Beyond Expression: Role of Phosphorylated Residues of EZH2 in Lineage Plasticity in Prostate Cancer
Bibliographic record
Abstract
Despite the development of effective targeted therapies and a significant understanding of carcinogenesis and cancer progression, treatment resistance is a major obstacle in achieving durable long-term control in many types of cancers. Emerging evidence supports that nongenetic mechanisms could play an underappreciated role in therapy resistance. These mechanisms include phenotypic plasticity, which is recognized as a hallmark of cancer and translates to epigenetic and transcriptional control of gene expression. Alterations in the expression and activity of the epigenetic modifier enhancer of zeste homolog 2 (EZH2) support prostate cancer lineage plasticity and progression. EZH2 expression and activity is elevated in castration-resistant prostate cancer treated with androgen receptor pathway inhibitors and in treatment-resistant prostate cancer. Moreover, 17 known residues of EZH2 are phosphorylated on by multiple kinases that modulate its activity, localization, stability, and polycomb repressive complex (PRC2) assembly. In this review, we explore the contribution of EZH2 phosphorylation in regulating canonical PRC2 in a methylation-dependent manner as an epigenetic repressor and in a noncanonical manner independent of PRC2 as a transcription activator. Apart from the contribution of EZH2 phosphorylation at serine 21, threonine 350, and threonine 311 in prostate cancer progression and treatment resistance, we discuss how other EZH2 phosphorylated residues with unknown functions could contribute to prostate cancer based on their upstream regulators and potential therapeutic utility.
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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 | 0.001 | 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".