肺腺癌（LUAD）是非小细胞肺癌的主要亚型，由于其异质性和复杂的肿瘤微环境（TME），继续对治疗结果提出挑战。核苷酸代谢失调已被确定为肿瘤发生的一个重要因素，表明其作为治疗靶点的潜力。本研究使用非负矩阵分解 (NMF) 聚类、加权相关网络分析分析了来自癌症基因组图谱 (TCGA) 的 LUAD 样本（WGCNA）以及各种机器学习技术。我们通过大规模数据分析和单细胞测序研究了核苷酸代谢与临床特征和免疫微环境相关的作用。通过RT-qPCR、Western Blot、免疫组化、小鼠皮下肿瘤形成等体内外实验，我们进一步验证了关键核苷酸代谢基因在细胞系和动物中的功能。核苷酸代谢基因将LUAD患者分为两种不同的类型具有显着预后差异的亚型。与活跃的核苷酸代谢途径相关的“C1”亚型表现出较差的预后和更具侵袭性的肿瘤表型。此外，根据 28 个关键基因的表达计算出的核苷酸代谢相关评分 (NMRS) 可以有效区分患者的结果以及与致癌途径和免疫反应的预测关联。通过整合各种免疫浸润算法，我们描绘了核苷酸代谢特征基因与肿瘤微环境之间的关联，并通过分析与免疫化疗相关的单细胞测序数据集来表征它们在细胞水平上的分布差异。最后，我们证明了关键核苷酸代谢基因 AUNIP 的差异表达作为癌基因促进 LUAD 细胞增殖，并与肿瘤免疫浸润相关。该研究强调了核苷酸代谢在 LUAD 进展和预后中的关键作用，强调 NMRS临床结果和治疗反应的有价值的生物标志物。具体来说，AUNIP 作为一种关键的致癌基因，为 LUAD 的新型治疗策略提供了一个有前景的靶点。版权所有 © 2024 Luo、Wang、Zeng、Chen 和 Wang。

Lung adenocarcinoma (LUAD), a predominant subtype of non-small cell lung cancers, continues to challenge treatment outcomes due to its heterogeneity and complex tumor microenvironment (TME). Dysregulation in nucleotide metabolism has been identified as a significant factor in tumorigenesis, suggesting its potential as a therapeutic target.This study analyzed LUAD samples from The Cancer Genome Atlas (TCGA) using Non-negative Matrix Factorization (NMF) clustering, Weighted Correlation Network Analysis (WGCNA), and various machine learning techniques. We investigated the role of nucleotide metabolism in relation to clinical features and immune microenvironment through large-scale data analysis and single-cell sequencing. Using in vivo and in vitro experiments such as RT-qPCR, Western Blot, immunohistochemistry, and subcutaneous tumor formation in mice, we further validated the functions of key nucleotide metabolism genes in cell lines and animals.Nucleotide metabolism genes classified LUAD patients into two distinct subtypes with significant prognostic differences. The 'C1' subtype associated with active nucleotide metabolism pathways showed poorer prognosis and a more aggressive tumor phenotype. Furthermore, a nucleotide metabolism-related score (NMRS) calculated from the expression of 28 key genes effectively differentiated between patient outcomes and predicted associations with oncogenic pathways and immune responses. By integrating various immune infiltration algorithms, we delineated the associations between nucleotide metabolism signature genes and the tumor microenvironment, and characterized their distribution differences at the cellular level by analyzing single-cell sequencing dataset related to immunochemotherapy. Finally, we demonstrated the differential expression of the key nucleotide metabolism gene AUNIP acts as an oncogene to promote LUAD cell proliferation and is associated with tumor immune infiltration.The study underscores the pivotal role of nucleotide metabolism in LUAD progression and prognosis, highlighting the NMRS as a valuable biomarker for clinical outcomes and therapeutic responses. Specifically, AUNIP functions as a critical oncogene, offering a promising target for novel treatment strategies in LUAD.Copyright © 2024 Luo, Wang, Zeng, Chen and Wang.