Abstract A109: Novel germline genetic variants in pseudogenes associated with overall survival in advanced stage ovarian cancer treated with carboplatin, paclitaxel, and bevacizumab: Results from the ROSiA trial
Bibliographic record
Abstract
Abstract Background: Current guidelines recommend the use of bevacizumab, a vascular endothelial growth factor (VEGF) inhibitor, for the treatment of epithelial ovarian cancer (EOC). However, predictive biomarkers for anti-angiogenic agents in gynecologic malignancies are currently limited. Emerging evidence suggests that inherited genetic information may play a role in influencing treatment outcomes under VEGF inhibition. Aim: We evaluated the role of inherited single nucleotide polymorphisms (SNPs) on overall survival (OS) in ROSiA, a single-arm, multinational, phase 3b clinical trial that explored the efficacy of bevacizumab combined with carboplatin and paclitaxel chemotherapy followed by maintenance bevacizumab in the frontline treatment of FIGO stage IIB-IV EOC. Methods: In this genome-wide association study (GWAS), germline DNA extracted from 405 ROSiA trial patients was genotyped using the Infinium OncoArray-500K BeadChip. Cox proportional-hazard models assessed the association of each SNP on OS, generating adjusted hazard ratios (aHR), 95% confidence intervals (CI), and p-values. All models assumed an additive inheritance model and were adjusted for relevant clinical variables, such as age, body surface area, FIGO stage, history of diabetes, and surgical debulking (primary or interval). Kaplan-Meier (KM) curves were generated to compare survival rates by genotypes of the significant SNPs identified from GWAS analysis. Results: After quality control, 399 patients with EOC were analyzed. The median age was 56 years [IQR 15.7]; 46% had FIGO stage IIIC disease, and 80% had undergone debulking surgery. Our analyses revealed two genetic markers in linkage disequilibrium that reached global GWAS significance (p<5E-08). The top signal was for a minor allele at rs7801321 which was associated with an aHR of 4.33 [95%CI: 2.77-7.19], p<5E-08) compared to the major allele. In KM analysis, the presence of a minor allele had a lower 2-year OS rate of 62.3% [95%CI: 48.5-80.1%] compared to the wildtype genotype, which had a 2-year OS of 87.8% [95%CI: 84.2-91.5%]. Progression-free survival (PFS) curves at 2 years revealed a similar pattern, with the presence of a minor allele showing a PFS rate of 40.0% [95%CI: 27.0-60.0%] compared to the wildtype genotype of 56.2% [95%CI: 50.9-62.1%]. These two SNPs correspond to the eukaryotic translation elongation factor 1 gamma gene. This gene is a member of the pseudogene family of eukaryotic translation elongation factors, which have been implicated in the pathogenesis and progression of various malignancies, including ovarian cancer. Conclusion: Our GWAS analysis identified novel genetic markers associated with reduced OS in advanced EOC patients treated with bevacizumab. We are currently evaluating options to replicate these findings in other clinical trial datasets that have investigated the benefit of bevacizumab in ovarian cancer. Citation Format: Salahaldin Alamleh, Robert Grant, Wei Xu, Osvaldo Espin-Garcia, Helen MacKay, Geoffrey Liu. Novel germline genetic variants in pseudogenes associated with overall survival in advanced stage ovarian cancer treated with carboplatin, paclitaxel, and bevacizumab: Results from the ROSiA trial [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A109.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".