<i>In Vitro</i> Comparison of Sestamibi, Tetrofosmin, and Furifosmin as Agents for Functional Imaging of Multidrug Resistance in Tumors
Bibliographic record
Abstract
Sestamibi, tetrofosmin, and furifosmin are 99mTc-labeled myocardial perfusion imaging agents which have been shown to be substrates for P-glycoprotein (Pgp), the multidrug-resistance transporter which is overexpressed in some tumors. The three tracers were directly compared in vitro in the human breast cancer cell line MCF7-WT and two multidrug-resistant variants, MCF7-BC19 (MDR1 gene transfected) and MCF7-AdrR (doxorubicin selected). Tracer accumulation over the course of 60 minutes was determined. Dose-response curves were generated for two modulators of Pgp function, GG918 and PSC833. The general shape of accumulation curves for the three tracers in MCF7-WT cells was similar, with accumulation levels being sestamibi > tetrofosmin > furifosmin. Accumulation of sestamibi and furifosmin in MCF7-BC19 cells was reduced to 10% and 21% of MCF7-WT levels, respectively, but this accumulation deficit could be completely reversed by addition of 0.1 microM GG918 or 2 microM PSC833. Accumulation of sestamibi and tetrofosmin in MCF7-AdrR cells was 1.6% and 12% of MCF7-WT levels, respectively, and could only be enhanced to 30% and 45% of MCF7-WT levels by addition of GG918 or PSC833. In contrast, furifosmin showed similar levels of accumulation in MCF7-WT and MCF7-BC19 cells, slightly lower levels in MCF7-AdrR cells, and no consistent response to Pgp modulators. These results support the continued investigation of sestamibi and tetrofosmin as agents for functional imaging of multidrug resistance in human cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".