Painting a Picture of the Ovarian Cancer N-Glycome

Abstract

Our story begins with the current clinical strategies that are used by clinicians today to (1) screen and detect ovarian cancer in the early-stages, (2) monitor treatment effectiveness, (3) detect ovarian cancer recurrence and (4) stratify ovarian cancer patients. However, these current strategies utilise FDA-approved ovarian cancer biomarkers, such as CA125 and HE4, which are relatively unsuccessful and lack specificity, especially for early stage patients. In the introduction, it is highlighted that these ovarian cancer biomarkers and other disease biomarkers are typically glycoproteins, but their glycan structure-protein function relationship remains unknown. Protein glycosylation is one of the most complex post-translational modifications (PTMs) found in humans, with N-linked glycans playing a significant role in protein folding and conformation, protein stability and activity, cell-cell interaction, and cell signalling pathways. The best approach to study and analyse N-glycans so far has been to structurally characterise them by firstly, releasing them from complex glycoprotein mixtures using PNGase F, and secondly, identifying specific structures using analytical strategies that may potentially translate into clinical strategies. Ultimately, this thesis focuses on analytical techniques, primarily mass spectrometry, that are available to qualitatively and quantitatively assess N-glycosylation while successfully characterising compositional, structural and linkage features with high specificity and sensitivity. Analytical techniques that were explored include liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS) and matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF-MS). These analytical techniques have previously been implemented in the clinic for other diseases, however, not yet for ovarian cancer. It may be possible to implement either LC-ESI-MS/MS or MALDI-TOF-MS in the clinic for ovarian cancer using N-glycomic-based approaches since aberrant N-glycosylation patterns have been observed consistently between clinical samples, such as serum, plasma, ascites and tissue. MALDI mass spectrometry imaging (MSI) has emerged as a platform to visualise N-glycans in tissue-specific regions. Outlined in this thesis, our group studied the intrapatient and interpatient variability between early- and late-stage ovarian cancer patients. From our studies, specific N-glycan differences were identified between the early- and late-stage tumour microenvironment that could lead to the development of ovarian cancer diagnosis and prognosis strategies for the clinic.