Metastatic Breast Cancer: Review of Emerging Nanotherapeutics
Bibliographic record
Abstract
Metastases of breast cancer (BC) are often referred to as stage IV breast cancer due to their severity and high rate of mortality. The median survival time of patients with metastatic BC is reduced to 3 years. Currently, the treatment regimens for metastatic BC are similar to the primary cancer therapeutics and are limited to conventional chemotherapy, immunotherapy, radiotherapy, and surgery. However, metastatic BC shows organ-specific complex tumor cell heterogeneity, plasticity, and a distinct tumor microenvironment, leading to therapeutic failure. This issue can be successfully addressed by combining current cancer therapies with nanotechnology. The applications of nanotherapeutics for both primary and metastatic BC treatments are developing rapidly, and new ideas and technologies are being discovered. Several recent reviews covered the advancement of nanotherapeutics for primary BC, while also discussing certain aspects of treatments for metastatic BC. This review provides comprehensive details on the recent advancement and future prospects of nanotherapeutics designed for metastatic BC treatment, in the context of the pathological state of the disease. Furthermore, possible combinations of current treatment with nanotechnology are discussed, and their potential for future transitions in clinical settings is explored.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".