Chimeric Antigen Receptor T-Cell Therapy in Metastatic Castrate-Resistant Prostate Cancer
Bibliographic record
Abstract
Prostate cancer is the most commonly diagnosed solid-organ cancer amongst males worldwide. Metastatic castrate-resistant prostate cancer (mCRPC) is a rapidly fatal end-sequelae of prostate cancer. Therapeutic options for men with mCRPC are limited and are not curative in nature. The recent development of chimeric antigen receptor T-cell (CAR-T) therapy has revolutionised the treatment of treatment-resistant haematological malignancies, and several studies are underway investigating the utility of this technology in the treatment of solid tumours. In this review, we evaluate the current treatment options for men with mCRPC as well as the current landscape of preclinical and clinical trials of CAR-T cell therapy against prostate cancer. We also appraise the various prostate cancer-specific tumour-associated antigens that may be targeted by CAR-T cell technology. Finally, we examine the potential translational barriers of CAR-T cell therapy in solid tumours. Despite preclinical success, preliminary clinical trials in men with prostate cancer have had limited efficacy. Therefore, further clinically translatable preclinical models are required to enhance the understanding of the role of this investigational therapeutic in men with mCRPC. In the era of precision medicine, tailored immunotherapy administered to men in a tumour-agnostic approach provides hope to a group of men who otherwise have few treatment options available.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".