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Record W3036458210 · doi:10.1172/jci132513

Trp53 and Rb1 regulate autophagy and ligand-dependent Hedgehog signaling

2020· article· en· W3036458210 on OpenAlexaff
Catherine R. Cochrane, Vijesh Vaghjiani, Anette Szczepny, W. Samantha N. Jayasekara, Álvaro González-Rajal, Kazu Kikuchi, Geoffrey W. McCaughan, Andrew Burgess, Daniel J. Gough, D. Neil Watkins, Jason E. Cain

Bibliographic record

VenueJournal of Clinical Investigation · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsUniversity of ManitobaResearch Institute in Oncology and HematologyCancerCare Manitoba
FundersCancer Council NSWVictorian Cancer Agency
KeywordsSmoothenedCiliumBiologyCell biologyHedgehog signaling pathwayHedgehogTransmembrane proteinSignal transductionCancer researchLigand (biochemistry)GeneticsReceptor

Abstract

fetched live from OpenAlex

Ligand-dependent activation of Hedgehog (Hh) signaling in cancer occurs without mutations in canonical pathway genes. Consequently, the genetic basis of Hh pathway activation in adult solid tumors, such as small-cell lung cancer (SCLC), is unknown. Here we show that combined inactivation of Trp53 and Rb1, a defining genetic feature of SCLC, leads to hypersensitivity to Hh ligand in vitro, and during neural tube development in vivo. This response is associated with the aberrant formation of primary cilia, an organelle essential for canonical Hh signaling through smoothened, a transmembrane protein targeted by small-molecule Hh inhibitors. We further show that loss of both Trp53 and Rb1 disables transcription of genes in the autophagic machinery necessary for the degradation of primary cilia. In turn, we also demonstrate a requirement for Kif3a, a gene essential for the formation of primary cilia, in a mouse model of SCLC induced by conditional deletion of both Trp53 and Rb1 in the adult airway. Our results provide a mechanistic framework for therapeutic targeting of ligand-dependent Hh signaling in human cancers with somatic mutations in both TP53 and RB1.

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)0.002
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 score0.037
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.082
GPT teacher head0.343
Teacher spread0.262 · 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
Published2020
Admission routes1
Has abstractyes

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