Salivary Glycopatterns as Potential Biomarkers for Screening of Early-Stage Breast Cancer

Abstract Objective We systematically investigated and assessed the alterations of salivary glycopatterns and possibility as biomarkers for diagnosis of early-stage breast cancer. Design Alterations of salivary glycopatterns were probed using lectin microarrays and blotting analysis from 337 patients with breast benign cyst or tumor (BB) or breast cancer (I/II stage) and 110 healthy humans. Their diagnostic models were constructed by a logistic stepwise regression in the retrospective cohort. Then, the performance of the diagnostic models were assessed by ROC analysis in the validation cohort. Finally, a double-blind cohort was tested to confirm the application potential of the diagnostic models. Results The diagnostic models were constructed based on 9 candidate lectins (e.g., PHA-E + L, BS-I, and NPA) that exhibited significant alterations of salivary glycopatterns, which achieved better diagnostic powers with an AUC value > 0.750 (p  Conclusions This study could contribute to the screening for patients with early-stage breast cancer based on precise alterations of salivary glycopatterns.