Comparison of printed glycan array, suspension array and ELISA in the detection of human anti-glycan antibodies

Abstract

Anti-glycan antibodies represent a vast and yet insufficiently investigated subpopulation of naturally occurring and adaptive antibodies in humans. Recently, a variety of glycan-based microarrays emerged, allowing high-throughput profiling of a large repertoire of antibodies. As there are no direct approaches for comparison and evaluation of multi-glycan assays we compared three glycan-based immunoassays, namely printed glycan array (PGA), fluorescent microsphere-based suspension array (SA) and ELISA for their efficacy and selectivity in profiling anti-glycan antibodies in a cohort of 48 patients with and without ovarian cancer. The ABO blood group glycan antigens were selected as well recognized ligands for sensitivity and specificity assessments. As another ligand we selected P(1), a member of the P blood group system recently identified by PGA as a potential ovarian cancer biomarker. All three glyco-immunoassays reflected the known ABO blood groups with high performance. In contrast, anti-P(1) antibody binding profiles displayed much lower concordance. Whilst anti-P(1) antibody levels between benign controls and ovarian cancer patients were significantly discriminated using PGA (p=0.004), we got only similar results using SA (p=0.03) but not for ELISA. Our findings demonstrate that whilst assays were largely positively correlated, each presents unique characteristic features and should be validated by an independent patient cohort rather than another array technique. The variety between methods presumably reflects the differences in glycan presentation and the antigen/antibody ratio, assay conditions and detection technique. This indicates that the glycan-antibody interaction of interest has to guide the assay selection.

Fig. 1

Comparison of glycan-based immunoassays using ABO blood groups. Scatter plots demonstrating the correlation between printed glycan array, suspension array and ELISA. The x- and y- axes represent standardized signals for each method, the dashed line indicates linear regression for A_tri (empty dots) and dotted line for B_tri (filled dots). The solid line indicates intercept of 0 and slope of 1. Each dot is represented by two-method measurement of one plasma sample (n = 31). R_ccc represents concordance correlation coefficient per blood group including the 95% confidence interval in brackets

Fig. 2

Binding of plasma anti-A/B antibodies to A_tri and B_tri. Boxplots generated for SA (suspension array), PGA (printed glycan array) and ELISA, demonstrate the distribution of anti-glycan antibodies to glycans A_tri (a) and B_tri (b). Blood groups are shown on the x-axis, standardized signals for each method are on the y-axis. Kruskal-Wallis p-values indicate the equality of population medians among blood groups. ROC curves for blood groups A and AB (low anti-A antibody levels) versus B and O (high anti-A antibody levels) were determined by SA, PGA and ELISA (c). Data from blood group B and AB versus blood group A and O were combined respectively (d)

Fig. 3

Anti-P₁ antibody levels in suspension array and printed glycan array. Boxplots demonstrate the distribution of anti-glycan antibodies directed to P₁ in benign control (n = 24; BD) and cancer plasma samples (n = 24; CA) for suspension and printed glycan arrays as well as ELISA