Hybrid capture-based genomic profiling of circulating tumor DNA from patients with metastatic breast cancer.

person Xiaoxiang Guan Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China info_outline Xiaoxiang Guan, Hong Zhu, Wenzhuan Xie, Jing Zhao, Guoqiang Wang, Yuzi Zhang, Zhengyi Zhao, Shangli Cai

Authors person Xiaoxiang Guan Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China info_outline Xiaoxiang Guan, Hong Zhu, Wenzhuan Xie, Jing Zhao, Guoqiang Wang, Yuzi Zhang, Zhengyi Zhao, Shangli Cai Organizations Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, Department of Oncology, the First Affiliated Hospital of Soochow University, Suzhou, China, The Medical Department, 3D Medicines Inc., Shanghai, China Abstract Disclosures Research Funding Other Background: Breast cancer is the most common malignancy among women worldwide. It is particularly important to provide precise therapies based on genomic alterations, especially for metastatic breast cancers (MBC), which exhibit a high tumor heterogeneity and dynamic changes during the course of disease progression. However, genomic sampling upon metastatic tissue biopsy frequently encountered difficulties due to its inherent invasive approach such as insufficient samples and clinical risks. Our study aims to assess the genomic alternation landscape of metastatic breast cancer detected by blood-based circulating tumor DNA (ctDNA) and evaluate the assay performance. Methods: We performed hybrid capture-based next-generation sequencing (NGS) of 150 genes on ctDNA from 203 female patients with MBC. The mean sequencing depth was more than 3000×. The results were compared with our internal tissue genomic database (297 female patients with MBC) tested by NGS and TCGA database (N=982) tested by whole exome sequencing. Genomic alterations including single nucleotide variation (SNV), insertions/deletions, copy number variations, gene rearrangement and fusions were assessed. Results: Genomic data from 203 female patients with metastatic breast cancer were analyzed via ctDNA [median age 53 years (range, 46–61 years)]. Evidence of ctDNA as estimated by the maximum somatic allele frequency (MSAF) was detected in 95.6% of the patients (median=7.1 alterations/patient), and 97.0% of the patients had at least one characterized altered gene. The most frequently mutated genes identified for SNV occurred in TP53 (47.8%), PIK3CA (36.0%), and ESR1 (16.3%) upon ctDNA analysis and TP53 (73.2%), PIK3CA (38.4%), and ESR1 (4.0%) from our internal tissue database. However, in TCGA cohort, where most patients were presented with early stage diseases, the most mutated gene in terms of SNV was PIK3CA (32.5%), followed by TP53 (30.7%) and TTN (16.0%). The status of ERBB2 amplifications had a high concordance among ctDNA (14.8%), tissue (14.9%), and TCGA database (13.5%). The MSAF level was significantly higher for the fusion-present cases (P=0.048) or amplification cases (p<0.0001) than non-fusion or non-amplification cases. Conclusions: Our study has suggested that ctDNA profiling is a feasible approach for the molecular analysis in metastatic breast cancer and may better capture the mutational landscape of MBC for further clinical implications.