From Intractable to Treatable: Milestones and Horizons in the Management of HER2+ Breast Cancer
Bibliographic record
Abstract
The human epidermal growth factor receptor 2 (HER2) is a member of the epidermal growth factor receptor (EGFR) family that initiates various signalling pathways that control cell proliferation and tumourigenesis. Historically, approximately 15% of breast cancers have been characterized by overexpression or amplification of HER2, known as “HER2+” breast cancers. This subtype has been associated with an adverse prognosis, along with a high risk of recurrence and worse survival outcomes. However, with the discovery and subsequent development of HER2‑targeted therapies, the clinical course of HER2+ breast cancers has fundamentally changed. Optimizing therapeutic strategies using existing and emerging HER2-targeted therapies to build upon these advances remains a major priority for clinical development and treatment delivery. In 1998, the American Food and Drug Administration (FDA) and Health Canada approved trastuzumab, the first HER2-targeted therapy. Trastuzumab, a monoclonal antibody that binds to the HER2 receptor, has demonstrated clinical activity and improved outcomes in patients with metastatic HER2+ breast cancer when combined with chemotherapy. Following soon after, the first trial of adjuvant trastuzumab (HERA) demonstrated improvements in outcomes when combined with chemotherapy for early HER2+ breast cancer. More than 25 years after its first approval, trastuzumab retains a central role in the treatment of both early and advanced HER2+ breast cancer and has provided a backbone for both new therapeutic combinations (eg. with small molecule inhibitors of HER2) and new classes of therapeutic agents (antibody drug conjugates [ADC]). These successors of trastuzumab are currently redefining the HER2+ treatment landscape in both advanced and early breast cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".