posted on 2023-12-21, 10:37authored byJ Stebbing, PG Takis, CJ Sands, L Maslen, MR Lewis, K Gleason, K Page, D Guttery, D Fernandez-Garcia, L Primrose, JA Shaw
To assess their roles in breast cancer diagnostics, we aimed to compare plasma cell-free DNA (cfDNA) levels with the circulating metabolome in a large breast screening cohort of women recalled for mammography, including healthy women and women with mammographically detected breast diseases, ductal carcinoma in situ and invasive breast cancer: the Breast Screening and Monitoring Study (BSMS). In 999 women, plasma was analyzed by nuclear magnetic resonance (NMR) and Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) and then processed to isolate and quantify total cfDNA. NMR and UPLC-MS results were compared with data for 186 healthy women derived from the AIRWAVE cohort. Results showed no significant differences between groups for all metabolites, whereas invasive cancers had significantly higher plasma cfDNA levels than all other groups. When stratified the supervised OPLS-DA analysis and total cfDNA concentration showed high discrimination accuracy between invasive cancers and the disease/medication-free subjects. Furthermore, comparison of OPLS-DA data for invasive breast cancers with the AIRWAVE cohort showed similar discrimination between breast cancers and healthy controls. This is the first report of agreement between metabolomics and plasma cfDNA levels for discriminating breast cancer from healthy subjects in a true screening population. It also emphasizes the importance of sample standardization. Follow on studies will involve analysis of candidate features in a larger validation series as well as comparing results with serial plasma samples taken at the next routine screening mammography appointment. The findings here help establish the role of plasma analysis in the diagnosis of breast cancer in a large real-world cohort.
Funding
C14315/A23464
Establishing MRC-NIHR Phenome Centre, a world leading high-throughput metabolic phenotyping centre for humanpopulation disease-risk biomarker discovery.
Stebbing, J., Takis, P.G., Sands, C.J. et al. Comparison of phenomics and cfDNA in a large breast screening population: the Breast Screening and Monitoring Study (BSMS). Oncogene 42, 825–832 (2023)
Author affiliation
Department of Genetics and Genome Biology, University of Leicester