Targeting the RANKL/RANK/OPG Axis for Cancer Therapy
Bibliographic record
Abstract
RANKL and RANK are expressed in different cell types and tissues throughout the body. They were originally described for their essential roles in bone remodeling and the immune system but have subsequently been shown to provide essential signals from regulating mammary gland homeostasis during pregnancy to modulating tumorigenesis. The success of RANKL/RANK research serves as a paragon for translational research from the laboratory to the bedside. The case in point has been the development of Denosumab, a RANKL-blocking monoclonal antibody which has already helped millions of patients suffering from post-menopausal osteoporosis and skeletal related events in cancer. Here we will provide an overview of the pathway from its origins to its clinical relevance in disease, with a special focus on emerging evidence demonstrating the therapeutic value of targeting the RANKL/RANK/OPG axis not only in breast cancer but also as an addition to the cancer immunotherapy arsenal.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".