Abstract
It is particularly important to provide precise therapies and understand tumor heterogeneity based on the molecular typing of mutational landscape. However, the landscape of somatic mutations in different subtypes of advanced breast cancer (ABC) is largely unknown. We applied target-region capture deep sequencing to determine the frequency and spectrum of common cancer-related gene mutations in circulating tumor DNA (ctDNA) among different ABC subtypes and analyze their association with clinical features. In this retrospective study of 100 female advanced breast cancer patients, 96 (96.0%) had somatic genomic alterations in ctDNA, including copy number variants and point mutations. The results revealed that different subtypes of ABC have distinct features in terms of genetic alterations. Multivariate regression analyses revealed that the number of somatic mutations increased with the line of endocrine therapy and the fractions of trunk mutations was positive associated with the line of target therapy.
Highlights
Breast cancer, one of the most common cancers worldwide, is a heterogeneous disease with a variety of outcomes and drug responses
We applied target-region-capture deep sequencing to detect somatic mutations in plasma Circulating tumor DNA (ctDNA) from advanced breast cancer (ABC) patients to understand the mutational characteristics of ABC and analyze the association of clinical features and therapeutic history with gene variations
A total of 100 female ABC patients were enrolled in the present study
Summary
One of the most common cancers worldwide, is a heterogeneous disease with a variety of outcomes and drug responses. We applied target-region-capture deep sequencing to detect somatic mutations in plasma ctDNA from ABC patients to understand the mutational characteristics of ABC and analyze the association of clinical features and therapeutic history with gene variations. Somatic genomic alterations in ctDNA, including CNVs and point mutations, were identified in 96 of 100 patients (96.0%). We examined the relationship between the number of somatic mutations and the age at diagnosis in the 100 patients.
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