Glutamine Metabolism-associated Molecular Heterogeneity and Prognosis in Pancreatic Adenocarcinoma

Pancreatic Adenocarcinoma (PAAD) is characterized by pronounced molecular heterogeneity and profound metabolic reprogramming. Glutamine metabolism plays a critical role in sustaining tumor growth and shaping the tumor microenvironment; however, its contribution to molecular heterogeneity, immune characteristics, and clinical outcomes in PAAD remains incompletely understood.

We conducted an integrative transcriptomic analysis utilizing transcriptomic and clinical data from TCGA, GTEx, and an independent GEO cohort to focus on genes involved in glutamine metabolism. Unsupervised consensus clustering was performed to define molecular subtypes associated with glutamine metabolism. Differential expression analysis, pathway enrichment analysis, and established transcriptome-based methods were applied to characterize subtype-specific biological features. Using LASSO-- Cox regression, a prognostic risk model was created and validated in internal and external cohorts. Multilevel biological validation was further conducted using immunohistochemistry data, pancreatic cancer cell line profiles, and single-cell RNA sequencing resources.

Two reproducible glutamine metabolism-associated molecular subtypes were identified, exhibiting distinct survival outcomes and immune landscapes. The metabolically aggressive subtype was associated with increased immune evasion potential and enrichment of pathways related to cell cycle progression, hypoxia, and metabolic dysregulation. An eight-gene prognostic signature demonstrated stable predictive performance across cohorts and remained independently associated with overall survival. Protein-level expression and single-cell analyses further supported the biological relevance of key prognostic genes.

These findings suggest that glutamine metabolism-associated heterogeneity may contribute to immune modulation and clinical divergence in PAAD. The integration of metabolic stratification with immune landscape characterization provides a biologically coherent framework for understanding tumor progression and therapeutic resistance.

This study establishes a glutamine metabolism-centered integrative framework that links molecular heterogeneity with immune modulation and clinical outcomes in PAAD. The identified biomarkers and stratification strategy provide biologically interpretable insights and may facilitate metabolic-based risk stratification and personalized therapeutic decision-making in pancreatic adenocarcinoma.