Gerald Li

Effectiveness of PARP Inhibitor Maintenance Therapy in Ovarian Cancer by BRCA1/2 and a Scar-Based HRD Signature in Real-World Practice

Abstract Purpose: The purpose of the study was to compare the effectiveness of PARP inhibitor maintenance therapy (mPARPi) in real-world practice by biomarker status [BRCA1/2 alterations (BRCAalt) and a homologous recombination deficiency signature (HRDsig)] in advanced ovarian cancer. Experimental Design: Patients with ovarian cancer receiving first-line platinum-based chemotherapy and either mPARPi or no maintenance were included. Patient data were obtained by a US-based de-identified ovarian cancer Clinico-Genomic Database, from ∼280 US cancer clinics (01/2015–03/2023). Real-world progression-free survival (rwPFS) and overall survival (rwOS) were compared by biomarker status using Cox models, weighted by propensity scores. Results: Of 673 patients, 160 received mPARPi [31.2% BRCAalt and 51.9% HRDsig(+)] and 513 no maintenance [15.6% BRCAalt and 34.1% HRDsig(+)]. BRCAalt patients receiving mPARPi versus no maintenance had favorable rwPFS [HR, 0.48; 95% confidence interval (CI), 0.26–0.87; P = 0.0154], as did BRCA wild-type (WT; HR, 0.76; 95% CI, 0.57–1.01; P = 0.0595). Favorable rwOS was not observed with mPARPi for BRCAalt or BRCA-WT. HRDsig(+) patients receiving mPARPi versus no maintenance had favorable rwPFS (HR, 0.36; 95% CI, 0.24–0.55; P < 0.001) and numerically favorable rwOS (HR, 0.46; 95% CI, 0.21–1.02; P = 0.0561). No differences were observed for HRDsig(−). mPARPi treatment interaction was observed for HRDsig(+) versus HRDsig(−) (rwPFS P < 0.001/rwOS P = 0.016) but not for BRCAalt versus BRCA-WT. Patients with BRCA-WT/HRDsig(+) receiving mPARPi had favorable rwPFS (HR, 0.40; 95% CI, 0.22–0.72; P = 0.003), whereas no difference was observed for BRCA-WT/HRDsig(−). Conclusions: HRDsig predicted benefit of mPARPi better than BRCAalt. Patients with HRDsig(+) status experienced favorable outcomes, even if they had BRCA-WT status. In contrast, patients with HRDsig(−) status did not show significant benefit from mPARPi treatment. HRDsig might predict benefit from mPARPi regardless of BRCAalt status.

Validation of comprehensive genomic profiling for prognostic and potential therapeutic molecular classification of endometrial cancer

We sought to validate the prognostic utility of comprehensive genomic profiling (CGP)-based molecular stratification for patients with endometrial carcinoma and to assess co-occurring biomarkers across subtypes. This study included patients from a de-identified nationwide (US-based) endometrial cancer clinicogenomic database who underwent CGP testing as part of routine care. Molecular subtypes were classified as POLE mutated (POLEmut), MSI-H, TP53 mutated (TP53mut), and no specific molecular profile (NSMP). Time to next treatment and overall survival were compared between molecular subtypes, with multivariable Cox models adjusted for relevant covariables. Of 1,139 evaluated patients with advanced or recurrent endometrial carcinoma, the prevalence of the 4 molecular subtypes was 1% POLEmut, 22% high microsatellite instability, 47% TP53mut, and 31% NSMP. Compared with NSMP patients, POLEmut patients had numerically more favorable time to next treatment (HR 0.50, 95% CI 0.21 to 1.21) and overall survival (HR 0.52, 95% CI 0.17 to 1.66). High microsatellite instability patients had similar time to next treatment (HR 1.08, 95% CI 0.89 to 1.30) and overall survival (HR 0.91, 95% CI 0.71 to 1.19) relative to NSMP patients. TP53mut patients had the least favorable outcomes for time to next treatment (compared with NSMP, HR 1.39, 95% CI 1.19 to 1.62) and overall survival (HR 2.15, 95% CI 1.77 to 2.61). In multivariable analysis, TP53mut status was associated with less favorable time to next treatment and overall survival. Frequencies of other biomarkers varied by molecular subtype. The Cancer Genome Atlas (TCGA)/Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) molecular classifier for endometrial carcinoma can be recapitulated using CGP and provides prognostic stratification even within an advanced or recurrent disease cohort. CGP for molecular subclassification could support trial design and enrollment and inform treatment escalation or selection.