<sup>18</sup>F-FDG Small-Animal PET/CT Differentiates Trastuzumab-Responsive from Unresponsive Human Breast Cancer Xenografts in Athymic Mice
Bibliographic record
Abstract
UNLABELLED: Breast cancers (BCs) with high human epidermal growth factor receptor type 2 (HER2) expression are most likely to respond to trastuzumab; however, the mechanisms of action of trastuzumab are complex and there are no established biomarkers to accurately monitor treatment outcome in individual patients. Therefore, our aim was to determine, in human BC xenografts in athymic mice treated with trastuzumab, whether there were any changes in (18)F-FDG uptake that were associated with response to the drug and that could have utility in monitoring response in patients. METHODS: Baseline tumor uptake of (18)F-FDG was measured in mice with MDA-MB-361 HER2-overexpressing xenografts and MDA-MB-231 xenografts with low HER2 expression by small-animal PET imaging on day 0. Mice were treated with phosphate-buffered saline (PBS) or trastuzumab (4 mg/kg), and small-animal PET was repeated 2 d after treatment. Maintenance doses of trastuzumab (2 mg/kg) or PBS were administered on days 7 and 14, and mice were imaged again on days 9 and 16. Tumor uptake was measured as percentage injected dose per gram (%ID/g) by volume-of-interest analysis on days 0 (baseline), 2, 9, and 16, followed by biodistribution studies on day 16. Tumor growth was measured, and a tumor growth index was calculated. RESULTS: The treatment of mice with trastuzumab, compared with control mice treated with PBS, resulted in a significant decrease in tumor uptake of (18)F-FDG in HER2-overexpressing MDA-MB-361 xenografts after 16 d of treatment (2.6 +/- 0.8 %ID/g vs. 4.6 +/- 1.8 %ID/g, respectively; P < 0.03) but not after 2 or 9 d of treatment (P = 0.28-0.32). In contrast, there was no significant change in the tumor uptake of MDA-MB-231 xenografts with low HER2 expression during the entire course of therapy (4.4 +/- 1.7 %ID/g vs. 3.6 +/- 1.1 %ID/g, respectively; P = 0.31). Trastuzumab treatment, compared with PBS treatment of controls, resulted in significant growth inhibition of MDA-MB-361 xenografts as early as 10 d from the initiation of treatment (tumor growth index, 0.7 +/- 0.2 vs. 1.7 +/- 0.3, respectively; P < 0.0005), whereas no tumor growth inhibition was observed for MDA-MB-231 xenografts (5.3 +/- 2.7 and 5.2 +/- 3.0; P = 0.95). CONCLUSION: Changes in the tumor uptake of (18)F-FDG after therapy accurately identified responding and nonresponding human BC xenografts in athymic mice treated with trastuzumab; however, diminished glucose utilization did not precede changes in tumor volume.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".