Abstract

Simple SummaryChanges in glycosylation occur during cancer transformation, altering the interaction among tumor, immune cells and microenvironment and impacting the anti-tumor immune response. The Macrophage galactose-like C-type lectin (MGL), expressed by dendritic cells (DCs), is the immune receptor recognizing the tumor Tn carbohydrate antigen. Recently, Tn/STn-CA125 glycoforms have been proposed as a promising tumor-associated biomarker and the targeting of MGL-Tn axis has been shown to be a valid therapeutic approach in ovarian cancer mouse model. Here we designed a chromatography method to identify glycoproteins relevant in DCs-tumor cell interaction by probing the ovarian cancer O-glycoproteome by means of MGL. The potential MGL binders identified were located on the cell membrane and in the intracellular compartment and matrisome, suggesting that MGL may play a role in sensing microenvironmental cues. These results may be relevant to investigate immune system-tumor interactions and contribute to the design of glycan targeting-based strategies for EOC immunotherapeutic interventions.Glycosylation, the posttranslational linking of sugar molecules to proteins, is notoriously altered during tumor transformation. More specifically in carcinomas, GalNAc-type O-glycosylation, is characterized by biosynthetically immature truncated glycans present on the cancer cell surface, which profoundly impact anti-tumor immune recognition. The tumor-associated glycan pattern may thus be regarded as a biomarker of immune modulation. In epithelial ovarian cancer (EOC) there is a particular lack of specific biomarkers and molecular targets to aid early diagnosis and develop novel therapeutic interventions. The aim of this study was to investigate the ovarian cancer O-glycoproteome and identify tumor-associated glycoproteins relevant in tumor–dendritic cell (DC) interactions, mediated by macrophage galactose-like C type lectin (MGL), which recognizes the tumor-associated Tn O-glycan. Lectin weak affinity chromatography (LWAC) was employed to probe the O-glycopeptidome by MGL and Vicia villosa agglutinin (VVA) lectin using glycoengineered ovarian cancer cell lines and ovarian cancer tissues as input material. Biochemical and bioinformatics analysis gave information on the glycan arrangement recognized by MGL in tumor cells. The potential MGL binders identified were located, as expected, at the cell membrane, but also within the intracellular compartment and the matrisome, suggesting that MGL in vivo may play a complex role in sensing microenvironmental cues. The tumor glycoproteins binders for MGL may become relevant to characterize the interaction between the immune system and tumor progression and contribute to the design of glycan targeting-based strategies for EOC immunotherapeutic interventions.

Highlights

  • Epithelial ovarian cancer (EOC) still accounts for the highest mortality rate among all the gynecological malignancies [1]

  • The recombinant human macrophage galactose-like C-type C lectin receptor containing the extracellular portion of the human Macrophage galactose-like-C-type lectin (MGL) (MGL396-476 ) linked to the human Fc of IgG1 was synthesized by GenScript USA Inc. (Piscataway, NJ, USA)

  • Most of the Tn clusters were flanked by other Tn moieties. These results suggest that ovarian tumor glycoproteins localized on the cell surface and intracellular compartment and in the matrix carry the Tn cluster recognized by MGL

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Summary

Introduction

Epithelial ovarian cancer (EOC) still accounts for the highest mortality rate among all the gynecological malignancies [1]. Most of the patients (75%) are diagnosed at late stage of the disease (International Federation of Gynecology and Obstetrics (FIGO) stages IIIC and IV) and a high incidence of disease recurrence results in an overall survival of less than 20% at five years from diagnosis. Innovative treatments (target therapies and immunotherapeutic approaches) have been pursued with the aim to improve treatment efficacy and quality of life for the patients [2]. Integrated bioinformatics analysis of omics databases has been performed to identify genes, expression profiles, and signaling pathways that can serve as potential biomarker candidates for progression and prognosis of EOC [4,5]

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