Liquid Biopsy Could Identify Advanced Breast Cancer Patients

Blood samples were collected and the plasma processed using the Circulating Nucleic Acids kit.

The team designed a custom 158-amplicon panel (size range 125–175 bp) across 16 genes based on previous studies and publically available databases. Library preparation and Personal Genome Machine (PGM) sequencing were performed using the Ion Ampliseq library preparation kit. Droplet digital polymerase chain reaction (ddPCR) was used to validate tumor protein p53 (TP53), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), and estrogen receptor 1 (ESR1) mutations.

The scientists identified no mutations in cell free DNA (cfDNA) of healthy controls, whereas exactly half the patients with metastatic breast cancer had at least one mutation or amplification in cfDNA (mean 2, range 1–6) across a total of 13 genes. Longitudinal follow up showed dynamic changes to mutations and gene amplification in cfDNA indicating clonal and subclonal response to treatment that was more dynamic than cancer antigen 15-3 (CA15-3).

At the time of blood sampling disease progression was occurring in seven patients with erb-b2 receptor tyrosine kinase 2 (ERBB2) gene amplification in their cfDNA and three of these patients were human epidermal growth factor receptor 2 (HER2) negative at diagnosis, suggesting clonal evolution to a more aggressive phenotype. Six of the women with hormone-driven cancers had mutations in the ESR1 gene, which has been linked to resistance to anti-hormone treatments.

David Guttery, PhD, a leading author of the study, said, “We have developed a novel blood test that can simultaneously detect somatic mutations and copy number alterations that are integral in driving the growth of breast cancer. By analyzing blood plasma to measure for cancer-specific changes to key breast cancer genes, including the HER2 and estrogen receptor genes, we hope this test could help doctors and patients choose the best treatment at the best time.” The study was described by Professor Jacqui A. Shaw, PhD, in an oral presentation at the Frank May Prize Lecture on June 26, 2017, at the University of Leicester.

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