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<0.001) for the diagnosis of BB (AUC: 0.752, sensitivity: 0.600, and specificity: 0.835) and I stage breast cancer (AUC: 0.755, sensitivity: 0.733, and specificity: 0.742) in the validation cohort. The diagnostic model of I stage breast cancer exhibited a high accuracy of 0.902 in double-blind cohort.

Conclusions: This study could contribute to the screening for patients with early-stage breast cancer based on precise alterations of salivary glycopatterns.

Keywords: Biomarkers; Breast diseases; Early-stage breast cancer; Glycopatterns; Saliva.

Fig. 1

The different salivary glycopatterns in HV, BB, BC-I and BC-II using a lectin microarray. (A) The layout of the lectin microarrays. Each lectin was spotted in triplicate per block, with quadruplicate blocks on one slide. Cy3-labeled BSA was spotted as a location marker and BSA as a negative control. (B) The glycopatterns of a Cy3-labeled pooled salivary sample bound to the lectin microarrays. The lectin microarrays revealed significant signal differences between HV, BB, BC-I and BC-II marked with yellow frames. While the significant differences among three mixture saliva from disease groups marked with white frames. (C) Unsupervised average linkage HCA of the lectin microarray responses to saliva. The samples were listed in columns, and the lectins were listed in rows. The color and intensity of each square indicated expression levels relative to the other data in the row. Red, high; green, low; black, medium. (D) Five lectins revealed significant differences between HV and patients with breast disease, but found no differences between patients with breast disease. (E) Six lectins revealed significant differences among breast diseases groups. Lectins showing increase of NFIs (fold change ≥ 2, p < 0.05) or decrease of NFIs (fold change ≤ 0.5, p < 0.05) between HV, BB, BC-I and BC-II according to one-way ANOVA (^⁎p < 0.05, ^⁎⁎p < 0.01, and ^⁎⁎⁎p < 0.001).

Fig. 2

The variable expression levels of salivary glycopatterns in the saliva with breast diseases represented in scatter diagram by Kruskal-Wallis test. The p value indicating the difference between HV and patients with breast diseases (p < 0.05) marked with black, and the difference between BB, BC-I and BC-II (p < 0.05) marked with gray.

Fig. 3

The diagnosis accuracy of the diagnostic models and selected lectins analyzed by ROC analysis. (A), (B), (C), (D) and (E), The ROC analysis for Model BD, Model BC, Model BB, Model BC-I and Model BC-II as well as the selected lectins in the retrospective cohort, respectively. ROC-AUC values were expressed by (1-value) if lectins showed the decreased signal.