MétaCan
Menu
Back to cohort
Record W2136713872 · doi:10.2174/187153010790827993

Imatinib Mesylate (Gleevec©): Targeted Therapy Against Cancer with Immune Properties

2010· review· en· W2136713872 on OpenAlexfundno aff
Moustapha Zoubir, Thomas Tursz, Cédric Menard, Laurence Zitvogel, Nathalie Chaput

Bibliographic record

VenueEndocrine Metabolic & Immune Disorders - Drug Targets · 2010
Typereview
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsnot available
FundersInstitut National Du CancerLigue Contre le CancerInstitute of Cancer ResearchInstitut National de la Santé et de la Recherche Médicale
KeywordsImatinib mesylateImatinibMedicineTargeted therapyTyrosine kinaseTyrosine-kinase inhibitorCancer researchImmune systemCancerPharmacologyImmunologyInternal medicineReceptorMyeloid leukemia

Abstract

fetched live from OpenAlex

The treatment against cancer is being flooded by targeted therapies. Imatinib mesylate (Gleevec) was the first molecule to provide the proof of principle that targeting an aberrant tyrosine kinase responsible for the uncontrolled cell cycle progression allows for the eradication of tumors. The ideal targeted therapy should eliminate the molecular event responsible for the disease, an oncogenic product such as c-KIT, ABL/BCR and PDGFRa in the case of Gleevec. Two issues related to this conceptual advance are raised in clinical practice. First, these therapies might target additional pathways generating side effects. Secondly, non tumoral cells bearing the molecular target might respond and induce additional biological outcomes. This review will summarize the by-stander immune modulations promoted by the paradigmatic compound Gleevec, leading to unexpected new therapeutic indications.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.020
GPT teacher head0.298
Teacher spread0.278 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueEndocrine Metabolic & Immune Disorders - Drug TargetsSame topicChronic Myeloid Leukemia TreatmentsFrench-language works237,207