Abstract 4305: Germline structural variants shape prostate cancer clinical and molecular evolution
Bibliographic record
Abstract
Abstract Inherited genetic variation profoundly influences cancer risk and outcome. While the impact of germline single nucleotide polymorphisms has been well-studied in several cancer types, the effects of germline structural variants (gSVs) on cancer biology and clinical outcomes is largely unknown. From our cohort of 300 men with localized, intermediate risk prostate cancer, we identified 6,003 gSVs present in at least 3% of patients; 48 were associated with recurrent somatic alterations or clinical outcome. Of these, approximately 50% were associated with expression of nearby genes or intersected with exons or regulatory regions. Using external cohorts, we validated three gSVs that were strongly associated with poor clinical outcomes, including an inversion at chr14q24.1 present in ~20% of patients. Notably, a strong synergistic effect on outcome was observed in patients with somatic TP53 alterations or high genomic instability, defining a new aggressive prostate cancer subtype with chr14INV as a novel, recurrent biomarker. Citation Format: Nicholas K. Wang, Alexandre Rouette, Kathleen E. Houlahan, Takafumi N. Yamaguchi, Julie Livingstone, Chol-Hee Jung, Peter Georgeson, Michael Fraser, Yu-Jia Shiah, Cindy Q. Yao, Vincent Huang, Natalie S. Fox, Natalie Kurganovs, Katayoon Kasaian, Veronica Y. Sabelnykova, Jay Jayalath, Kenneth Weke, Helen Zhu, Theodorus van der Kwast, Tony Papenfuss, Housheng H. He, Niall M. Corcoran, Robert G. Bristow, Alexandre R. Zlotta, Christopher Hovens, Paul C. Boutros. Germline structural variants shape prostate cancer clinical and molecular evolution. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4305.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".