Inhibitory Activity of Iron Chelators ATA and DFO on MCF-7 Breast Cancer Cells and Phosphatases PTP1B and SHP2
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".