Present and Emerging Targeted Therapy for Metastatic Breast Cancer
Bibliographic record
Abstract
Breast carcinoma is a complex and heterogeneous disease and several different molecular alterations are involved in its pathogenesis and progression. Different growth factor receptor-driven signaling pathways sustain the growth and survival of breast cancer cells. Actually, three targeted agents are available for the treatment of breast cancer: trastuzumab, a monoclonal antibody directed against the human epidermal growth factor receptor-2 (HER2); lapatinib, an oral available dual tyrosine-kinase inhibitor of the human epidermal growth factor receptor-1 (HER1, EGFR) and HER2; bevacizumab, a monoclonal antibody directed against the vascular endothelial growth factor (VEGF). All these agents demonstrated to be synergistic with chemotherapy. In addition, recently concluded clinical trials suggest that signaling inhibitors can prevent or overcome resistance to endocrine therapy in estrogen receptor positive (ER+) breast cancer. Moreover, several other targeted drugs are under investigation in clinical trials. The aim of this review is to give a synthetic but complete picture of various targeted agents for breast cancer therapy that are under clinical trials or currently available in clinical practice.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".