Abstract 4670: A novel companion diagnostic predicts response to the PARP inhibitor rucaparib in ovarian cancer
Bibliographic record
Abstract
Abstract Background: Genomic studies suggest that ∼50% of high-grade serous ovarian cancers (OC) have homologous recombination deficiency (HRD). Germline BRCA1/2 mutations (gBRCAmut) are expected to account for 1/3 of HRD in OC, and identification of non-gBRCAmut HRD tumors likely to respond to PARP inhibitors (PARPi) remains a challenge. Using comprehensive next generation sequencing (NGS)-based tumor genomic profiling, we developed a companion diagnostic HRD assay to predict sensitivity to the PARP inhibitor rucaparib by combining tumor BRCA1/2 status (germline and somatic) and genomic loss of heterozygosity (LOH). The HRD assay is being validated in a Phase 2 study (ARIEL2) and will be prospectively applied to the primary analysis of the ongoing Phase 3 study (ARIEL3) of rucaparib. Methods: The HRD assay uses 50-200ng of DNA from tumor FFPE specimens, which undergoes sequencing library construction and hybrid-capture of all coding exons from 100s of cancer-related genes. Libraries are sequenced to high, uniform depth (>500× unique coverage, Illumina® HiSeq) and data are processed by a customized pipeline that accurately detects all classes of genomic alterations, including BRCA1/2 base substitutions, indels, and homozygous deletions. Genomic LOH is assessed by a CGH-like analysis of sequencing coverage and >3,500 genome-wide SNPs and a tumor is classified as HRD with either BRCA1/2 alteration or high genomic LOH (LOH+). Somatic/germline status of discovered BRCA1/2 alterations is assessed by a previously-presented computational approach (“SGZ”, AACR 2014 abstract #1893), and verified against medical records where available. ARIEL2 is an ongoing single-arm (n = 180), open-label study of rucaparib in recurrent, platinum-sensitive OC patients. The primary objective is to evaluate clinical activity of rucaparib among 3 prospectively defined subgroups: tumor BRCAmut, BRCAwt/LOH+ (“BRCAness”) and BRCAwt/LOH-. Response is determined by RECIST and/or GCIG-CA125 criteria. Results: The HRD assay was performed on tumors from 121 patients, of whom 25% were found to be BRCA mutant (17 germline/12 somatic), 42% had the BRCAness signature (BRCAwt/LOH+), and 33% were biomarker negative (BRCAwt/LOH-). Efficacy data available for 61 patients revealed objective response rates (combined RECIST/CA125 criteria) at 70%, 40% and 8%, respectively. Responses were observed for all classes of genomic alterations, and in gBRCAmut and non-gBRCAmut tumors. Conclusions: Preliminary clinical data indicates that the HRD assay identifies OC patients likely to respond to rucaparib and highlights the potential for innovative companion diagnostics enabled by comprehensive genomic profiling based on NGS. Citation Format: James Sun, Iain McNeish, Robert L. Coleman, Amit Oza, Clare Scott, David M. O'Malley, Kevin K. Lin, Christine Burns, Christine Vietz, Philip J. Stephens, Murtaza Mehdi, Matthew Hawryluk, Heidi Giordano, Mitch Raponi, Lindsey Rolfe, Jeff Isaacson, Vincent A. Miller, Andrew Allen, Elizabeth Swisher, Roman Yelensky. A novel companion diagnostic predicts response to the PARP inhibitor rucaparib in ovarian cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4670. doi:10.1158/1538-7445.AM2015-4670
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".