<i>PTEN</i> genomic deletion is associated with p‐Akt and AR signalling in poorer outcome, hormone refractory prostate cancer
Bibliographic record
Abstract
PTEN haploinsufficiency is common in hormone-sensitive prostate cancer, though the incidence of genomic deletion and its downstream effects have not been elucidated in clinical samples of hormone refractory prostate cancer (HRPC). Progression to androgen independence is pivotal in prostate cancer and mediated largely by the androgen receptor (AR). Since this process is distinct from metastatic progression, we examined alterations of the PTEN gene in locally advanced recurrent, non-metastatic human HRPC tissues. Retrospective analyses of PTEN deletion status were correlated with activated downstream phospho-Akt (p-Akt) pathway proteins and with the androgen receptor. The prevalence of PTEN genomic deletions in transurethral resection samples of 59 HRPC patients with known clinical outcome was assessed by four-colour FISH analyses. FISH was performed using six BAC clones spanning both flanking PTEN genomic regions and the PTEN gene locus, and a chromosome 10 centromeric probe. PTEN copy number was also evaluated in a subset of cases using single nucleotide polymorphism (SNP) arrays. In addition, the samples were immunostained with antibodies against p-Akt, p-mTOR, p-70S6, and AR. The PTEN gene was deleted in 77% of cases, with 25% showing homozygous deletions, 18% homozygous and hemizygous deletions, and 34% hemizygous deletions only. In a subset of the study group, SNP array analysis confirmed the FISH findings. PTEN genomic deletion was significantly correlated to the expression of downstream p-Akt (p < 0.0001), AR (p = 0.025), and to cancer-specific mortality (p = 0.039). PTEN deletion is common in HRPC, with bi-allelic loss correlating to disease-specific mortality and associated with Akt and AR deregulation.
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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) | 0.002 | 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".