Glycans are monosaccharide-based heteropolymers that are found covalently attached to many different proteins and lipids and are ubiquitously displayed on the exterior surfaces of cells. Serum glycan composition and structure are well known to be altered in many different types of cancer. In fact, glycans represent a promising but only marginally accessed source of cancer markers. The approach used in this dissertation, which is referred to as “glycan node analysis”, is a molecularly bottom-up approach to plasma/serum (P/S) glycomics based on glycan linkage analysis that captures features such as α2-6 sialylation, β1-6 branching, and core fucosylation as single analytical signals.
The diagnostic utility of this approach as applied to lung cancer patients across all stages as well as prostate, serous ovarian, and pancreatic cancer patients compared to certifiably healthy individuals, nominally healthy individuals and/or risk-matched controls is reported. Markers for terminal fucosylation, α2-6 sialylation, β1-4 branching, β1-6 branching and outer-arm fucosylation were most able to differentiate cases from controls. These markers behaved in a stage-dependent manner in lung cancer as well as other types of cancer. Using a Cox proportional hazards regression model, the ability of these markers to predict progression and survival in lung cancer patients was assessed. In addition, the potential mechanistic role of aberrant P/S glycans in cancer progression is discussed.
Plasma samples from former bladder cancer patients with currently no evidence of disease (NED), non-muscle invasive bladder cancer (NMIBC), and muscle invasive bladder cancer (MIBC) along with certifiably healthy controls were analyzed. Markers for α2-6 sialylation, β1-4 branching, β1-6 branching, and outer-arm fucosylation were able to separate current and former (NED) cases from controls; but NED, NMIBC, and MIBC were not distinguished from one another. Markers for α2-6 sialylation and β1-6 branching were able to predict recurrence from the NED state using a Cox proportional hazards regression model adjusted for age, gender, and time from cancer. These two glycan features were found to be correlated to the concentration of C-reactive protein, a known prognostic marker for bladder cancer, further strengthening the link between inflammation and abnormal plasma protein glycosylation.