Integrating bulk and single-cell transcriptomic data to construct a risk model for histidine metabolism-related epithelial cell features in lung adenocarcinoma, predicting prognosis and immune landscape

Key Points

• This research aims to create a prognostic model that utilizes transcriptomic data to study epithelial cell features related to histidine metabolism in lung adenocarcinoma.
• Combined bulk and single-cell transcriptomic data
• Focused on epithelial cell-specific genes
• Analyzed immune characteristics in LUAD patients
• The model accurately distinguishes lung adenocarcinoma patients based on histidine metabolism
• Epithelial cells are identified as a critical population influencing metabolism and immune response