Risk Factors in Serrated Pathway Lesions: N-Glycosylation Profile as a Potential Biomarker of Progression to Malignancy.

INTRODUCTION

The serrated pathway contributes to interval colorectal cancers, highlighting the need for new biomarkers to assess lesion progression risk. The β1,6-GlcNAc branched -glycans expression in CRC cells was associated with an invasive phenotype and with immune evasion. Therefore, this study aims to identify potential risk factors for progression of serrated lesions (SLs) to malignancy, analyzing the -glycosylation profile of epithelial/infiltrating immune cells.

METHODS

A retrospective cohort study was performed with data from 53 colonoscopies (48 patients). Sixty-three serrated pathway lesions (SPLs) were characterized based on -glycosylation profile (lectin histochemistry/flow cytometry) and expression. Statistical analysis was performed to search for associations between the glycoprofile and clinical variables from each patient.

RESULTS

Increased β1,6-GlcNAc branched -glycans expression in epithelial cells is found associated with age ( = 0.007 in SPL), smoking ( = 0.038 in SL), increased BMI ( = 0.036 in sessile serrated lesions [SSL]), and polyp dimensions ≥10 mm ( = 0.001 in SL), while increased expression of these structures on immune cells is associated with synchronous CA number (CD4T cells: = 0.016; CD8T cells: = 0.044 in SL) and female gender ( = 0.026 in SL). Moreover, a lower high-mannose -glycans expression in immune cells is associated with smoking ( = 0.010 in SPL) and synchronous CA presence ( = 0.010 in SPL). Higher expression of these glycans is associated with female ( = 0.016 in SL) and male ( = 0.044 in SL) gender, left colon location ( = 0.028), dysplasia ( = 0.028), and adenocarcinoma ( = 0.010).

CONCLUSIONS

We identified an association between an abnormal glycoprofile and several clinical risk factors, proposing the glycosylation profile as a potential biomarker of tumor progression in the serrated pathway. The glycosylation anatomopathological profile analysis could be further used to decide shorter interval follow-up in patients with SPL.