Elevated XPO6 expression as a potential prognostic biomarker for prostate cancer recurrence
Bibliographic record
Abstract
Recurrence of localized prostate cancer following treatment can lead to lethal metastatic castration-resistant prostate cancer. Although numerous studies aimed at developing biomarkers for predicting recurrence of localized prostate cancer are promising, they have not yet led to useful applications. Dysregulation of exportins (XPOs, nucleocytoplasmic transporters) associated with subcellular mislocalization of proteins has been reported for various human cancers. However, most of the XPOs have not been studied in prostate cancer. In this study, we are the first to examine whether changes in expression of XPOs could be used as potential biomarkers for recurrence of localized prostate cancer. Using the oncomine database, gene expressions of 7 known XPOs by 1128 patient samples, obtained from 16 independent prostate cancer patient cohorts, were analyzed. Relatively highly elevated expression of XPO6 (compared to prostate cancer tissue) was found to be significantly associated with poor patient prognosis, in particular, with rapid recurrence in a clinical low risk group. As such, expression of XPO6 may be a potential prognostic biomarker for predicting prostate cancer recurrence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".