High‐resolution array CGH identifies novel regions of genomic alteration in intermediate‐risk prostate cancer
Bibliographic record
Abstract
Approximately one-third of prostate cancer patients present with intermediate risk disease. Interestingly, while this risk group is clinically well defined, it demonstrates the most significant heterogeneity in PSA-based biochemical outcome. Further, the majority of candidate genes associated with prostate cancer progression have been identified using cell lines, xenograft models, and high-risk androgen-independent or metastatic patient samples. We used a global high-resolution array comparative genomic hybridization (CGH) assay to characterize copy number alterations (CNAs) in intermediate risk prostate cancer. Herein, we show this risk group contains a number of alterations previously associated with high-risk disease: (1) deletions at 21q22.2 (TMPRSS2:ERG), 16q22-24 (containing CDH1), 13q14.2 (RB1), 10q23.31 (PTEN), 8p21 (NKX3.1); and, (2) amplification at 8q21.3-24.3 (containing c-MYC). In addition, we identified six novel microdeletions at high frequency: 1q42.12-q42.3 (33.3%), 5q12.3-13.3 (21%), 20q13.32-13.33 (29.2%), 22q11.21 (25%), 22q12.1 (29.2%), and 22q13.31 (33.3%). Further, we show there is little concordance between CNAs from these clinical samples and those found in commonly used prostate cancer cell models. These unexpected findings suggest that the intermediate-risk category is a crucial cohort warranting further study to determine if a unique molecular fingerprint can predict aggressive versus indolent phenotypes.
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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) | 0.001 | 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".