Biologyarticle2026-10-11

N-linked glycoproteomic and proteomic characterization of esophageal squamous cell carcinoma cell lines

Open access0 citations

Abstract

Esophageal squamous cell carcinoma (ESCC) is an aggressive disease with a low survival rate. While considerable progress has been made in uncovering the biological mechanisms of the disease, diagnosing ESCC at an early stage remains challenging. Altered N-glycosylation patterns are hallmarks of various cancers, and identifying glycosylation changes in cancer has paved the way to identify novel diagnostic and therapeutic markers. Quantitative N-glycoproteomic profiling was carried out on a panel of ESCC cell lines, TE-1, TE-2, TE-5, TE-8 and a non-neoplastic cell line, Het-1A. Glycopeptides derived from these cell lines were enriched by size-exclusion chromatography and analysed on an Orbitrap Exploris 480 instrument. Data were searched using pGlyco3. Global proteome profiling of these cells was performed, and the data were searched using Proteome Discoverer. Glycoproteomic analysis of ESCC cell lines led to the identification of 1,368 N-glycopeptides containing 375 glycosylation sites derived from 247 glycoproteins. Of these, 167 glycopeptides were significantly altered (≥ 2-fold cut-off, p -value < 0.05) between tumor and normal cell lines. Global proteomic analysis identified 7,503 proteins, of which 1,030 were differentially expressed (≥ 2-fold cut-off, p -value < 0.05) in ESCC cell lines compared to Het-1A. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of altered proteins and glycoproteins revealed enrichment of extracellular matrix-receptor interaction and focal adhesion pathways. This study reports differentially abundant N-glycopeptides and alterations in multiple enzymes involved in glycosylation pathways that may play a role in driving ESCC progression. Furthermore, these findings suggest that the identified glycoproteins may serve as candidate molecules for future biomarker studies and warrant further verification and validation in ESCC patient samples to determine their clinical relevance.

// Source

View paper (DOI)Open access versionOpenAlexDiscover OncologyPublished 2026-10-11

Authors: Srijon Munshi, Kishore Garapati, Neha Joshi, Vivek Ghose, Hariprabu K. Gopal, Gunveen S. Sachdeva, Krishnappa Ramachandrappa, Purushottam Chavan, Govind Babu, Naveena A. N. Kumar, Akhilesh Pandey, Vishalakshi Nanjappa

Institutions: Manipal Academy of Higher Education, Mayo Clinic, Institute of Bioinformatics, Kidwai Memorial Institute of Oncology, HCG Cancer Hospital