Clinical Application of Next-Generation Sequencing in Patients With Breast Cancer: Real-World Data

Next-generation sequencing (NGS)-based tumor panel testing has been reimbursed by the Korean government since 2017. We evaluated the use of NGS-based tumor panel testing in real-world clinical practice, focusing on molecular profiling (MP)-guided breast cancer treatment.

A total of 137 breast cancer patients underwent NGS panel testing between December 2017 and July 2020 at Seoul National University Bundang Hospital (SNUBH). Samples from patients were profiled using an in-house SNUBH pan-cancer panel. Sixty-four patients were profiled on SNUBH Pan_Cancer v1.0, targeting 89 genes, while 73 patients were profiled on SNUBH Pan_Cancer v2.0, targeting 546 genes.

Breast cancer subtypes included hormone receptor+/human epidermal growth factor receptor 2 (HER2)- (n = 87), triple-negative (n = 44), and HER2+ (n = 6). Most patients had locally advanced or metastatic cancers (92%). Approximately 92% (126/137) of the patients had significant genomic alterations (tiers I and II), and 62% (85/137) had targetable genomic alterations. The most common targetable genomic alterations were PIK3CA (39%) and ESR1 mutations (9%), followed by ERBB2 (7%), PTEN (7%), BRCA2 (6%), and BRCA1 mutations (4%). Of the 81 patients with locally advanced/metastatic breast cancer with targetable genomic alterations, 6 (7.4%) received MP-guided treatments, including PARP inhibitor (n = 4), ERBB2-directed therapy (n = 1), and PI3K inhibitor (n = 1). Among these 6 patients, 4 participated in clinical trials, 1 underwent treatment at their own expense, and 1 received drugs through an expanded access program. The remaining 66 patients (81%) with targetable genomic alteration did not receive MP-guided treatment due to lack of matched drugs and/or clinical trials, poor performance status, and/or financial burden.

NGS panel testing allowed MP-guided treatment in only 4.7% (6/127) of patients with advanced breast cancer in a real-world setting. The availability of matched drugs is critical for the realistic implementation of personalized treatment.