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Record W2056737836 · doi:10.1158/1538-7445.am2014-491

Abstract 491: Selective killing of oncogenically transformed cells by arsenic trioxide and trolox

2014· article· en· W2056737836 on OpenAlexaffabout
Geneviève G. J. Redstone, Jessica N. Nichol, Brandon Faubert, Russell G. Jones, Koren K. Mann, Wilson H. Miller

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsTroloxPropidium iodideArsenic trioxideApoptosisCytotoxic T cellCancer cellPopulationCell biologyProgrammed cell deathChemistryBiologyCancer researchBiochemistryMedicineOxidative stressCancerIn vitro

Abstract

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Abstract Background: A major disadvantage of cytotoxic chemotherapy is the difficulty in selectively targeting tumor cells. Although arsenic trioxide (ATO) is an effective therapy in acute promyelocytic leukemia (APL), its use in solid tumors is limited by the toxicity observed at concentrations required to induce apoptosis in non-APL cells. We previously found that trolox, a vitamin E derivative, enhances ATO-induced apoptosis in APL cells, while simultaneously protecting normal cells. The objective of the current study is to understand the mechanism(s) by which trolox switches from cytoprotective to cytotoxic upon the oncogenic transformation of cells. Materials and methods: This study was conducted using two isogenic models: mouse embryonic fibroblast (MEFs) and MEFs stably-transfected with either E6/E7 or E1A/Ras oncogenes. Apoptosis was assessed via staining with Propidium Iodide (Cell Signaling) followed by FACS analysis. Cells were treated with various concentrations of ATO alone or in combination with 100μM trolox for 48 hours. SubG0 cell population results were obtained by staining the cells with PI, followed by analysis using CellQuest software. Mitochondrial ROS levels were measured with MitoSox (Life Technologies), followed by FACS analysis. Cells were treated with 5μM ATO alone or in combination with 100μM trolox for 18 hours. Mitochondrial fluorescence was examined by staining the cells with MitoSOX (Life Technologies). For the visualization and enumeration of mitochondria, cells were examined with Transmission Electron Microscopy (TEM). Intracellular pictures were taken with TEM at FEMR, McGill University. Changes in cellular metabolism were measured with an XF96 Extracellular Flux Analyzer (Seahorse Bioscience). Results: In both the E6/E7 and E1A/Ras models, trolox enhances ATO-induced death. In contrast, trolox has a protective effect from ATO toxicity in their untransformed counterparts. In the transformed cell lines, cell death correlates with enhanced formation of mitochondrial superoxide when treated with arsenic in combination with trolox. The functionality of mitochondria is closely linked to their structure. Preliminary analysis of TEM images indicates that mitochondrial structural integrity in transformed cells deteriorates when treated with ATO in combination with trolox. Finally, these results are supported by changes in cellular metabolisms in the transformed cell lines. Conclusion: Transformed cells are more sensitive to cytotoxicity induced by arsenic trioxide in combination with trolox than their wild-type counterparts. We hypothesize that the predominant mechanism of action by which transformed cells are sensitized to the actions of trolox and ATO is due to a dysfunction of mitochondrial activity. The results of this study will provide a means to expand the therapeutic spectrum of ATO beyond APL by enhancing tumor selectivity and protecting normal tissue from toxicity. Citation Format: Genevieve G. J. Redstone, Jessica N. Nichol, Brandon Faubert, Russell G. Jones, Koren K. Mann, Wilson H. Miller. Selective killing of oncogenically transformed cells by arsenic trioxide and trolox. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 491. doi:10.1158/1538-7445.AM2014-491

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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 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 score0.027
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.331
Teacher spread0.312 · 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.

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

Citations1
Published2014
Admission routes2
Has abstractyes

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