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. 2025 Mar 7;11(10):eadt0029.
doi: 10.1126/sciadv.adt0029. Epub 2025 Mar 7.

Multiplexed glycan immunofluorescence identification of pancreatic cancer cell subpopulations in both tumor and blood samples

Braelyn Binkowski  1 , Zachary Klamer  1 , ChongFeng Gao  1 , Ben Staal  1 , Anna Repesh  1 , Hoang-Le Tran  1 , David M Brass  1 , Pamela Bartlett  2 , Steven Gallinger  3 , Maria Blomqvist  4   5 , J Bradley Morrow  2 , Peter Allen  6 , Chanjuan Shi  6 , Aatur Singhi  7 , Randall Brand  7 , Ying Huang  8 , Galen Hostetter  1 , Brian B Haab  1
Affiliations

Multiplexed glycan immunofluorescence identification of pancreatic cancer cell subpopulations in both tumor and blood samples

Braelyn Binkowski et al. Sci Adv. .

Abstract

Pancreatic ductal adenocarcinoma (PDAC) tumor heterogeneity impedes the development of biomarker assays for early disease detection. We hypothesized that PDAC cell subpopulations could be identified by aberrant glycan signatures in both tumor tissue and blood samples. We used multiplexed glycan immunofluorescence to distinguish between PDAC and noncancer cell subpopulations within tumor tissue, and we developed hybrid glycan sandwich assays to determine whether the aberrant glycan signatures could be detected in blood samples. We found that PDAC cells were identified by signatures of glycans detected by four glycan-binding proteins (VVL, CA19-9, sTRA, and GM2) and that there are three types of glycan-defined PDAC tumors: sTRA type, CA19-9 type, and intermixed. In patient-matched tumor and blood samples, the PDAC tumor type could be determined by the aberrant glycans in the blood. As a result, the combined assays of aberrant glycan signatures were more sensitive and specific than any individual assay. Our results demonstrate a methodology to detect and stratify PDAC.

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Figures

Fig. 1.
Fig. 1.. Multiplexed IF glycan imaging enables identification and quantification of cellular glycan signatures.
(A) Model of cell surface glycan signatures. (B) Glycan-binding proteins (GBPs) and their targets. (C) Multiplexed immunofluorescence with automated signal thresholding by SignalFinder, followed by assignments of glycan signatures to individual cells. (A) and (C) created with BioRender.com.
Fig. 2.
Fig. 2.. A training set of PDAC tumor specimens shows cancer association glycan signatures.
(A) Training design. (B) Quantification of cells with each glycan signature in ROIs. (C) Distributions of cell surface glycan signatures among acinar and PDAC cells. (D) Volcano plots of pairwise comparisons between cell types. (E) Cancer-associated and noncancer-associated glycan signatures. (F) Representative images and quantifications of noncancer and cancer ROIs. The asterisk marks normal islet cells and the arrowhead marks a normal duct.
Fig. 3.
Fig. 3.. A test set of PDAC tumor specimens validates the putative PDAC-associated glycan signatures.
(A) Test set design. (B) Patterns of positivity of the putative cancer-associated glycan signatures compared to CA19-9 in individual ROIs in each specimen. (C) Prevalence and association with cancer of the predicted cancer-associated (left) and noncancer-associated (right) glycan signatures.
Fig. 4.
Fig. 4.. The glycan-defined PDAC cell subpopulations have unequal distributions among spatial clusters and tumors.
(A) Cluster and tumor heterogeneity. Clusters may be classified as uniform or mixed, and tumors may be classified as heterogeneous or heterogeneous. Created with BioRender.com. (B) Two examples of within-cluster subpopulation purity, or uniformity, in cancer-cell clusters. (C) Tumor type classifications based on the predominance of cells with each glycan signature type—CA19-9 exclusive, sTRA exclusive, or dual expressing—in the tumor. (D) Probability of association with pure or uniform clusters. Positive log odds are associated with pure clusters. (E) Apparent lineages of glycan-defined PDAC cell subpopulations in the cell clusters and tumors. (F) Relationship between average subpopulation uniformity in the clusters and the average centroid differences between clusters within each tumor. Each data point is a tumor, color coded by tumor type from (C). The dashed lines are the median values in each axis. (G) Kaplan-Meijer plot of patients with PDAC in the different groups defined in (F).
Fig. 5.
Fig. 5.. Blood assays for PDAC cell–released glycans provide complementary detection of tumors with divergent PDAC subpopulations.
(A) Model of co-secretion of glycans. (B) Hybrid glycan sandwich assays. (C) Correspondence of combined plasma assays to tumor types. The tumor types at the top were based on the classifications in Fig. 4C, and the predicted tumor types at the bottom were based on the blood assay. (D) Cancer-associated relative fluorescent unit (RFU) values in the individual assays. *** indicates P < 0.001. (E) Complementary detection and stratification of PDACs using the combined assays. The detection and subtype cutoffs are given in table S9. (F) Detection and stratification decision tree. (A) and (B) created with BioRender.com.
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