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Record W2132487225 · doi:10.2174/187152012798764741

Impact of Oncogenic Protein Tyrosine Phosphatases in Cancer

2012· review· en· W2132487225 on OpenAlexaff
Serge Hardy, Sofi G. Julien, Michel L. Tremblay

Bibliographic record

VenueAnti-Cancer Agents in Medicinal Chemistry · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsMcGill University
Fundersnot available
KeywordsProtein tyrosine phosphataseReceptor tyrosine kinasePhosphorylationPhosphataseCarcinogenesisG protein-coupled receptorBiologyReceptor Protein-Tyrosine KinasesTyrosine phosphorylationProtein phosphorylationCancerProto-oncogene tyrosine-protein kinase SrcKinaseSignal transductionCancer researchDual-specificity phosphataseTyrosine kinasePTPN11ReceptorTyrosineCell biologyBiochemistryProtein kinase AGenetics

Abstract

fetched live from OpenAlex

Protein tyrosine phosphatases (PTPs) constitute a large family of enzymes that can exert both positive and negative effects on signaling pathways. They play dominant roles in setting the levels of intracellular phosphorylation downstream of many receptors including receptor tyrosine kinases and G protein-coupled receptors. As observed with kinases, deregulation of PTP activity can also contribute to cancer. This review will examine a broad array of PTP family members that positively affect oncogenesis in human cancer tissues. We will describe the PTP family, their biological significance in oncology, and how recent progress is being made to more effectively target specific PTPs. Finally, we will discuss the therapeutic implications of targeting these oncogenic PTPs in cancer. Keywords: Cancer, Inhibitors, dual-specificity phosphatases (DSPs), Oncogene, Protein tyrosine phosphatases, Phosphorylation, Tumor suppressor, G protein-coupled receptors (GPCRs), Amplification, Gynecological Cancers

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.066
GPT teacher head0.411
Teacher spread0.345 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations41
Published2012
Admission routes1
Has abstractyes

Explore more

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