Tipifarnib Plus Tamoxifen in Tamoxifen-Resistant Metastatic Breast Cancer: A Negative Phase II and Screening of Potential Therapeutic Markers by Proteomic Analysis
Bibliographic record
Abstract
PURPOSE: Tipifarnib, a farnesyltransferase inhibitor, has antitumor activity in heavily pretreated metastatic breast cancer patients. Preclinical data suggest that FTIs could restore tamoxifen responsiveness in tamoxifen-resistant disease. Thus, combining FTIs and tamoxifen may be a promising clinical approach after relapse or progression on tamoxifen. EXPERIMENTAL DESIGN: Postmenopausal patients with measurable estrogen receptor- and/or progesterone receptor-expressing metastatic breast cancers were enrolled. Only patients with disease progression on tamoxifen were eligible, but there was no limitation regarding prior chemotherapy or hormone therapy regimens. Patients were immediately treated with 300 mg (n = 12) or 200 mg (n = 10) tipifarnib twice daily for 21 of 28-day cycles plus tamoxifen once daily. Serum was collected at baseline and after 8 weeks of treatment to enable proteomic comparison and identify possible predictive response markers. RESULTS: Twenty patients were enrolled and evaluated for efficacy: one patient had an objective response (liver metastasis) and nine had stable disease after 6 months for a clinical benefit rate of 50%; median duration of benefit was 10.3 (range, 7.4-20.2) months. The proteomic analysis by SELDI-TOF and LTQ-FT-Orbitrap identified a known peptide of fibrinogen alpha, the intensity of which was significantly increased in patients with progression compared with patients who benefited from the combined treatment after 8 weeks. CONCLUSIONS: Because the primary end point of efficacy (three objective responses) was not achieved, the study is negative. Nevertheless, the identified peptide could be of interest in discriminating, at 8 weeks of treatment, responders from nonresponders.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".