Assessment of homologous recombination deficiency phenotype in breast cancers in adolescents and young adults in the clinical setting

Background Homologous recombination deficiency (HRD), which may be associated with high efficacy of PARP inhibitor- and platinum agent-based therapies, is a prevalent phenotype of breast cancer diagnosed in adolescents and young adults (AYAs; 15–39 years old). HRD score, indicating HRD status, is not routinely assessed in the oncology clinic due to the need for genome-wide analyses. Methods Subjects were a Japanese cohort of 46 AYA breast cancer patients, whose HRD scores were calculated from whole-exome sequencing data, and two existing breast cancer cohorts (US and European) for which HRD scores were available. Genetic and clinicopathological factors associated with the HRD-high phenotype, defined as HRD score ≥42, were selected based on the criterion that they be assessible by routine examinations qualifying for insurance reimbursement. A model for prediction of the HRD-high phenotype was constructed and validated using data from the three cohorts. Results In the Japanese AYA cohort, as in the US and European cohorts, HRD-high phenotype (13/46, 28.3%) was preferentially observed in cases with any or combination of germline BRCA1/2 mutations, somatic TP53 mutations, triple-negative subtype, and higher tumor grades. Because these four factors can be assessed by routine examination that qualifies for insurance reimbursement, we developed a model based on these factors to judge whether a case is HRD-high, using the US cohort (n = 744; Area under the curve [AUC] = 0.85). The predictive power of the model was validated in the Japanese (n = 46; AUC = 0.90) and European (n = 58; AUC = 0.96) AYA cases. A model developed using the European cohort (n = 477; AUC = 0.89) had similar predictive power in Japanese (AUC = 0.89) and US (n = 54; AUC = 0.87) AYA cohorts. Conclusions The HRD-high phenotype of AYA breast cancer can be deduced based on genomic and pathological factors that are routinely examined in the oncology clinic. The predictive model presented here could increase the fraction of AYA breast cancer patients who could benefit from PARP inhibitor­- and platinum agent-based therapies.