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Record W2317269400 · doi:10.1158/1538-7445.am2011-4405

Abstract 4405: The novel allosteric Akt inhibitor, MK-2206, synergizes with gefitinib against human glioma cells via promoting the switch from autophagy to apoptosis

2011· article· en· W2317269400 on OpenAlexaff
Yan Cheng, Yi Zhang, Xingcong Ren, Yan Li, Eric H. Rubin, Jin‐Ming Yang

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldChemistry
TopicQuinazolinone synthesis and applications
Canadian institutionsUniversity College of the North
Fundersnot available
KeywordsGefitinibProtein kinase BApoptosisCancer researchGliomaEpidermal growth factor receptorAutophagyCancer cellTyrosine-kinase inhibitorBiologyPharmacologyCancerMedicineInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Gefitinib, a small molecule inhibitor of the epidermal growth factor receptor tyrosine kinase, has been shown to induce autophagy as well as apoptosis in tumor cells. This drug, in addition to being used for treatment of patients with non-small cell lung cancer, has also been in clinical trials for treating other types of cancer, including malignant brain tumors. However, the mechanism and signaling pathways mediating the gefitinib-induced tumor cell death, and the approach to enhancing the therapeutic efficacy of this drug against cancer, remain to be fully investigated. To explore the ways that can maximize the efficacy of gefitinib, in the current study we determined whether MK-2206, a potent allosteric small-molecule inhibitor of Akt currently in Phase I trials in patients with solid tumors, could reinforce the cytocidal effect of gefitinib against glioma, the most common form of brain cancer. We found in human glioma cell lines, LN229 and T98G, that both gefitinib and MK-2206 induced apoptosis and reduced the level of phosphorylation of Akt in a dose-dependent manner, indicating that these agents may induce apoptosis by inhibiting the Akt-mediating anti-apoptotic pathways. Co-treatment with gefitinib and MK-2206 increased the cytotoxicity of gefitinib in the glioma cells, and the Compusyn synergism/antagonism analysis showed that MK-2206 acted synergistically with gefitinib. Apoptosis assay (Annexin V staining) demonstrated that in the presence of MK-2206, there was a significant increase in apoptotic cell death in glioma cells treated with gefitinib, in comparison with the cells treated with gefitinib alone. Survivin, a member of inhibitor of apoptosis protein (IAP) family and a downstream player of the Akt pathway, was decreased by the combination treatment. MK-2206 also augmented the autophagy-inducing effect of gefitinib, as evidenced by increased levels of the autophagy marker, LC3-II. Inhibition of autophagy by silencing of the key autophagy gene, beclin 1, further increased the cytotoxicity of the combination treatment of gefitinib with MK-2206, suggesting that autophagy induced by these agents plays a cytoprotective role. Notably, at 48 hours following the combination treatment, the level of LC3-II began to decrease but the accumulation of Bim, a pro-apoptotic BH3-only protein, was elevated, suggesting a switch from autophagy to apoptosis. Study of the precise molecular mechanism underlying this cross-talk between autophagy and apoptosis is still in progress. Based on the synergistic effect of MK-2206 on gefitinib observed in this study, the combination of these two drugs may be utilized as a new therapeutic regimen for malignant glioma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4405. doi:10.1158/1538-7445.AM2011-4405

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 categoriesInsufficient payload (model declined to judge)
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 score0.011
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.086
GPT teacher head0.335
Teacher spread0.249 · 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 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
Published2011
Admission routes1
Has abstractyes

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