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非小细胞肺癌中的代谢途径激活与免疫微环境特征:来自单细胞转录组学的见解

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

作者信息

Liu Yanru, Liu Hanmin, Xiong Ying

机构信息

Department of Pediatric Pulmonology and Immunology, West China Second University Hospital, Sichuan University, Chengdu, China.

Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China.

出版信息

Front Immunol. 2025 Feb 28;16:1546764. doi: 10.3389/fimmu.2025.1546764. eCollection 2025.

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.

摘要

引言

在本研究中,我们旨在通过从公共数据库获得的单细胞RNA测序(scRNAseq)数据,深入了解非小细胞肺癌(NSCLC)中的肿瘤微环境(TME)及其代谢特征。鉴于肺癌是全球癌症相关死亡的主要原因,且NSCLC占肺癌病例的大多数,了解NSCLC中TME与代谢途径之间的关系对于开发新的治疗策略至关重要。

方法

最后,采用机器学习算法构建了一个在多个独立队列中具有强大预测能力的风险特征。经过质量控制后,保留了29,053个细胞,并使用主成分分析(PCA)和均匀流形近似与投影(UMAP)技术来区分13个主要细胞亚群。在恶性细胞亚群中鉴定出四条高度激活的代谢途径,这些途径进一步分为七个不同的亚组,它们在分化潜能和代谢活性方面存在显著差异。加权基因共表达网络分析(WGCNA)被用于识别与这四条代谢途径密切相关的基因模块和枢纽基因。

结果

我们的分析表明,肿瘤组织与正常组织之间的差异表达基因(DEG)主要富集在免疫反应和细胞粘附途径中。对我们模型的综合检查显示,高风险组和低风险组在临床和病理特征、富集途径、癌症特征以及免疫浸润评分方面存在显著差异。湿实验室实验验证了角蛋白6B(KRT6B)在NSCLC中的作用,表明KRT6B表达升高并刺激癌细胞增殖。

讨论

这些观察结果不仅加深了我们对NSCLC中代谢重编程及其生物学功能的理解,还为早期检测、预后评估和靶向治疗提供了新的视角。然而,未来的研究应进一步探索这些代谢途径的具体机制及其在临床实践中的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a34/11906459/116a78d324d0/fimmu-16-1546764-g001.jpg

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