Glycosylation is increasingly being recognized as an important layer of tumor biology, with relevance for cancer progression, immune interactions, and biomarker development. But the structural complexity of glycans, and the difficulty of studying them in tissue context, has historically limited their use in translational research.
In the following interview, Catherine Bladen, Vice President of Technical Development at Vector Laboratories, discusses how advances in glycoscience are changing cancer research, what analytical challenges remain, and where glycosylation could support future diagnostic and therapeutic development.
Why is glycosylation such an important, but historically underexplored, feature of cancer biology?
Glycosylation sits at the intersection of protein biology, metabolism, and cell signaling, so it plays a central role in how cancer cells communicate, metastasize, and evade immune defenses. Historically, though, glycans have been much more difficult to study than genes or proteins because they are highly heterogeneous, structurally complex, and not directly encoded by the genome. For many years, researchers lacked robust tools to visualize and characterize glycan patterns in the context of tissue, especially in clinically relevant samples. As analytical technologies improve, we’re now recognizing that glycosylation is a fundamental layer of cancer biology with major diagnostic and therapeutic implications.
How could a better understanding of tumor-associated glycoforms shape diagnostic/therapeutic development?
Tumor-associated glycoforms can provide a much more disease-specific signature than protein expression alone because cancer cells often alter glycosylation in highly characteristic ways. In colorectal cancer especially, where incidence rates are rising globally and younger patient populations are increasingly affected, there is an urgent need for biomarkers that support earlier and more accurate detection. A substantial body of research has already described glycosylation patterns specific to colorectal cancer and established the role of altered glycosylation in driving disease progression. The challenge is now putting those findings to use in diagnostics and therapeutics. Glycan-based signatures could help distinguish aggressive disease states, predict therapeutic response, or identify tumors before conventional pathological changes become obvious. Aberrant glycans and glycoforms may also serve as selective targets for antibody-based therapies or immune engagement strategies.
What are the biggest analytical challenges researchers face when studying site-specific glycosylation in tumors?
One of the biggest challenges is the sheer complexity of glycosylation itself: multiple glycan structures can exist on a single protein, and those structures may vary by cell type, disease state, or even subcellular localization. Preserving spatial information while achieving site-specific resolution is also technically difficult, particularly in heterogeneous tumor tissues. Researchers face additional challenges related to sample preparation, sensitivity, and reproducibility, especially when working with limited clinical specimens. Finally, integrating glycomics data with proteomics, transcriptomics, and pathology workflows remains a major hurdle for translating findings into biologically actionable insights.
How has the field of glycoscience evolved in recent years, particularly in terms of tools and analytical capabilities?
The field has advanced dramatically over the past decade thanks to improvements in mass spectrometry, glycoproteomics workflows, imaging technologies, and glycan-specific reagents. Researchers can now characterize glycan structures with much greater sensitivity and spatial precision than was previously possible. At the same time, there has been significant progress in tissue-based detection approaches that allow glycans and glycoforms to be studied directly in situ alongside protein biomarkers. These advances are making glycoscience more accessible to mainstream cancer researchers and accelerating its integration into translational oncology workflows.
What technologies are currently helping researchers better detect and characterize cancer-associated glycoforms?
A combination of advanced mass spectrometry platforms, glycoproteomics pipelines, lectin-based detection methods, and multiplex imaging technologies is driving the field forward. Immunohistochemistry and immunofluorescence workflows are also evolving to support more sophisticated glycan analysis in tissue context, which is particularly important for understanding tumor microenvironments. Specialized glycan detection reagents and enzyme-based labeling approaches are helping researchers visualize specific glycan motifs with improved specificity and reproducibility. At the same time, AI and machine learning tools are becoming increasingly valuable for identifying complex glycosylation patterns across large imaging and multi-omics datasets, helping researchers uncover predictive cancer-associated signatures that may not be apparent through conventional analysis alone.
How are advances in glycosylation analysis influencing biomarker discovery or drug target identification?
More refined glycosylation analysis is helping researchers identify biomarkers that may have been overlooked when focusing only on gene or protein abundance. In many cases, the glycoform of a protein, not just the protein itself, is what correlates with disease progression, metastasis, or treatment resistance. These insights are especially valuable for improving specificity in diagnostics and for identifying novel therapeutic targets that are selectively expressed on tumor cells. As analytical resolution improves, researchers are gaining a much clearer understanding of how glycosylation contributes to immune modulation and tumor biology, which has important implications for immuno-oncology.
What still needs to happen before glycosylation insights can reliably translate into new diagnostic tools and therapies for colorectal cancer?
Standardization will be critical – from sample preparation workflows to analytical methods and data interpretation – so findings can be reproduced consistently across laboratories and clinical studies. We also need larger-scale validation studies that link specific glycosylation signatures to clinical outcomes in diverse patient populations. Another important step is improving accessibility to robust, user-friendly glycan analysis tools that fit into existing pathology and translational research workflows. Ultimately, successful clinical translation will depend on strong collaboration between glycobiologists, clinicians, pathologists, and technology developers.
Looking ahead, where do you see the most promising opportunities for glycosylation research in oncology?
One of the most exciting opportunities is integrating glycosylation analysis with spatial biology and multi-omics approaches to build a more complete picture of tumor behavior. There is also enormous potential in using glycan signatures to improve patient stratification and personalize immunotherapy approaches. As detection technologies continue to mature, I think we’ll see glycosylation become increasingly important in early cancer detection and minimal residual disease monitoring. This will be particularly critical to improving outcomes as rates of colorectal cancer rise in younger populations. More broadly, the field is moving toward a future where glycan biology is considered a routine and essential component of cancer research rather than a highly specialized niche.
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