Related Experiment Video
Updated: Dec 13, 2025
Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids
Published on: June 8, 2019
Landscape of circulating tumour DNA in metastatic breast cancer
Andrew A Davis1, Saya Jacob2, Lorenzo Gerratana3
1Division of Hematology and Oncology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States; Robert H. Lurie Comprehensive Cancer Center of Northwestern University, 710N. Fairbanks Court- Olson Pavilion, Suite 8-250A, Chicago, IL 60611, United States.
Background:
We describe the genomic landscape of circulating tumour DNA (ctDNA) across pathological subtypes of metastatic breast cancer.
Methods:
255 clinically annotated patients with ctDNA testing by Guardant360 were stratified into HR+, HER2+, and TNBC cohorts. Frequency and heterogeneity of alterations were reported. Paired ctDNA and tissue sequencing were compared for a subset of patients. The association of ctDNA and metastatic sites of disease on imaging was also assessed.
Findings:
89% of patients had at least one ctDNA alteration detected. The most common single nucleotide variants (SNVs) for HR+ patients were PIK3CA, ESR1, and TP53. For HER2+, these were TP53, PIK3CA, and ERBB2 with ERBB2 as the most frequent copy number variant (CNV). For TNBC, the most common SNVs were TP53 and PIK3CA, and the most frequent CNVs were MYC, CCNE1, and PIK3CA. TNBC patients had a significantly higher mutant allele frequency (MAF) of the highest variant compared to HR+ or HER2+ patients (P<0.05). Overall, alterations in PIK3CA, ESR1, and ERBB2 were observed in 39.6%, 16.5%, and 21.6% of patients, respectively. Agreement between blood and tissue was 79-91%. MAF and number of alterations were significantly associated with number of metastatic sites on imaging (P<0.0001).
Interpretation:
These data demonstrate the genetic heterogeneity of metastatic breast cancer in blood, the high prevalence of clinically actionable alterations, and the potential to utilise ctDNA as a surrogate for tumour burden on imaging.
Funding:
Lynn Sage Cancer Research Foundation, OncoSET Precision Medicine Program, and REDCap support was funded by the National Institutes of Health UL1TR001422.
