Abstract

Noninvasive detection of aberrant DNA methylation could provide invaluable biomarkers for earlier detection of triple-negative breast cancer (TNBC) which could help clinicians with easier and more efficient treatment options. We evaluated genome-wide DNA methylation data derived from TNBC and normal breast tissues, peripheral blood of TNBC cases and controls and reference samples of sorted blood and mammary cells. Differentially methylated regions (DMRs) between TNBC and normal breast tissues were stringently selected, verified and externally validated. A machine-learning algorithm was applied to select the top DMRs, which then were evaluated on plasma-derived circulating cell-free DNA (cfDNA) samples of TNBC patients and healthy controls. We identified 23 DMRs accounting for the methylation profile of blood cells and reference mammary cells and then selected six top DMRs for cfDNA analysis. We quantified un-/methylated copies of these DMRs by droplet digital PCR analysis in a plasma test set from TNBC patients and healthy controls and confirmed our findings obtained on tissues. Differential cfDNA methylation was confirmed in an independent validation set of plasma samples. A methylation score combining signatures of the top three DMRs overlapping with the SPAG6, LINC10606 and TBCD/ZNF750 genes had the best capability to discriminate TNBC patients from controls (AUC=0.78 in the test set and AUC=0.74 in validation set). Our findings demonstrate the usefulness of cfDNA-based methylation signatures as noninvasive liquid biopsy markers for the diagnosis of TNBC.

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