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Record W2317684280 · doi:10.1158/1538-7445.am2012-5232

Abstract 5232: Tyrosine kinase inhibitor, gefitinib targets ZAP-70 over expressing chronic lymphocytic leukemia cells

2012· article· en· W2317684280 on OpenAlexaff
Spencer B. Gibson, Wenyan Xiao, Ju‐Yoon Yoon, Edward Noh, Michelle Brown, James B. Johnston

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGefitinibTyrosine kinaseCancer researchLYNSykCytotoxic T cellMedicineChronic lymphocytic leukemiaTyrosine-kinase inhibitorKinaseEpidermal growth factor receptorCancerInternal medicineChemistryLeukemiaBiologyReceptorCell biologyBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Abstract Most patients with chronic lymphocytic leukemia (CLL) initially respond to chemotherapy but relapse. There is a subset of CLL patients that have aggressive disease characterized by an over expression of the tyrosine kinase ZAP-70. These ZAP-70+ patients have a poorer survival and are more resistant to chemotherapy. The biological effects of ZAP-70 in CLL are believed to be related to its ability to enhance activation of Syk with subsequent triggering of down-stream modulators, such as ERK and AKT. Normally, Syk is activated by increased phosphorylation by Lyn, which is increased in CLL, or by activation of the B-cell receptor. Gefitinib is a tyrosine kinase inhibitor that is presently used to treat lung cancer. The drug inhibits epidermal growth factor receptor (EGFR) tyrosine kinase activity but has activity against >20 other kinase targets, including members of the Src family of kinases, such as Lyn and Syk. We thus evaluated the cytotoxic activity of gefitinib against primary CLL cells using the MTT assay. Gefitinib was cytotoxic to ZAP-70+ (≥20% cells positive) CLL samples (median IC50, ∼3.0 µM) while ZAP-70- patients failed to respond to gefitinib with a median IC50 of >15.0 µM. Jurkat cells, which are T cells that express high levels of ZAP-70, were more sensitive to gefitinib than B cell lines that did not express ZAP-70 (BJAB and NALM6). Further studies confirmed that gefitinib was inducing cell death through apoptosis. Gefitinib was also effective against ZAP-70+ CLL cells that were resistant to fludarabine and chlorambucil indicating a novel mechanism of action to standard chemotherapy. Enhanced apoptosis was observed in ZAP70+ CLL and Jurkat cells exposed to gefitinib and fludarabine or chlorambucil, but this was not observed in ZAP-70- or the B cell lines. In contrast, another EGFR inhibitor, erlotinib, had no effect against ZAP-70+ CLL cells indicating that gefitinib was inhibiting a kinase unaffected by erlotinib. When Jurakat and ZAP-70+ CLL cells were treated with gefitinib, there was reduced total tyrosine phosphorylation and decreased tyrosine phosphorylation of ZAP-70, and Syk but no difference in Lyn phosphorylation. Furthermore, gefitinib blocked B cell receptor activation and mediated cell survival. Taken together, these results indicate that gefitinib may be useful agent in the treatment of ZAP-70+ CLL, either alone or in combination with fludarabine or chlorambucil. Ongoing studies are determining the precise mechanism of action of gefitinib in ZAP-70+ CLL and assessing its effects on the CLL microenvironment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5232. doi:1538-7445.AM2012-5232

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.001

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 head0.065
GPT teacher head0.391
Teacher spread0.326 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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