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Record W2057895084 · doi:10.1182/blood-2011-08-375873

Role of SHP2 phosphatase in KIT-induced transformation: identification of SHP2 as a druggable target in diseases involving oncogenic KIT

2012· article· en· W2057895084 on OpenAlexaff
Raghuveer Singh Mali, Peilin Ma, Li‐Fan Zeng, Holly Martin, Baskar Ramdas, Yantao He, Emily Sims, Sarah C. Nabinger, Joydeep Ghosh, Namit Sharma, Veerendra Munugalavadla, Anindya Chatterjee, Shuo Li, George E. Sandusky, Andrew W. Craig, Kevin D. Bunting, Gen‐Sheng Feng, Rebecca J. Chan, Zhong-Yin Zhang, Reuben Kapur

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsQueen's University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteNational Heart, Lung, and Blood InstituteSchool of Medicine, Indiana University
KeywordsDruggabilityCancer researchProtein tyrosine phosphataseKinasePhosphataseBiologyLeukemiaTyrosine kinaseOncogeneSignal transductionPhosphorylationCell biologyCancerImmunologyGeneticsGeneCell cycle

Abstract

fetched live from OpenAlex

Intracellular mechanism(s) that contribute to promiscuous signaling via oncogenic KIT in systemic mastocytosis and acute myelogenous leukemia are poorly understood. We show that SHP2 phosphatase is essential for oncogenic KIT-induced growth and survival in vitro and myeloproliferative disease (MPD) in vivo. Genetic disruption of SHP2 or treatment of oncogene-bearing cells with a novel SHP2 inhibitor alone or in combination with the PI3K inhibitor corrects MPD by disrupting a protein complex involving p85α, SHP2, and Gab2. Importantly, a single tyrosine at position 719 in oncogenic KIT is sufficient to develop MPD by recruiting p85α, SHP2, and Gab2 complex to oncogenic KIT. Our results demonstrate that SHP2 phosphatase is a druggable target that cooperates with lipid kinases in inducing MPD.

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 score0.023
Threshold uncertainty score0.634

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)0.0010.000

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Citations54
Published2012
Admission routes1
Has abstractyes

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