teacher spread0.216 · 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

Citations18
Published2019
Admission routes1
Has abstractyes

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