Glycan Nodes as Cancer Markers


Altered sugar polymer (glycan) structures are a universal feature of cancer cells that represent a promising, but only marginally used source of markers. With appropriate analytical techniques, global blood plasma/serum (P/S) glycomics show great potential as non-invasive markers for the presence and progression of cancer. Unfortunately, modern analytical methods for quantifying the relative abundance of different glycans in P/S vary widely and focus mostly on N-linked glycans, often to the exclusion of O- and lipid-linked glycans.

Researchers at the Biodesign Institute of Arizona State University have developed a method of using P/S glycomics based on glycan linkage analysis that captures glycan features such as α2-6 sialylation, β1-6 branching, and core fucosylation as single analytical signals to evaluate the behavior of P/S glycans in cancer. This approach was applied to over 950 clinical P/S samples from 7 different case control studies across all stages of cancer in which the cancer cases were compared to related benign conditions and healthy controls. The marker for α2-6 sialylation was found to predict both progression and all-cause mortality in lung cancer patients with p-values of <0.01. Further, this method was able to separate current and former evidence of disease cases of bladder cancer from certifiably healthy controls.

This unique approach to analyzing P/S glycomics captures all major classes of P/S glycans to provide a powerful platform for detecting a variety of different types of cancer at varying stages.

Potential Applications

• Cancer diagnostics/prognostics

o Lung, bladder, prostate, ovarian, pancreatic, and possibly others

• Creation of unique cancer specific glycan biosignatures

Benefits and Advantages

• Does not require special sample pre-processing

• No biological reagents (no antibodies or enzymes)

• Cost effective

• Captures information from all major classes of P/S glycans, including N-,O- and lipid-linked glycans

• α2−6 sialylation is able to predict lung cancer progression and survival with p-values of <0.01

• All five top-performing glycan nodes were able to predict progression and survival to a more limited extent than α2−6 sialylation

• Uses clinically established instrumentation (gas chromatograph-mass spectrometer)

• Sensitive – works well on limited sample quantity

• The behavior of the nodes is independent of the organ of tumor origin

For more information about this opportunity, please see

Ferdosi et al - J. Proteome Res - 2018

Ferdosi et al - PloS One - 2018

For more information about the inventor(s) and their research, please see

Dr. Borges' departmental webpage

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Chad Borges Shadi Ferdosi

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