Abstract 118: A comprehensive profile of the genomic architecture of curable prostate cancer
Bibliographic record
Abstract
Abstract There is an urgent need to develop novel biomarkers of treatment response for precision medicine in prostate cancer, particularly in the setting of localized, non-indolent disease, which represents the vast majority of cases at initial clinical presentation. The Canadian Prostate Cancer Genome Network (CPC-GENE) - a member of the International Cancer Genome Consortium - aims to identify multi-modal prognostic and predictive signatures of therapeutic outcome based on intrinsic tumour genomics, transcriptomics, and epigenomics, which are being incorporated into novel clinical trials of treatment escalation/de-escalation for image-guided radiotherapy and/or radical prostatectomy. Herein we report the results of the largest prostate cancer whole-genome sequencing study to date, consisting of 194 patients and whole-exome sequencing of 479 patients with localized, potentially curable disease; a sample size that allows for saturating discovery of genes mutated at ≥1% frequency. We show that tumours treated by curative local therapy have a paucity of clinically-actionable mutations relative to high-risk localized or metastatic disease, but instead harbor a significant number of recurrent non-coding aberrations and genomic rearrangements, including a novel inversion - and an associated reduction in gene expression - of the PTEN tumour suppressor gene on chromosome 10. The median tumour contains three distinct driver mutations, with >86% of tumours possessing at least one known driver. Importantly, multiple driver aberrations are associated with patient outcome, including copy number aberrations and methylation events, but notably excluding well-described recurrent events such as TMPRSS2:ERG fusions and SPOP point mutations. Localized hypermutation events (e.g. kataegis) were detected in >20% of tumours, and were strongly enriched for aggressive disease. Taken together, these data provide a comprehensive analysis of the genomic landscape of localized, non-indolent prostate cancer. Moreover, our results strongly suggest that specific molecular aberrations may serve as useful biomarkers for improved pre-treatment stratification of patients with localized, low/intermediate risk disease into escalation/de-escalation protocols, and support the development of clinical trials to assess this hypothesis, based on patient-specific molecular profiles. Citation Format: Michael E. Fraser, Theodorus van der Kwast, John McPherson, Colin C. Collins, Yves Fradet, Bernard Tetu, Alain Bergeron, Rob G. Bristow, Paul C. Boutros. A comprehensive profile of the genomic architecture of curable prostate cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 118.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".