Abstract
Purpose
The detection of circulating tumor DNA (ctDNA) is a valuable method to predict the risk of recurrence and to detect real-time gene changes. The amount of ctDNA is affected by many factors. Moreover, the detection rate of ctDNA varies from report to report.
Methods
The present study evaluated differentially expressed genes using a DNA microarray assay for gene expression in tumors with and without detected ctDNA and constructed a prediction model for the detectability of ctDNA in breast tumor tissues. The model, named Cir-Predict, consisted of 73 probe sets (56 genes) and was constructed in a training set of breast cancer patients (n = 35) and validated in a validation set (n = 13).
Results
The accuracy, sensitivity and specificity in training and validation sets were over 95%, and Cir-Predict was significantly associated with ctDNA detection independently of the other conventional clinicopathological parameters in all cohorts. Pathway analysis revealed that nine pathways including tight junction and cell cycle tended to be related to ctDNA detectability.
Conclusion
Cir-Predict not only provides information useful for breast cancer treatment, but also helps the understanding of the mechanism by which ctDNA is detected.