Construction of a Tissue Microarray for Validation of EphA2 Receptor as a Prostate Cancer Biomarker
Bibliographic record
Abstract
Introduction: Prostate cancer is the most common non-cutaneous male cancer, with an increasing incidence secondary to PSA use.There remains much uncertainty regarding its natural history, and thus further uncertainty surrounding treatment with subsequent under-and over-treatment.There is an association with diet, particularly diets high in 6 polyunsaturated fatty acids such as arachidonic acid.Arachidonic acid may promote the metastasis-like behaviour of epithelial to mesenchymal transition of prostate cancer cells via the EphA2 pathway.In an initial study, EphA2 expression was shown to correlate in prostate cancer specimens to overall survival suggesting use as a biomarker.The aim of this project was to construct a new tissue microarray for validation of EphA2 as a biomarker.Methods: Electronic patient records were reviewed to update the Salford Royal Prostate Cancer database.Samples were identified from the Salford Royal Prostate Cancer tissue bank.H&E slides were reviewed to identify areas of prostate cancer to be isolated for construction of a new tissue microarray.An immunofluorescence protocol using the Ventana system was optimised to assess EphA2 expression.Results: A total of 296 patients were included within the new tissue microarray.Sample size calculations showed that this is of a sufficient size to validate earlier findings regarding overall survival, metastatic disease, and biochemical progression, but not prostate cancer death.The validation cohort was comparable both with the original tissue microarray cohort in terms of age, stage, Gleason score, biochemical progression, and overall survival.Results were also comparable to national data.Discussion: EphA2 has shown potential to be a prostate cancer biomarker to predict for overall survival, metastasis, and biochemical progression.This project has resulted in the construction of a sufficiently sized new tissue microarray from patients with prostate cancer TRUS biopsies at the time of diagnosis with an extensive follow-up.This may potentially be used to validate initial findings but also act as a resource for assessment of future prostate cancer biomarkers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".