SETD7 functions as a transcription repressor in prostate cancer via methylating FOXA1
Bibliographic record
Abstract
Dysregulation of histone lysine methyltransferases and demethylases is one of the major mechanisms driving the epigenetic reprogramming of transcriptional networks in castration-resistant prostate cancer (CRPC). In addition to their canonical histone targets, some of these factors can modify critical transcription factors, further impacting oncogenic transcription programs. Our recent report demonstrated that LSD1 can demethylate the lysine 270 of FOXA1 in prostate cancer (PCa) cells, leading to the stabilization of FOXA1 chromatin binding. This process enhances the activities of the androgen receptor and other transcription factors that rely on FOXA1 as a pioneer factor. However, the identity of the methyltransferase responsible for FOXA1 methylation and negative regulation of the FOXA1-LSD1 oncogenic axis remains unknown. SETD7 was initially identified as a transcriptional activator through its methylation of histone 3 lysine 4, but its function as a methyltransferase on nonhistone substrates remains poorly understood, particularly in the context of PCa progression. In this study, we reveal that SETD7 primarily acts as a transcriptional repressor in CRPC cells by functioning as the major methyltransferase targeting FOXA1-K270. This methylation disrupts FOXA1-mediated transcription. Consistent with its molecular function, we found that SETD7 confers tumor suppressor activity in PCa cells. Moreover, loss of SETD7 expression is significantly associated with PCa progression and tumor aggressiveness. Overall, our study provides mechanistic insights into the tumor-suppressive and transcriptional repression activities of SETD7 in mediating PCa progression and therapy resistance.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".