N-glycosylation and receptor tyrosine kinase signaling affect claudin-3 levels in colorectal cancer cells

Changes in protein levels in different components of the apical junctional complex occur in colorectal cancer (CRC). Claudin-3 is one of the main constituents of tight junctions, and its overexpression can increase the paracellular flux of macromolecules, as well as the malignant potential of CRC cells. The aim of this study was to investigate the molecular mechanisms involved in the regulation of claudin-3 and its prognostic value in CRC. In silico evaluation in each of the CRC consensus molecular subtypes (CMSs) revealed that high expression levels of CLDN3 (gene encoding claudin-3) in CMS2 and CMS3 worsened the patients' long-term survival, whereas a decrease in claudin-3 levels concomitant with a reduction in phosphorylation levels of epidermal growth factor receptor (EGFR) and insulin-like growth factor 1 receptor (IGF1R) could be achieved by inhibiting N-glycan biosynthesis in CRC cells. We also observed that specific inactivation of these receptor tyrosine kinases (RTKs) led to a decrease in claudin-3 levels, and this regulation seems to be mediated by phospholipase C (PLC) and signal transducer and activator of transcription 3 (STAT3) in CRC cells. RTKs are modulated by their N-linked glycans, and inhibition of N-glycan biosynthesis decreased the claudin-3 levels; therefore, we evaluated the correlation between N-glycogenes and CLDN3 expression levels in each of the CRC molecular subtypes. The CMS1 (MSI immune) subtype concomitantly exhibited low expression levels of CLDN3 and N-glycogenes (MGAT5, ST6GAL1, and B3GNT8), whereas CMS2 (canonical) exhibited high gene expression levels of CLDN3 and N-glycogenes (ST6GAL1 and B3GNT8). A robust positive correlation was also observed between CLDN3 and B3GNT8 expression levels in all CMSs. These results support the hypothesis of a mechanism integrating RTK signaling and N-glycosylation for the regulation of claudin-3 levels in CRC, and they suggest that CLDN3 expression can be used to predict the prognosis of patients identified as CMS2 or CMS3.