Validation of the Clinical Use of GIScar, an Academic-developed Genomic Instability Score Predicting Sensitivity to Maintenance Olaparib for Ovarian Cancer
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
- Klinik und Poliklinik für Frauenheilkunde und Geburtshilfe
- Laboratoire de Biologie et de Génétique du Cancer
- Experimental and Clinical Research Center (ECRC)
- Unité d'Oncologie Moléculaire Humaine
- Département de Génétique Médicale
- Unité de Génomique Fonctionnelle
- Service de Génétique des Tumeurs
- Medizinische Universität Innsbruck
- Clinica Universidad de Navarra (CUN)
- DKMS Clinical Trials Unit gGmbH
- MVZ Onko Medical GmbH Hannover
- Institut Gustave Roussy
- Association de Recherche Cancers Gynécologiques (ARCAGY)
- GINECO - Groupe d'Investigateurs Nationaux pour l'Etude des Cancers Ovariens et du sein
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.
Details
Originalsprache | Englisch |
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Seiten (von - bis) | 4419-4429 |
Seitenumfang | 11 |
Fachzeitschrift | Clinical Cancer Research |
Jahrgang | 29 |
Ausgabenummer | 21 |
Publikationsstatus | Veröffentlicht - 1 Nov. 2023 |
Peer-Review-Status | Ja |
Externe IDs
PubMedCentral | PMC10618649 |
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Scopus | 85175742052 |
Schlagworte
Ziele für nachhaltige Entwicklung
Schlagwörter
- Humans, Female, Poly(ADP-ribose) Polymerase Inhibitors/therapeutic use, Ovarian Neoplasms/drug therapy, Phthalazines/therapeutic use, Genomic Instability