TY  - EJOU
AU  - Liu, Yu-Wei 
AU  - Lee, Yung-Kuo 
AU  - Chang, Kai-Fu 
AU  - Hsieh, Chung-Bao 
AU  - Chang, Chih-Hsuan 
AU  - Ko, Ching-Chung 
AU  - Lin, Hui-Ru 
AU  - Wu, Chi-Jen 
AU  - Yuan, Chien-Han 
AU  - Kumar, Sachin 
AU  - Solomon, Dahlak Daniel 
AU  - Xuan, Do Thi Minh 
AU  - Palekkode, Neethu 
AU  - Fathima, Ayman 
AU  - Lin, Hung-Yun 
AU  - Wang, Chih-Yang 
AU  - Yang, Chih-Jen 
AU  - Wu, Yuen-Jung 

TI  - Integrative Analysis of Glycosylation-Related Genes Reveals Prognostic Subtypes, Immune Evasion, and Therapeutic Vulnerabilities in Lung Adenocarcinoma
T2  - Oncology Research

PY  - 
VL  - 
IS  - 
SN  - 1555-3906

AB  - <b>Background:</b> Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and remains a leading cause of cancer-related mortality worldwide. Aberrant glycosylation contributes to tumor progression by regulating receptor signalling, immune evasion, and metastatic. However, the prognostic and therapeutic relevance of glycosylation-related genes (GRGs) in LUAD has not been comprehensively defined. Therefore, this study aimed to comprehensively evaluate GRG-associated molecular subtypes and their clinical and therapeutic relevance in LUAD. <b>Methods</b>: GRGs were curated from multiple public databases and integrated with transcriptomic and clinical data from The Cancer Genome Atlas LUAD cohort (TCGA-LUAD) with validation in Gene Expression Omnibus (GEO) datasets. Consensus clustering, pathway enrichment, and immune profiling were used to identify glycosylation-associated subtypes. A glycosylation activity scoring (Glyco. marker) was developed to quantify glycosylation features. Drug response prediction was analyzed using OncoPredict and the Genomics of Drug Sensitivity in Cancer (GDSC) database. Single-cell RNA sequencing (scRNA-seq) was analyzed to evaluate cell-type-specific GRG expression. Selected proteins were by immunohistochemistry (IHC) in LUAD tissue microarrays. <b>Results:</b> GRG expression stratified 513 LUAD patients into four molecular clusters with distinct clinical and immune characteristics. The Glyco.High group showed elevated expression of MGAT5 (mannosyl (α-1,6)-glycoprotein β-1,6-N-acetylglucosaminyltransferase), ST6GAL1 (β-galactoside α-2,6-sialyltransferase 1), GALNT7 (polypeptide N-acetylgalactosaminyltransferase 7), and FUT8 (fucosyltransferase 8), frequent tumor protein p53 (TP53) mutations, increased immune checkpoint expression, and enrichment of regulatory T cells. The Glyco. marker score predicted overall survival and was associated with stemness signatures. Drug response prediction suggested reduced sensitivity to platinum chemotherapy and epidermal growth factor receptor (EGFR) inhibitors but increased sensitivity to phosphoinositide 3-kinase/protein kinase B/mechanistic target of rapamycin (PI3K/AKT/mTOR) inhibitors. <b>Conclusion:</b> GRG-based molecular stratification identifies clinically distinct LUAD subtypes associated with immune regulation, tumor stemness, and therapeutic response. The Glyco. marker system provides a potential framework for prognostic assessment and precision oncology strategies in LUAD.
KW  - Lung adenocarcinoma; glycosylation; prognostic biomarker; tumor microenvironment; immune evasion; single-cell RNA sequencing; immunohistochemistry; precision oncology

DO  - 10.32604/or.2026.074013