MétaCan
Menu
Back to cohort
Record W2404028782 · doi:10.1016/j.celrep.2016.04.076

Haploinsufficiency of the ESCRT Component HD-PTP Predisposes to Cancer

2016· article· en· W2404028782 on OpenAlexafffund
Sanaz Manteghi, Marie‐Claude Gingras, Dmitri Kharitidi, Luc Galarneau, Maud Marques, Ming Yan, Regina Cencic, Françis Robert, Marilène Paquet, Michael Witcher, Jerry Pelletier, Arnim Pause

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversité de MontréalJewish General HospitalMcGill University
FundersCanadian Institutes of Health Research
KeywordsESCRTHaploinsufficiencyBiologyCancer researchTumor suppressor geneCarcinogenesisDownregulation and upregulationLoss functionSuppressorCancerLymphomaEndosomeCell biologyCellImmunologyGeneGeneticsPhenotype

Abstract

fetched live from OpenAlex

Endosomal sorting complexes required for transport (ESCRT) drive cell surface receptor degradation resulting in attenuation of oncogenic signaling and pointing to a tumor suppressor function. Here, we show that loss of function of an ESCRT protein (HD-PTP encoded by the PTPN23 gene, located on the tumor suppressor gene cluster 3p21.3) drives tumorigenesis in vivo. Indeed, Ptpn23(+/-) loss predisposes mice to sporadic lung adenoma, B cell lymphoma, and promotes Myc-driven lymphoma onset, dissemination, and aggressiveness. Ptpn23(+/-)-derived tumors exhibit an unaltered remaining allele and maintain 50% of HD-PTP expression. Consistent with the role of HD-PTP in attenuation of integrin recycling, cell migration, and invasion, hemizygous Ptpn23(+/-) loss increases integrin β1-dependent B cell lymphoma survival and dissemination. Finally, we reveal frequent PTPN23 deletion and downregulation in human tumors that correlates with poor survival. Altogether, we establish HD-PTP/PTPN23 as a prominent haploinsufficient tumor suppressor gene preventing tumor progression through control of integrin trafficking.

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 score0.156
Threshold uncertainty score0.152

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 head0.009
GPT teacher head0.241
Teacher spread0.232 · 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

Citations51
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueCell ReportsSame topicRNA modifications and cancerFrench-language works237,207