PACE4-altCT isoform of proprotein convertase PACE4 as tissue and plasmatic biomarker for prostate cancer
Bibliographic record
Abstract
The proprotein convertase PACE4 has demonstrated value as a viable therapeutic target in prostate cancer (PCa). A novel isoform named PACE4-altCT, which arises in neoplastic lesions, plays an important role in tumor progression and has been validated as a pharmacological target. With the discovery of its overexpression in PCa and the alternative splicing of its pre-RNA to generate an oncogenic C-terminally modified isoform named PACE4-altCT, understanding and validating its value as a potential biomarker is of great interest either from prognostic or targeted therapy intervention. Expression of ERG in LNCaP cells was used to investigate the relationship between ERG expression occurring in PCa cells and PACE4-altCT expression by Western blot and qPCR. Using immunohistochemistry, the expression levels of PACE4 isoforms in patient tissues were investigated and correlated with ERG tumor status and Gleason score. An ELISA method was developed using affinity purified recombinant protein and used for quantitative analysis of plasma concentrations of PACE4-altCT and used for correlation. In contrast with the consensual isoform, PACE4-altCT was only strongly overexpressed in prostate cancer patients, correlated with ERG expression levels. Despite its intracellular retention PACE4-altCT could be detected in the plasma of most patients with prostate cancer, whereas it was only found at low levels in normal patients whereas total plasmatic PACE4 levels did not vary significantly between groups. Our study demonstrates that PACE4-altCT is strongly overexpressed in prostate cancer using both immunohistochemical and ELISA techniques and may have some interesting potential as a biomarker.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".