AcornHRD: an HRD algorithm highly associated with anthracycline-based neoadjuvant chemotherapy in breast cancer in China.

PURPOSE

Our study aimed to develop and validate a homologous recombination deficiency (HRD) scoring algorithm in the Chinese breast cancer population.

METHODS AND MATERIALS

Ninety-six in-house breast cancer (BC) samples and 6 HRD-positive standard cells were analyzed by whole-genome sequencing (WGS). Besides, 122 BCs from the TCGA database were down-sampled to ~ 1X WGS. We constructed an algorithm named AcornHRD for HRD score calculated based on WGS at low coverage as input data to estimate large-scale copy number alteration (LCNA) events on the genome. A clinical cohort of 50 BCs (15 cases carrying BRCA mutation) was used to assess the association between HRD status and anthracyclines-based neoadjuvant treatment outcomes.

RESULTS

A 100-kb window was defined as the optimal size using 41 in-house cases and the TCGA dataset. HRD score high threshold was determined as HRD score ≥ 10 using 55 in-house BCs with BRCA mutation to achieve a 95% BRCA-positive agreement rate. Furthermore, the HRD status agreement rate of AcornHRD is 100%, while the ShallowHRD is 60% in standard cells. BRCA mutation was significantly associated with a high HRD score evaluated by AcornHRD and ShallowHRD (p = 0.008 and p = 0.003, respectively) in the TCGA dataset. However, AcornHRD showed a higher positive agreement rate than did the ShallowHRD algorithm (70% vs 60%). In addition, the BRCA-positive agreement rate of AcornHRD was superior to that of ShallowHRD (87% vs 13%) in the clinical cohort. Importantly, the high HRD score assessed by AcornHRD was significantly correlated with a residual cancer burden score of 0 or 1 (RCB0/1). Besides, the HRD-positive group was more likely to respond to anthracycline-based chemotherapy than the HRD-negative group (pCR [OR = 9.5, 95% CI 1.11-81.5, p = 0.040] and RCB0/1 [OR = 10.29, 95% CI 2.02-52.36, p = 0.005]).

CONCLUSION

Using the AcornHRD algorithm evaluation, our analysis demonstrated the high performance of the LCNA genomic signature for HRD detection in breast cancers.