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Glycosylation is one of the most common and dynamic post-translational modification of cell surface and secreted proteins. Cancer cells display unique glycosylation patterns that decisively contribute to drive oncogenic behavior, including disease progression and dissemination. Moreover, alterations in glycosylation are often responsible for the creation of protein signatures holding significant biomarker value and potential for targeted therapeutics. Accordingly, many analytical protocols have been outlined for the identification of abnormally glycosylated proteins by mass spectrometry. Nevertheless, very few studies undergo a comprehensive mining of the generated data. Herein, we build on bladder cancer O -glycoproteomics datasets resulting from a hyphenated technique comprising enrichment by Vicia villosa agglutinin (VVA) lectin and nanoLC-ESI-MS/MS to propose an in silico step-by-step tutorial (Panther, UniProtKB, NetOGlyc, NetNGlyc, Oncomine, Cytoscape) for biomarker discovery in cancer. We envisage that this approach may be generalized to other mass spectrometry-based analytical approaches, including N -glycoproteomics studies, and different types of cancers. Significance The glycoproteome is an important source of cancer biomarkers holding tremendous potential for targeted therapeutics. We now present an in silico roadmap for comprehensive interpretation of big data generated by mass spectrometry-based glycoproteomics envisaging the identification of clinically relevant glycobiomarkers. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the potential of sialyl-Tn (STn), a cancer-associated glycan antigen present in membrane glycoproteins, to improve a recent molecular model for stratification and prognostication of advanced stage bladder tumors based on keratins (KRT14, 5, and 20) expression. In addition, determine the association between STn and disease dissemination based on the evaluation of circulating tumor cells (CTCs) and the metastasis, which is a critical matter to improve patient management.Patients and Methods: A retrospective series of 80 muscle-invasive primary bladder tumors and associated metastasis were screened for KRT14, 5, and 20 and STn by real-time polymerase chain reaction and immunohistochemistry. Peripheral blood was collected in a patients' subset, CTCs were isolated through a size-based microfluidic chip and screened for KRTs and STn.Results: Basal-like lesions presented worse cancer-specific and disease-free survival compared to luminal tumors. STn antigen inclusion discriminated patients with worst survival in each subgroup (P = 0.047 for luminal; P = 0.027 for basal-like tumors). STn expression in CTCs and distant metastasis was also demonstrated.Conclusion: This work reinforces the potential of the KRT-based model for bladder cancer management and the association of STn with aggressiveness, supporting its inclusion in predictive molecular models toward patient-tailored precision medicine. Moreover, we describe for the first time that CTCs and the metastasis present a basal phenotype and express the STn antigen, highlighting its link with disease dissemination. Future studies should focus on determining the biological and clinical significance of these observations in the context of liquid biopsies. Given the membrane nature of STn, highly specific targeted therapeutics may also be envisaged. [ABSTRACT FROM AUTHOR]