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Pilot study uncovers glycan signatures in non-muscle-invasive and muscle-invasive bladder cancer, suggesting new biomarkers.
The critical need for minimally invasive biomarkers to stratify non-muscle-invasive (NMIBC) and muscle-invasive bladder cancer (MIBC) prompted our investigation into tumor-specific glycan signatures. We hypothesized that lectin-based glycoprofiling could stratify MIBC and NMIBC via stage-specific glycan remodeling. Leveraging the emerging role of lectin microarrays in glycoprofiling, the first comprehensive plasma-based analysis comparing NMIBC and MIBC glycosylation patterns using a high-density 95-lectin platform was conducted. A pilot cohort of 48 plasma samples (22 NMIBC, 10 MIBC, 16 NL) was analyzed using RayBiotech's high-density 95-lectin microarray platform (GA-Lectin-95). Advanced bioinformatics pipelines (Limma package, R/Bioconductor) identified differentially expressed lectins (LogFC > 1.2, adj.p < 0.05) with stringent validation, including ROC analysis (Receiver Operating Characteristic, pROC package) and cross-validated AUC (Area Under the Curve) calculations. Stage-specific glycoarchitectural remodeling revealed profound pathophysiological divergence: NMIBC plasma exhibited global glycan depletion marked by SSA/ASA/SHA downregulation (diagnostic AUC 0.79-1.00), whereas MIBC demonstrated aggressive sialylation/fucosylation signatures dominated by VVA/WFA overexpression (AUC 0.91-0.95). A decalectin panel in DSA/ASA/STL/ABL/MNM-M/PWA/PTL-1/SSA/CAA/GAL3C-S achieved perfect stratification of NMIBC from controls (AUC = 1.00), while four invasion-associated lectin complexes GAL1-S/RCA60/MPL/LSL-N showed MIBC-specific amplification (AUC > 0.80). Notably, CAA/DSA/SSA precisely discriminated MIBC from NMIBC (AUC = 1.00). GAL2 emerged as a novel metastasis checkpoint through its dramatic suppression in invasive tumors, suggesting its role as a glycosylation gatekeeper restraining muscle invasion. These findings support plasma glycoprofiling as a paradigm-shifting tool for bladder cancer subtyping. The results of this study provide actionable biomarkers for clinical stratification and diagnostics applications in bladder cancer management.
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Xiang et al. (2025) studied this question.
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