Genomic Deletion at 10q23 in Prostate Cancer: More Than PTEN Loss?
Bibliographic record
Abstract
The PTEN gene encodes for the phosphatase and tensin homolog; it is a tumour suppressor gene that is among the most frequently inactivated genes throughout the human cancer spectrum. The most recent sequencing approaches have allowed the identification of PTEN genomic alterations, including deletion, mutation, or rearrangement in about 50% of prostate cancer (PCa) cases. It appears that mechanisms leading to PTEN inactivation are cancer-specific, comprising gene mutations, small insertions/deletions, copy number alterations (CNA), promoter hypermethylation, and RNA interference. The examination of publicly available results from deep-sequencing studies of various cancers showed that PCa appears to be the only cancer in which PTEN is lost mostly through CNA. Instead of inactivating mutations, which are seen in other cancers, deletion of the 10q23 locus is the most common form of PTEN inactivation in PCa. By investigating the minimal deleted region at 10q23, several other genes appear to be lost simultaneously with PTEN. Expression data indicate that, like PTEN, these genes are also downregulated upon loss of 10q23. These analyses raise the possibility that 10q23 is lost upon selective pressure not only to inactivate PTEN, but also to impair the expression of surrounding genes. As such, several genes from this deleted region, which represents about 500 kb, may also act as tumour suppressors in PCa, requiring further studies on their respective functions in that context.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".