# Sialylation Inhibition Impairs Migration and Promotes Adhesion of GBM Cells

## TL;DR

This study shows that inhibiting sialylation in glioblastoma cells reduces their migration and increases adhesion, suggesting sialic acids could be new biomarkers or drug targets.

## Contribution

The study identifies specific sialyltransferases and sialic acids in GBM cells and demonstrates their role in migration and adhesion through inhibition experiments.

## Key findings

- ST6GAL1, ST3GAL2, and ST8SIA4 are upregulated in GBM and linked to poor patient survival.
- Inhibiting sialyltransferases reduces GBM cell migration and increases adhesion.
- Aberrant sialic acid expression is crucial for GBM cell behavior.

## Abstract

Aberrant sialylation has been associated with many types of tumors, characterized by aggressiveness and undifferentiated state. However, not exhaustive investigations have been performed on the sialylation status in glioblastoma multiforme (GBM), the most common primary and lethal malignant brain tumor in humans. Hence, in this study we performed a comprehensive characterization of the sialylation status in GBM evaluating specific sialyltransferases and various types of sialic acids (Sias) in different GBM cell lines. First, through in silico analysis we showed that the sialyltransferases ST6GAL1, ST3GAL2 and ST8SIA4 are significantly up-regulated in GBM tissues and related to lower patient survival. Then, we evaluated the expression levels of these sialyltransferases and their related Sias and observed a high variability among the different GBM cell lines. In addition, using the pan-sialyltransferase inhibitor 3-Fax, we highlighted the role of sialylation in some of the main oncogenic properties of GBM. Indeed, a significant reduction in mobility and migration capacity along with increased adhesiveness of GBM cells was observed upon sialyltransferases inhibition. Our findings showed that aberrant expression of different Sias types is crucial for cell migration and adhesion ability of GBM cells, suggesting that Sias might represent biomarkers for GBM and be useful to design innovative therapeutic strategies.