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Abstract A146: The role of cystine transport in darinaparsin-induced cell death

2009· article· en· W1976746884 on OpenAlexaff
Nicolas Garnier, Yuxuan Gu, Maria Kourelis, Koren K. Mann, D. Scott Bohle, Wilson H. Miller

Bibliographic record

VenueMolecular Cancer Therapeutics · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsGlutathioneIntracellularCystineExtracellularPropidium iodideButhionine sulfoximineCysteineChemistryApoptosisOxidative stressFlow cytometryBiochemistryProgrammed cell deathMolecular biologyBiologyEnzyme

Abstract

fetched live from OpenAlex

Abstract Darinaparsin (ZIO-101; S-dimethylarsino-glutathione; Dar) is a promising novel organic arsenical, currently undergoing clinical studies in various malignancies. Dar is synthesized by conjugating dimethylarsenic (DMA) to glutathione (GSH) and shows enhanced activity as compared to arsenic trioxide (ATO). Dar induces more intracellular arsenic accumulation, oxidative stress (OS) and cell death than ATO. However, Dar has a maximum tolerated dose that is 35-fold higher than ATO. The mechanisms responsible for the lower toxicity and higher anti-tumor efficacy associated with Dar remains to be elucidated. Here, we propose a mechanism for Dar import that might, at least partially, explain the enhanced efficacy. Preliminary results show that both ATO and Dar induce the expression of the cystine importer xCT and that high levels of xCT expression correlates with high sensitivity to Dar, as shown in a NCI60 panel. The cystine/cysteine redox cycle consists of cystine uptake, intracellular reduction to cysteine which is secreted into the extracellular space where it is oxidized back to cystine. Intracellular cysteine (Cys-SH) can be used for the synthesis of GSH, the major intracellular OS scavenger. We find that increased extracellular concentration of L-cysteine or equivalent thiols during Dar treatment inhibits intracellular arsenic accumulation, measured by Inductively Coupled Plasma Mass Spectrometry (ICP-MS), as well as apoptosis, assessed by propidium iodide staining quantitated by flow cytometry. Thus, we hypothesized that L-cysteine or equivalent thiols might prevent Dar import. GSH itself is not imported in the cell, so we thought it unlikely that darinaparsin would enter the cell without being somehow modified. Structural analysis of darinaparsin reveals putative break-down products: dimethylarsino-cysteine (DMAC), dimethylarsenic III (DMA III) and dimethylarsenic V (DMA V). ICP-MS experiments showed that treatment with DMA III and DMA V does not lead to significant intracellular accumulation of arsenic, and correlates with their inability to induce cell death. However, DMAC is very similar to Dar in terms of intracellular accumulation of arsenic, G2/M arrest and cell death. As with Dar, thiols were able to inhibit DMAC-induced cell death. In summary, we hypothesize that darinaparsin gets transformed extracellularly into DMAC, which is imported via xCT or another cystine/cysteine importing system. Cells respond to arsenic-induced OS by increasing cystine uptake, which may selectively increase the anti-cancer activity of Dar. The fact that cancer cells, under a high OS state, have an increase need for GSH, i.e. for cystine, might explain the fewer systemic toxicities reported with Dar. Moreover, cystine/cysteine importers may be valuable biomarkers to predict Dar sensitivity. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A146.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.001

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 head0.013
GPT teacher head0.260
Teacher spread0.247 · 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".

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Citations0
Published2009
Admission routes1
Has abstractyes

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