Comparative Impact of Trastuzumab and Cyclophosphamide on HER-2–Positive Human Breast Cancer Xenografts
Bibliographic record
Abstract
PURPOSE: Metronomic chemotherapy is a minimally toxic and frequently effective new treatment strategy that is beginning to show promising phase II clinical trial results, particularly for metastatic breast cancer when combined with various molecularly targeted antitumor agents. Here, we assessed a treatment strategy that uses trastuzumab plus daily oral metronomic cyclophosphamide on metastatic Her-2-positive human breast cancer models. EXPERIMENTAL DESIGN: Treatments were initiated on orthotopic transplanted primary tumors as well as established visceral metastatic disease of two independent Her-2-positive breast cancer models, both independently derived from the human MDA-MB-231 breast cancer cell line. Outcome was assessed by noninvasive measurements of tumor cell-secreted human choriogonadotropin in the urine as a surrogate marker of relative tumor burden, or by whole body bioluminescent imaging, in addition to prolongation of survival. RESULTS: Orthotopic primary tumors responded to trastuzumab monotherapy with significant growth delays, whereas minimal antitumor effect was observed when mice with metastatic disease were treated. Nevertheless, trastuzumab showed a benefit in this latter setting when combined with metronomic low-dose cyclophosphamide as assessed by prolongation of survival. This benefit was similar to trastuzumab plus maximum tolerated dose cyclophosphamide, but was associated with lesser toxicity. CONCLUSIONS: Trastuzumab combined with metronomic cyclophosphamide may be an effective long-term maintenance strategy for the treatment of Her-2-positive metastatic breast 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".