Purpose: The detection of circulating tumor DNA (ctDNA) after curative-intent therapy in early-stage breast cancer is highly prognostic of disease recurrence. Current ctDNA assays, mainly targeting single-nucleotide variants, vary in sensitivity and specificity. Although increasing the number of single-nucleotide variants in tumor-informed assays improves sensitivity, structural variants (SV) may achieve similar or better sensitivity without compromising specificity. SVs occur across all cancers, linked to genomic instability and tumorigenesis, with unique tumor- and patient-specific breakpoints occurring throughout the genome. SVs in breast cancer are underexplored, and their potential for ctDNA detection and monitoring has not been fully evaluated. Experimental Design: We retrospectively analyzed a tumor-informed SV-based ctDNA assay in a cohort of patients with early-stage breast cancer (n = 100, 568 timepoints) receiving neoadjuvant systemic therapy, evaluating ctDNA dynamics and lead times to clinical recurrence in the postoperative period. Results: ctDNA was detected in 96% (91/95) of participants at baseline with a median variant allele frequency of 0.15% (range: 0.0011%–38.7%); of these, 10% (9/91) had a variant allele frequency <0.01%. ctDNA detection at cycle 2 (C2) of neoadjuvant therapy was associated with a higher likelihood of distant recurrence (log-rank P = 0.047) and enhanced residual cancer burden prognostication (log-rank P = 0.041). ctDNA was detected prior to distant recurrence in all cases (100% sensitivity) with a median lead time of 417 days (range: 4–1,931 days). Conclusions: These results demonstrate the clinical validity of ultrasensitive ctDNA detection and monitoring using SVs. Prospective trials are required to evaluate ctDNA-guided treatment strategies.

Early-stage breast cancer (BC) is a curable disease with many patients dying of causes other than BC. The influence of non-BC death and other competing risks on the interpretation of Kaplan-Meier (KM)-based analyses for BC-specific outcomes are unknown. We searched the Oxford University website to identify all meta-analyses published by the Early Breast Cancer Trialists Collaborative Group (EBCTCG) between 2005 and 2018. The potential influence of competing risks was estimated using a validated multivariable linear model that predicts the difference between KM and cumulative incidence function (CIF) on estimates of BC-specific outcomes. The initial search identified 14 EBCTCG papers, 10 (71%) reported data on BC and competing events. Eight (80%) had a relative difference between KM and the competing risk adjusted estimates exceeding 10%. The median relative difference was 28.4% for local-recurrence; 16.8% for distant-recurrence, and 6.7% for BC-specific mortality. There was a 18.9% relative difference between KM and CIF adjusted analyses beyond 10 years. The use of KM-based methods when competing risks are present biases risk estimates in studies of early BC especially for uncommon outcomes such as local recurrence. The use of CIF to calculate BC-specific outcomes may be preferable in this setting.