Preclinical recapitulation of antiangiogenic drug clinical efficacies using models of early or late stage breast cancer metastatis
Bibliographic record
Abstract
Historically, preclinical tumor therapy models in mice have frequently been deficient in predicting subsequent clinical activity; over-prediction of clinical anti-tumor efficacy is common. Several approaches are being made in an attempt to improve the clinical relevance of preclinical models, and include the use of genetically engineered mouse models (GEMMs) of cancer or patient derived xenografts (PDXs). Here we summarize, in the context of breast cancer, another approach, namely, the development of postsurgical models of either macroscopic or microscopic metastatic disease to mimic metastatic or adjuvant therapy. To do so we used in vivo selected metastatic variants of established human breast cancer cell lines such as MDA-MB-231. Testing antiangiogenic drugs such as the oral tyrosine kinase inhibitor (TKI) sunitinib alone or combined with chemotherapy in models involving treatment of established primary tumors invariably resulted in demonstrable anti-tumor activity. In contrast, identical treatments of postsurgical mice with advanced metastatic disease did not: survival times were not prolonged. This reflects multiple failed phase III trials of sunitinib based therapies in metastatic breast cancer patients. However, using a VEGF pathway targeting antibody drug instead of a TKI, with (paclitaxel) chemotherapy, resulted in anti-tumor activity in the metastatic setting, partially reflecting prior clinical results of the E2100 phase III trial of weekly paclitaxel plus bevacizumab. Other experiments involving postsurgical adjuvant treatment of early stage disease foreshadowed the phase III clinical trial failures of adjuvant bevacizumab in colorectal or breast cancer. In contrast, some investigational metronomic oral chemotherapy protocols alone or in combination with an antiangiogenic drug demonstrated potent activity in the advanced metastatic setting; these encouraging results have yet to be validated in randomized phase III clinical trials, which are underway based on some encouraging phase II clinical trial results. We have also observed circumstances where mice with advanced systemic disease, when successfully treated so as to prolong survival, sometimes relapse with brain metastases, reflecting a similar clinical phenomenon. Given our overall findings, we suggest that using preclinical mouse tumor models which mimic postsurgical adjuvant or metastatic therapy may be a promising strategy to help improve the ability to predict subsequent clinical outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".