The Genomic Landscape of Early-Stage Ovarian High-Grade Serous Carcinoma

Abstract

Purpose: Ovarian high-grade serous carcinoma (HGSC) is usually diagnosed at late stage. We investigated whether late-stage HGSC has unique genomic characteristics consistent with acquisition of evolutionary advantage compared with early-stage tumors.

Experimental design: We performed targeted next-generation sequencing and shallow whole-genome sequencing (sWGS) on pretreatment samples from 43 patients with FIGO stage I-IIA HGSC to investigate somatic mutations and copy-number (CN) alterations (SCNA). We compared results to pretreatment samples from 52 patients with stage IIIC/IV HGSC from the BriTROC-1 study.

Results: Age of diagnosis did not differ between early-stage and late-stage patients (median 61.3 years vs. 62.3 years, respectively). TP53 mutations were near-universal in both cohorts (89% early-stage, 100% late-stage), and there were no significant differences in the rates of other somatic mutations, including BRCA1 and BRCA2. We also did not observe cohort-specific focal SCNA that could explain biological behavior. However, ploidy was higher in late-stage (median, 3.0) than early-stage (median, 1.9) samples. CN signature exposures were significantly different between cohorts, with greater relative signature 3 exposure in early-stage and greater signature 4 in late-stage. Unsupervised clustering based on CN signatures identified three clusters that were prognostic.

Conclusions: Early-stage and late-stage HGSCs have highly similar patterns of mutation and focal SCNA. However, CN signature analysis showed that late-stage disease has distinct signature exposures consistent with whole-genome duplication. Further analyses will be required to ascertain whether these differences reflect genuine biological differences between early-stage and late-stage or simply time-related markers of evolutionary fitness. See related commentary by Yang et al., p. 2730.

Figure 1.

REMARK diagram for early-stage and late-stage cohorts.

Figure 2.

Clinical features and mutational landscape of early-stage and late-stage cohorts. A, Diagnosis age [median 61.3 years (early stage), 62.3 years (late stage); P = NS]. B, Overall survival. Median 60.3 months for late stage, and not reached for early stage. Log-rank. HR, 0.13 (95% CI, 0.07–0.26), P < 0.0001 (Log-rank). C, Short variants (SNV and indels) for each patient in early-stage and late-stage cohorts. The top plot shows the number of mutations in each tumor sample. D, Gene mutation mapper plot of TP53 in early-stage cohort and (E) late-stage cohort. Key hotspot residues are marked. The commonest residue mutations in each cohort are marked in red.

Figure 3.

Focal gene amplifications and deletions in early-stage and late-stage cohorts. A, Purity comparison of early-stage and late-stage cohorts. B, Ploidy comparison of early-stage and late-stage cohorts; Mann–Whitney test. C, Global CN amplifications, gains and losses in early-stage and late-stage cohorts. D, Estimation of focal amplifications and deletions in 17 genes of interest, determined by sWGS. The top plot shows the number of amplifications and deletions in each tumor sample.

Figure 4.

CN signatures in early-stage and late-stage cohorts. A, CN signature exposures in early-stage and late-stage patients. Note that signature exposures sum to 1 in each sample. Bars above signatures indicate adjacent samples derived from the same patient. B, Mean signature exposure proportions across the early-stage and late-stage cohorts. C, Comparison of signature exposures across early-stage and late-stage cohorts; Wald test. D, Overall survival of combined early-stage and late-stage cohorts by zero versus nonzero exposures to CN signature 3 (left) and 4 (right). Log-rank (Mantel–Cox) analysis. E, Simplex plots representing exposures for CN signature 3 (right axis), signature 4 (bottom axis), and the rest of the signatures (–S3–S4) combined (left axis) in early-stage (left) and late-stage (right) cohorts. Each red dot represents a single sample, and the contours represent the density of observed samples.

Figure 5.

Relationship between signature exposures and clinical factors. A, Unsupervised hierarchical clustering in combined early-stage and late-stage cohorts. B, Distributions of CN signature exposures in three clusters. C, Early-stage and late-stage samples by cluster; chi-square test. D, Overall survival by cluster. Log-rank for trend. E, Forest plot of HR estimates on overall survival (OS) for clusters. Cox proportional hazards.

Figure 6.

Cluster ploidy and WGD. A, Ploidy distribution of late-stage samples in three clusters. Kruskal–Wallis test. B, Correlation between CN signature 4 exposure and ploidy across both cohorts. Spearman rank correlation. C, Fraction of CN segments with absolute CN ≥3 in three clusters. Kruskal–Wallis test. D, CN changepoint. Graphic depiction of CN changepoint (left); distribution of CN changepoint ≥+2 in the three clusters. Kruskal–Wallis test (center); density distribution (right). E, Overall survival of combined early-stage and late-stage cohorts by ploidy. Log-rank for trend analysis.