Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics

非小细胞肺癌的代谢通路激活和免疫微环境特征:来自单细胞转录组学的启示

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Abstract

INTRODUCTION: In this study, we aim to provide a deep understanding of the tumor microenvironment (TME) and its metabolic characteristics in non-small cell lung cancer (NSCLC) through single-cell RNA sequencing (scRNAseq) data obtained from public databases. Given that lung cancer is a leading cause of cancer-related deaths globally and NSCLC accounts for the majority of lung cancer cases, understanding the relationship between TME and metabolic pathways in NSCLC is crucial for developing new treatment strategies. METHODS: Finally, machine learning algorithms were employed to construct a risk signature with strong predictive power across multiple independent cohorts. After quality control, 29,053 cells were retained, and PCA along with UMAP techniques were used to distinguish 13 primary cell subpopulations. Four highly activated metabolic pathways were identified within malignant cell subpopulations, which were further divided into seven distinct subgroups showing significant differences in differentiation potential and metabolic activity. WGCNA was utilized to identify gene modules and hub genes closely associated with these four metabolic pathways. RESULTS: Our analysis showed that DEGs between tumor and normal tissues were predominantly enriched in immune response and cell adhesion pathways. The comprehensive examination of our model revealed substantial variations in clinical and pathological characteristics, enriched pathways, cancer hallmarks, and immune infiltration scores between high-risk and low-risk groups. Wet lab experiments validated the role of KRT6B in NSCLC, demonstrating that KRT6B expression is elevated and it stimulates the proliferation of cancer cells. DISCUSSION: These observations not only enhance our understanding of metabolic reprogramming and its biological functions in NSCLC but also provide new perspectives for early detection, prognostic evaluation, and targeted therapy. However, future research should further explore the specific mechanisms of these metabolic pathways and their application potentials in clinical practice.

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