The Future of ER+/HER2− Metastatic Breast Cancer Therapy: Beyond PI3K Inhibitors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Most breast cancers express the estrogen receptor (ER) receptor and are negative for the human epidermal growth factor receptor 2 (HER2) receptor. ER+/HER2- cancers are treated with hormone-based therapies in the adjuvant setting and derive significant survival benefit from these therapies in the metastatic setting. However, hormone resistance develops in most metastatic patients. An increased understanding of the biology of ER+/HER2- breast cancers has led to the development of new therapies for this disease including CDK4/6 inhibitors and PI3K inhibitors. Several other neoplastic processes are targeted by novel drugs in clinical development, addressing cancer vulnerabilities. These include newer ways to block the ER and targeting the HER2 receptors in ER+/HER2- cancers expressing HER2 in low levels not qualifying for clinical positivity. In addition, promising therapeutic options include targeting other surface receptors or their downstream pathways, as well as targeting the apoptotic machinery and boosting the immune response which is initially insufficient in these cancers. A selection of new drugs in advanced development for ER+/HER2- breast cancer will be discussed in this review.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it