Aberrant glycosylation represents an important modification that occurs in cancer cells during tumor progression and that favors invasion and metastatic spread. The aberrant expression of truncated O-glycans appeared to be the most widely diffuse change in glycosylation pattern present in epithelial cancer tissues. The expression of truncated T (Galß1-3GalNAc¿1-O-Ser/Thr), STn (NeuAc¿2-6GalNAc¿1-O-Ser/Thr) and Tn (GalNAc¿1-O-Ser/Thr) carbohydrate moieties are associated with poor prognosis and low survival of cancer patient and they are also used as biomarkers to predict prognosis and to follow the progression disease.
Ovarian cancer (OC) is characterized by the presence of several STn- and Tn- glycoproteins that are released by the cells and that are commonly use as biomarkers. The mucin MUC16 (CA125) and MUC1 (CA15.3) represent optimal models of altered glycoproteins that are considered a serum ovarian cancer biomarkers to predict malignant progression, although their overexpression is not limited to malignant disease.
Glycoproteins interact with the cell of the immune system through the C-type lectins. MGL, expressed by dendritic cells (DCs) and macrophages, is a C-type lectin able to selectively bind to Tn residues. This receptor is involved in the clearance of non-sialylated glycoproteins from bloodstream and in the activation of DCs representing an optimal target for immunotherapy.
The aim of this project is to use the MGL receptor to capture and identified criptic Tn-Tumor Associated Antigens from ovarian cancer that could be used as novel biomarkers for the monitoring of the disease and as immune activators in the setting of the immunotherapy protocols.
Ovarian cancer (OC) remains the most lethal gynaecological malignancy. Advances in cancer genomics, epigenomics and proteomics have led to the understanding that OC is a heterogeneous group of different tumours displaying distinct phenotypes and aetiology (Vaughan S, Nat Rev Cancer 2011). The identification of predictive biomarkers is still an urgent need in this lethal cancer setting and this step is pivotal for designing new treatment strategies able to reduce OC-related mortality (Network CGAR, Nature 2011).
Glycosylation is one of the most important and common post-translational modifications. More than 50% of human proteins have been reported to be glycosylated. In the case of cancer, a profound correlation between glycosylation and disease development and/or malignancy has been demonstrated (Kawaguchi,2005). Accordingly, unequivocal identification and quantification of glycoproteins associated with cancer may provide an opportunity to discover reliable and sensitive cancer biomarkers that permit the detection of the disease at early stages.
Furthermore, the identification of ovarian cancer-associated glycoproteins with both prognostic and immunological impact may provide novel patterns of immune recognition in cancer patients for the development of a new anti-cancer vaccination strategy.
Two new `omics¿ fields aiming to evaluate the protein glycosylation in ovarian cancer specimens will be applied in the present study, namely: glycomics and glycoproteomics.
The main potential of the present study is to impact on OC early diagnosis (through the identification of new circulating/tissue biomarkers) and on OC treatment/prevention (through the possible development of a new anti-cancer vaccine based on the identified glycoproteins).