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Updated: Oct 8, 2026

Glycan Node Analysis: A Bottom-up Approach to Glycomics
Published on: May 22, 2016
The total serum N-glycome landscape of hematological malignancies
Yueyi Xu1, Xiaoqing Dong2, Junli Zhang3
1Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, The State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing, China.
Abstract:
A holistic and dynamic view of the glycomic landscape in hematological malignancies (HMs) remains poorly characterized, hindering clinical the application of glycomics in HMs. We launched a large-scale analysis of multicenter cohorts, combining retrospective (n=1,370) and prospective longitudinal (n=130) data across major HM types. We defined distinct total serum N‑glycome (TSNG) profiles for multiple myeloma, lymphoma, and acute leukemia at diagnosis, revealing shared and disease-specific signatures that support their diagnostic and subtyping potential. TSNG features changed with disease status. Key glycans decreased significantly upon complete remission and increased again at relapse. Receiver operating characteristic curve analyses demonstrated that TSNG could distinguish disease states, supporting its utility for assessing treatment response. We systematically mapped the TSNG landscape of HMs, established its clinical relevance across diagnosis, subtyping, and treatment monitoring, providing a framework for advancing the glycomics-based understanding and management of these malignancies.

