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Record W2317141295 · doi:10.1002/jcb.25561

The Tyrosine Kinome Dictates Breast Cancer Heterogeneity and Therapeutic Responsiveness

2016· review· en· W2317141295 on OpenAlexafffund
Jacqueline R. Ha, Peter M. Siegel, Josie Ursini‐Siegel

Bibliographic record

VenueJournal of Cellular Biochemistry · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsOccupational Cancer Research CentreMcGill University Health CentreMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsKinomeCancer researchBiologyTyrosine kinaseReceptor tyrosine kinaseTyrosineBreast cancerSignal transductionCancerCell biologyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Phospho-tyrosine signaling networks control numerous biological processes including cellular differentiation, cell growth and survival, motility, and invasion. Aberrant regulation of the tyrosine kinome is a hallmark of malignancy and influences all stages of breast cancer progression, from initiation to the development of metastatic disease. The success of specific tyrosine kinase inhibitors strongly validates the clinical relevance of tyrosine phosphorylation networks in breast cancer pathology. However, a significant degree of redundancy exists within the tyrosine kinome. Numerous receptor and cytoplasmic tyrosine kinases converge on a core set of signaling regulators, including adaptor proteins and tyrosine phosphatases, to amplify pro-tumorigenic signal transduction pathways. Mutational activation, amplification, or overexpression of one or more components of the tyrosine kinome represents key contributing events responsible for the tumor heterogeneity that is observed in breast cancers. It is this molecular heterogeneity that has become the most significant barrier to durable clinical responses due to the development of therapeutic resistance. This review focuses on recent literature that supports a prominent role for specific components of the tyrosine kinome in the emergence of unique breast cancer subtypes and in shaping breast cancer plasticity, sensitivity to targeted therapies, and the eventual emergence of acquired resistance. J. Cell. Biochem. 117: 1971-1990, 2016. © 2016 Wiley Periodicals, Inc.

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 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 score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.297
Teacher spread0.282 · 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

Citations29
Published2016
Admission routes2
Has abstractyes

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