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Record W2027832172 · doi:10.1158/1538-7445.am10-1240

Abstract 1240: Functional deregulation of NF-kB and abnormal TNFa response in acute promyelocytic leukemia

2010· article· en· W2027832172 on OpenAlexaff
Mariam Thomas, Mahadeo A. Sukhai, Nicholas W. Schuh, Yali Xuan, Mark D. Minden, Suzanne Kamel‐Reid

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsAcute promyelocytic leukemiaMicroarray analysis techniquesLeukemiaFusion geneBiologyGeneCancer researchRetinoic acidChromosomal translocationGene expressionPromyelocytePathogenesisSignal transductionMicroarrayNF-κBGene expression profilingMolecular biologyImmunologyGenetics

Abstract

fetched live from OpenAlex

Abstract Acute promyelocytic leukemia (APL) accounts for approximately 10% of acute myelogenous leukemia (AML) cases, and is characterized by accumulation of abnormal promyelocytes in patient bone marrow and peripheral blood. APL is associated with balanced chromosomal translocations involving retinoic acid receptor alpha (RARA), giving rise to fusion oncoproteins referred to as X-RARA. As deregulation of retinoid signaling is insufficient for leukemia development, our studies aim to determine other signaling pathways involved in APL by assessing the gene expression profiles and cell biology of X-RARA. We previously determined, using gene expression microarray analysis, common downstream targets of the variant APL fusion proteins NPM- and NuMA-RARA. We observed an over-representation of NF-κB target genes within this dataset. In these cells, a number of NF-κB target genes were commonly over-expressed. A subset of commonly deregulated genes were validated in our APL cell lines and 23 primary APL patient samples by real-time quantitative RT-PCR (RQ-PCR). 13/16 genes that were tested were significantly altered in APL compared to normal BM (n=11) p<0.05. The majority of these deregulated genes showed a progressive trend towards normal expression levels in post-treated samples. These data indicate defects in NF-κB-mediated gene expression in APL pathogenesis. We next examined NF-κB activity by assessing the expression levels of NF-κB target genes by quantitative real-time RT-PCR, in the presence and absence of TNFα. We observed that there was sustained activation of NF-κB in cells expressing NPM-RARA, as evidenced by the increased expression of NF-κB transcriptional target genes after induction by TNFα. Western analysis of protein derived from U937-NPM-RARA and NB4 cells demonstrated over-expression of NF-κB (p65) protein, as well as its transcriptional target IκBα. The increased pool of NF-κB localized to both the cytoplasm and the nucleus in U937-NPM-RARA cells as visualized by immunofluorescent confocal microscopy. Having observed deregulated expression of downstream targets of TNFα, we sought to examine the ability of X-RARA to confer resistance to TNF-mediated apoptosis. Our results in colony formation assays indicated that NPM-RARA expressing cells formed significantly more colonies, in the presence of 0-100 ng/mL TNFα, in a dose-dependent manner, compared to U937 control cells. These data suggested a greater ability on the part of NPM-RARA+ cells to survive and proliferate in the presence of TNFα. Our data provides the first evidence of the functional deregulation of the NF-κB-mediated signaling pathway and the TNFα response in cells expressing the variant APL fusion proteins. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1240.

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: Observational · Consensus signal: none
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)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.025
GPT teacher head0.340
Teacher spread0.315 · 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 designObservational
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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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