Abstract 2722: The genomic landscape of high-grade serous ovarian cancer in long-term survivors
Bibliographic record
Abstract
Abstract Purpose: The majority of patients with high-grade serous ovarian cancer (HGSC) develop progressive disease following primary treatment, with a five-year survival rate of ~30%. However, a subset of patients have an extraordinary response to treatment and ~15% survive more than ten years (long-term survivors). The Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) aims to uncover factors that influence long-term survival of HGSC patients. Here, we investigated the genomic and immunologic determinants of exceptional survival of this deadly disease. Experimental Design: Patient characteristics and clinical histories were evaluated to identify patients diagnosed with advanced stage (Stage IIIC/IV) and histopathologically confirmed HGSC with greater than 10-year overall survival. Whole-genome sequencing (WGS) was performed on primary tumors (median 78x coverage) and germline samples (median 39x coverage) of 55 long-term survivors. Primary tumor samples were also characterised by RNA sequencing, DNA methylation profiling and immunohistochemistry. Results: A total 38 (69%) of long-term surviving patients had residual disease following surgery, suggestive of highly chemo-sensitive disease. Most patients (41, 75%) were alive at last follow-up and 26 (47%) were progression-free. Somatic mutation burden was higher in primary tumors of long-term survivors relative to controls (316 unselected HGSC patients in The Cancer Genome Atlas). Genome-wide mutational signatures were predominantly Signature 3 (associated with homologous recombination deficiency), Signature 1 (age related) and Signatures 5, 8 and 16 (unknown etiology). Inactivation of the tumor suppressor RB1 by structural rearrangements or homozygous deletion was frequent in long-term survivors, with 33% of tumors showing associated loss of RB1 protein expression by immunohistochemistry compared to 13% of unselected HGSC controls (n=207; P = 0.001). Staining of adjacent tumor tissue revealed that RB1 loss was associated with increased numbers of PD-1+ tumor-infiltrating lymphocytes (P = 0.015) and MHC class I on tumor cells (P = 0.002). In an independent HGSC cohort (n=847), RB1 protein loss was associated with prolonged survival (HR: 0.75, P < 0.001) compared to patients with RB1 positive tumors. Furthermore, co-occurrence of germline mutations in BRCA1 or BRCA2 and RB1 loss was associated with a significantly longer overall survival compared to patients with retained RB1 protein expression and no germline BRCA mutation (HR: 0.44, P < 0.001). Conclusions: This study delineates the full landscape of genomic alterations in HGSC of long-term survivors. Our findings indicate that specific mutations might be associated with enhanced host immune responses and long-term survival. Citation Format: Dale W. Garsed, Ahwan Pandey, Sian Fereday, Kathryn Alsop, Maartje C. Wouters, Flurina Saner, Jessica A. Beach, Katy Milne, Catherine J. Kennedy, Joy Hendley, Nadia Traficante, Celeste L. Pearce, Malcolm C. Pike, Multidisciplinary Ovarian Cancer Outcomes Group, Susan J. Ramus, Martin Köbel, Brad H. Nelson, Ellen L. Goode, Anna deFazio, David D. Bowtell. The genomic landscape of high-grade serous ovarian cancer in long-term survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2722.
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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 | 0.000 | 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) | 0.002 | 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".