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Validation of the Clinical Use of GIScar, an Academic-developed Genomic Instability Score Predicting Sensitivity to Maintenance Olaparib for Ovarian Cancer. | LitMetric

AI Article Synopsis

  • - The study aims to improve access to testing for homologous recombination deficiency (HRD) in ovarian cancer by developing a new academic test called GIScar, which is based on a targeted gene panel analysis.
  • - GIScar was validated using tumor samples from a clinical trial and showed a strong correlation with an existing HRD test, Myriad Genetics MyChoice, while identifying more HRD-positive tumors and yielding fewer inconclusive results.
  • - The results indicate that GIScar is an effective diagnostic tool that not only detects HRD reliably but also predicts treatment response to the drug olaparib, making it a practical option for labs in need of rapid testing solutions.

Article Abstract

Purpose: The optimal application of maintenance PARP inhibitor therapy for ovarian cancer requires accessible, robust, and rapid testing of homologous recombination deficiency (HRD). However, in many countries, access to HRD testing is problematic and the failure rate is high. We developed an academic HRD test to support treatment decision-making.

Experimental Design: Genomic Instability Scar (GIScar) was developed through targeted sequencing of a 127-gene panel to determine HRD status. GIScar was trained from a noninterventional study with 250 prospectively collected ovarian tumor samples. GIScar was validated on 469 DNA tumor samples from the PAOLA-1 trial evaluating maintenance olaparib for newly diagnosed ovarian cancer, and its predictive value was compared with Myriad Genetics MyChoice (MGMC).

Results: GIScar showed significant correlation with MGMC HRD classification (kappa statistics: 0.780). From PAOLA-1 samples, more HRD-positive tumors were identified by GIScar (258) than MGMC (242), with a lower proportion of inconclusive results (1% vs. 9%, respectively). The HRs for progression-free survival (PFS) with olaparib versus placebo were 0.45 [95% confidence interval (CI), 0.33-0.62] in GIScar-identified HRD-positive BRCA-mutated tumors, 0.50 (95% CI, 0.31-0.80) in HRD-positive BRCA-wild-type tumors, and 1.02 (95% CI, 0.74-1.40) in HRD-negative tumors. Tumors identified as HRD positive by GIScar but HRD negative by MGMC had better PFS with olaparib (HR, 0.23; 95% CI, 0.07-0.72).

Conclusions: GIScar is a valuable diagnostic tool, reliably detecting HRD and predicting sensitivity to olaparib for ovarian cancer. GIScar showed high analytic concordance with MGMC test and fewer inconclusive results. GIScar is easily implemented into diagnostic laboratories with a rapid turnaround.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10618649PMC
http://dx.doi.org/10.1158/1078-0432.CCR-23-0898DOI Listing

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