Cleavage and Polyadenylation-Specific Factor 4 (CPSF4) Expression Is Associated with Enhanced Prostate Cancer Cell Migration and Cell Cycle Dysregulation, In Vitro
Bibliographic record
Abstract
Potential oncogene cleavage and polyadenylation specific factor 4 (CPSF4) has been linked to several cancer types. However, little research has been conducted on its function in prostate cancer (PCa). In benign, incidental, advanced, and castrate resistant PCa (CRPCa) patient samples, protein expression of CPSF4 was examined on tissue microarray (TMAs) of 353 PCa patients using immunohistochemistry. Using the 'The Cancer Genome Atlas' Prostate Adenocarcinoma (TCGA PRAD) database, significant correlations were found between high CPSF4 expression and high-risk genomic abnormalities such as ERG-fusion, ETV1-fusion, and SPOP mutations. Gene Set Enrichment Analysis (GSEA) of CPSF4 revealed evidence for the increase in biological processes such as cellular proliferation and metastasis. We further examined the function of CPSF4 in vitro and confirmed CPSF4 clinical outcomes and its underlying mechanism. Our findings showed a substantial correlation between Gleason groups and CPSF4 protein expression. In vitro, CPSF4 knockdown reduced cell invasion and migration while also causing G1 and G2 arrest in PC3 cell lines. Our findings demonstrate that CPSF4 may be used as a possible biomarker in PCa and support its oncogenic function in cellular proliferation and metastasis.
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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 | 0.001 | 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".