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HRDetect in Tubo-ovarian Carcinoma: Stratification and Therapeutic Implications
Kalyan Banda1,2, Helen R Davies3, Yogesh Kumar3
1Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington.
Purpose:
To evaluate HRDetect, a mutational signature-based algorithm, for prognostic utility in tubo-ovarian carcinoma and to determine if whole-genome sequencing (WGS) with rearrangement signature (RS) analysis can refine genomic classification beyond the traditional homologous recombination-deficient versus homologous recombination-proficient framework.
Experimental Design:
WGS was performed on matched tumor-normal pairs from 185 patients with advanced-stage tubo-ovarian carcinoma from the University of Washington (UW) cohort. HRDetect scores were calculated using substitution signatures, RS, microhomology-mediated deletions, and global loss of heterozygosity. An independent validation cohort (ARIEL2, n = 77) of platinum-sensitive tubo-ovarian carcinoma treated with rucaparib was analyzed to correlate HRDetect with PARP inhibitor (PARPi) response. RS analysis and unsupervised hierarchical clustering were employed to delineate genomic subgroups.
Results:
In the UW cohort, 51.4% of cases were classified as HRDetect-high and had significantly prolonged median overall survival versus others [6.2 vs. 4.1 years; hazard ratio (HR), 0.6; 95% confidence interval (CI), 0.41-0.87; P = 0.007]. Furthermore, 48.4% of HRDetect-high tumors harbored BRCA1/2 mutations or BRCA1 promoter methylation, whereas 22.1% lacked BRCA1/2 alterations. A substantial fraction (23.2%) fell into an HRDetect-intermediate category, highlighting greater genomic heterogeneity than currently appreciated. RS profiling uncovered 11 genomic clusters, with specific RS profiles (RS1, RS14, and RS18) correlating with poor survival. In ARIEL2, HRDetect-high tumors showed better PARPi responses, with improved progression-free survival (11.1 vs. 7.1 months; HR, 0.44; 95% CI, 0.26-0.74; P = 0.03) and response rates (54% vs. 22.5%).
Conclusions:
HRDetect predicts survival and sensitivity to PARPi in tubo-ovarian carcinoma. Combined with RS-based clustering, it reveals unappreciated genomic heterogeneity and supports a nuanced stratification framework to improve precision oncology in tubo-ovarian carcinoma.
