Targeting the relaxin hormonal pathway in prostate cancer
Bibliographic record
Abstract
Targeting the androgen signalling pathway has long been the hallmark of anti-hormonal therapy for prostate cancer. However, development of androgen-independent prostate cancer is an inevitable outcome to therapies targeting this pathway, in part, owing to the shift from cancer dependence on androgen signalling for growth in favor of augmentation of other cellular pathways that provide proliferation-, survival- and angiogenesis-promoting signals. This review focuses on the role of the hormone relaxin in the development and progression of prostate cancer, prior to and after the onset of androgen independence, as well as its role in cancers of other reproductive tissues. As the body of literature expands, examining relaxin expression in cancerous tissues and its role in a growing number of in vitro and in vivo cancer models, our understanding of the important involvement of this hormone in cancer biology is becoming clearer. Specifically, the pleiotropic functions of relaxin affecting cell growth, angiogenesis, blood flow, cell migration and extracellular matrix remodeling are examined in the context of cancer progression. The interactions and intercepts of the intracellular signalling pathways of relaxin with the androgen pathway are explored in the context of progression of castration-resistant and androgen-independent prostate cancers. We provide an overview of current anti-hormonal therapeutic treatment options for prostate cancer and delve into therapeutic approaches and development of agents aimed at specifically antagonizing relaxin signalling to curb tumor growth. We also discuss the rationale and challenges utilizing such agents as novel anti-hormonals in the clinic, and their potential to supplement current therapeutic modalities.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".