Early mRNA Expression of Neuroendocrine Differentiation Signals Predicts Recurrence After Radical Prostatectomy: A Transcriptomic Analysis
Bibliographic record
Abstract
BACKGROUND: Neuroendocrine differentiation (NED) of prostate cancer (PC) is a process that often occurs under evolutionary pressure from pharmacologic blockade of androgen receptor signaling at advanced stages of the disease. Identifying a subset of early PC that has a higher likelihood to evolve into this entity is key for developing therapeutic strategies that could more effectively target this phenotype. This study aimed to assess the prognostic relevance of mRNA expression of major players involved in NED of primary prostate tumors. METHODS: RNA sequencing data from 122 patients with localized PC were analyzed. Transcript levels of key genes involved in NED, with a focus on endothelin axis and nuclear factor kappa B (NF-κB), were assessed and were correlated with time to prostate specific antigen (PSA) recurrence. Copy number alteration of tumor suppressor genes and gene expression of additional signals hallmarking NED was compared between altered and unaltered groups, including lineage determining transcription factors, transcriptional repressors, cell cycle and epigenetic regulators. RESULTS: The presence of altered mRNA expression using a z-score threshold of 2 in NFKB1, RELA, EDN1, EDNRA, and EDNRB genes was associated with a higher Gleason score (P < 0.001) and a shorter time to biochemical recurrence (BCR) (P = 0.029). There was a significant direct correlation between NFKB1 and RELA (P < 0.001), NFKB1 and EDNRA (P < 0.001), NFKB1 and EDNRB (P < 0.001), EDNRA and EDNRB expression (P < 0.001). ASCL1 (q < 0.001), ONECUT2 (q < 0.001), DLL3 (q = 0.019), AURKA (q = 0.013), AURKB (q = 0.014), PLK1 (q < 0.001), and EZH2 (q < 0.001) were enriched in patients with tumors harboring alterations in endothelin axis and NF-κB subunit genes whereas REST was downregulated (q < 0.001). CONCLUSIONS: This analysis suggests that altered mRNA expression of NF-κB and endothelin axis genes in early PC is not only a harbinger of a more aggressive clinical course but is also associated with aberrant gene expression of several transcription factors, transcriptional repressors, cell cycle and epigenetic regulators that are directly involved in NED, in line with their biological roles. This may have implications for closer follow-up and potential use of targeted therapeutic approaches postoperatively in the adjuvant setting to improve outcomes of these patients.
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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 | 0.001 |
| 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".