The Contributions of Prostate Cancer Stem Cells in Prostate Cancer Initiation and Metastasis
Bibliographic record
Abstract
Research in the last decade has clearly revealed a critical role of prostate cancer stem cells (PCSCs) in prostate cancer (PC). Prostate stem cells (PSCs) reside in both basal and luminal layers, and are the target cells of oncogenic transformation, suggesting a role of PCSCs in PC initiation. Mutations in PTEN, TP53, and RB1 commonly occur in PC, particularly in metastasis and castration-resistant PC. The loss of PTEN together with Ras activation induces partial epithelial⁻mesenchymal transition (EMT), which is a major mechanism that confers plasticity to cancer stem cells (CSCs) and PCSCs, which contributes to metastasis. While PTEN inactivation leads to PC, it is not sufficient for metastasis, the loss of PTEN concurrently with the inactivation of both TP53 and RB1 empower lineage plasticity in PC cells, which substantially promotes PC metastasis and the conversion to PC adenocarcinoma to neuroendocrine PC (NEPC), demonstrating the essential function of TP53 and RB1 in the suppression of PCSCs. TP53 and RB1 suppress lineage plasticity through the inhibition of SOX2 expression. In this review, we will discuss the current evidence supporting a major role of PCSCs in PC initiation and metastasis, as well as the underlying mechanisms regulating PCSCs. These discussions will be developed along with the cancer stem cell (CSC) knowledge in other cancer types.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".