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Record W4391847514 · doi:10.1172/jci.insight.176044

Increasing Sufu gene dosage reveals its unorthodox role in promoting polydactyly and medulloblastoma tumorigenesis

2024· article· en· W4391847514 on OpenAlexaff
Boang Han, Yu Wang, Shen Yue, Yunhao Zhang, Lun Kuang, Binbin Gao, Yue Wang, Ziyu Zhang, Xiaohong Pu, Xin-fa Wang, Chi‐chung Hui, Tingting Yu, Chen Liu, Steven Y. Cheng

Bibliographic record

VenueJCI Insight · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsGLI1Sonic hedgehogMedulloblastomaCarcinogenesisGLI3PTCH1HedgehogCancer researchSuppressorPolydactylyBiologyHedgehog signaling pathwayPatchedGeneCell biologyGene expressionGenetics

Abstract

fetched live from OpenAlex

Suppressor of fused (SUFU) is widely regarded as a key negative regulator of the sonic hedgehog (SHH) morphogenic pathway and a known tumor suppressor of medulloblastoma (MB). However, we report here that SUFU expression was markedly increased in 75% of specimens compiled in a tissue array comprising 49 unstratified MBs. The SUFU and GLI1 expression levels in this MB array showed strong positive correlation, which was also identified in a large public data set containing 736 MBs. We further report that increasing Sufu gene dosage in mice caused preaxial polydactyly, which was associated with the expansion of the Gli3 domain in the anterior limb bud and heightened Shh signaling responses during embryonic development. Increasing Sufu gene dosage also led to accelerated cerebellar development and, when combined with ablation of the Shh receptor encoded by Patched1 (Ptch1), promoted MB tumorigenesis. These data reveal multifaceted roles of SUFU in promoting MB tumorigenesis by enhancing SHH signaling. This revelation clarifies potentially counterintuitive clinical observation of high SUFU expression in MBs and may pave way for novel strategies to reduce or reverse MB progression.

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 score0.025
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.251
Teacher spread0.240 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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