Genomic alterations in intraductal prostate cancer: Insights from the Genomic Umbrella Neoadjuvant study (GUNS) in high-risk localized disease.
Bibliographic record
Abstract
417 Background: Intraductal carcinoma of the prostate (IDC) is an aggressive histological variant of prostate cancer, characterized by the presence of malignant cells within the prostatic ducts. Retrospective studies have shown IDC linked to higher tumor grades and odds of lymphatic metastasis and worse oncological outcomes. In patient derived xerograph models, IDC can persist after castration, with a subpopulation of castrate tolerant cells able to regenerate upon testosterone restoration. This suggests that IDC contributes to therapy resistance and highlights the need to understand molecular alterations of IDC. This study aims to evaluate genomic profiles of these tumors in the GUNS trial. Methods: From 9/2021 to 8/2024, GUNS enrolled 95 patients in Canada. Diagnostic biopsies underwent Tempus’ CLIA-certified 648-gene panel DNA sequencing. A total of 93 patients were evaluable for genomic alterations. Of those, 81 additionally had immunohistochemistry (IHC) staining for PTEN. All biopsy specimens were centrally reviewed by TvK. Associations between IDC and genomic alterations or PTEN IHC staining (positive vs. negative/heterogeneous) were assessed by Fisher’s exact test, and the false discovery rate (FDR) was controlled using the Benjamini-Hochberg method. Only genomic alterations annotated as biologically significant by Tempus were considered for analysis. Results: Of the 93 evaluable patients, 36 (39%) had IDC on biopsy. PTEN IHC status showed a significant association with IDC status, with negative or heterogeneous PTEN IHC staining being more prevalent among IDC-positive cases (p = 0.002; FDR q = 0.05). Specifically, PTEN IHC staining was negative/heterogeneous in 15/32 (47%) IDC-positive cases but only 7/49 (14%) IDC-negative cases. Genomic PTEN (22% vs. 7%) and TP53 (19% vs. 9%) alterations were also more common in IDC-positive cases than IDC-negative cases, although these trends were not statistically significant. Conversely, CDKN1B was exclusively altered in IDC-negative cases (0% vs. 9%), and BRCA2 alterations (germline or somatic) were also more frequent in IDC-negative cases (3% vs 11%), but these observations were also not statistically significant. Relatively low frequencies of genomic alterations were likely impediments to statistical significance, warranting larger sample sizes to assess these trends. Conclusions: Negative or heterogeneous PTEN IHC staining was more common in IDC-positive cases, consistent with the known association between PTEN loss and aggressive disease. PTEN IHC status, along with other genetic markers, may help to define subgroups within prostate cancer that differ in their underlying biology and response to neoadjuvant treatment. This highlights the importance of integrating molecular and histological data to better understand prostate cancer progression and to tailor therapeutic approaches.
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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) | 0.000 | 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) | 0.001 | 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".