PO-475 Unravelling the role of sialylation in targeted therapy resistance using 3D cancer models

Abstract

IntroductionIn the scenario of personalised medicine, targeted therapies are currently the focus of cancer drug development. These drugs can block the growth and spread of tumour cells by interfering with key molecules of malignancy. Receptor tyrosine kinases, major targets for treatment of advanced gastric cancer, are transmembrane glycoprotein receptors whose glycan modifications have been shown to modulate the receptor activation. In this work, we have addressed the role of aberrant glycosylation, specifically of sialylation, in gastric cancer malignancy and therapy resistance.Material and methodsTo mimic the in vivotumour features, an innovative 3D high-throughput cell culture methodology has been developed for gastric cancer cells. After in-depth characterisation of the gastric cancer spheroids, we evaluated the resistance of cell models glycoengineered for key sialylation-related enzymes by subjecting the spheroids to tyrosine kinase inhibitors that are currently in clinical use and preclinical trials.Results and discussionsThe phenotypical and functional parameters assessed disclose that cell sialylation leads to different cellular adhesive and invasive features. Furthermore, we demonstrate that by applying 3D cell culture methods, the cell glycocalix undergoes changes compared to the conventional 2D culture systems. Remarkably, our glycomodels display strikingly different cell cytotoxicity response to several inhibitors of major oncogenic receptors. Furthermore, distinct activation levels of cell receptors are observed by applying targeted therapy drugs, altogether suggesting sialylation as an important mechanism of cancer drug resistance.ConclusionOur results demonstrate that cell glycosylation, in addition to being a key feature of tumour progression, plays a critical role in therapy resistance to tyrosine kinase inhibitors in gastric cancer. These findings shed new light on the mechanisms underlying cancer drug resistance and propose aberrant sialylation as new predictive biomarker for patients’ treatment response.