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Record W2763700508 · doi:10.21873/anticanres.11886

Inhibitory Activity of Iron Chelators ATA and DFO on MCF-7 Breast Cancer Cells and Phosphatases PTP1B and SHP2

2017· article· en· W2763700508 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnticancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDeferoxamineAurintricarboxylic acidMCF-7Cancer cellCancer researchPhosphataseChemistryCancerEnzymeBiochemistryChelationBiologyPharmacologyApoptosisHuman breastProgrammed cell death

Abstract

fetched live from OpenAlex

BACKGROUND: Rapidly-dividing cancer cells have higher requirement for iron compared to non-transformed cells, making iron chelating a potential anticancer strategy. In the present study we compared the anticancer activity of uncommon iron chelator aurintricarboxylic acid (ATA) with the known deferoxamine (DFO). MATERIALS AND METHODS: We investigated the impact of ATA and DFO on the viability and proliferation of MCF-7 cancer cells. Moreover we performed enzymatic activity assays and computational analysis of the ATA and DFO effects on pro-oncogenic phosphatases PTP1B and SHP2. RESULTS: ATA and DFO decrease the viability and proliferation of breast cancer cells, but only ATA considerably reduces the activity of PTP1B and SHP2 phosphatases. Our studies indicated that ATA strongly inactivates and binds in the PTP1B and SHP2 active site, interacting with arginine residue essential for enzyme activity. CONCLUSION: We confirmed that iron chelating can be considered as a potential strategy for the adjunctive treatment of breast cancer.

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.

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)0.000
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 score0.090
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.036
GPT teacher head0.374
Teacher spread0.337 · 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