Zhou Jiejun, Zhang Kun, Yang Tian, Li Anqi, Li Meng, Peng Xiaojing, Chen Mingwei
Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710000, China.
Heliyon. 2024 Apr 9;10(8):e29383. doi: 10.1016/j.heliyon.2024.e29383. eCollection 2024 Apr 30.
The role of glycosyltransferase (GT) genes in lung adenocarcinoma (LUAD) needs further elucidation. Thus, our study aims to identify the prognostic gene signature of LUAD and explore its molecular functions.
We initially extracted GT gene sets from the database, and obtained mRNA expression levels and clinical data from The Cancer Genome Atlas (TCGA) database. For constructing a prognostic model for GT genes, we utilized univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Using the model, patients were categorized into high- and low-risk groups. Additionally, we evaluated differences in tumor immune infiltration between these groups and identified potential therapeutic drugs. Finally, we experimentally validated the expression levels of these crucial prognostic genes.
We developed a risk score comprising nine GT genes (C1GALT1, FUT1, GALNT2, PLOD2, POMK, PYGB, ST3GAL6, UGT2B11, UGT3A1). Patients were then categorized into low- and high-risk groups based on this score. The low-risk group showed superior overall survival (OS) compared to the high-risk group. There were significantly distinct tumor immune microenvironment statuses observed between the two groups. We identified potential therapeutic drugs, including the MEK inhibitor (PD-184352). Finally, we verified the expression of these nine GT genes through immunohistochemistry (IHC) staining and quantitative real-time PCR (qPCR).
We identified a distinct LUAD GT gene signature, and these differentially expressed mRNAs could serve as valuable prognostic biomarkers and therapeutic targets. Furthermore, we experimentally validated their expression levels and identified potential therapeutic agents.
糖基转移酶（GT）基因在肺腺癌（LUAD）中的作用尚需进一步阐明。因此，我们的研究旨在确定LUAD的预后基因特征并探索其分子功能。
我们首先从数据库中提取GT基因集，并从癌症基因组图谱（TCGA）数据库中获取mRNA表达水平和临床数据。为构建GT基因的预后模型，我们采用了单变量、最小绝对收缩和选择算子（LASSO）以及多变量Cox回归分析。利用该模型，将患者分为高风险组和低风险组。此外，我们评估了两组之间肿瘤免疫浸润的差异并确定了潜在的治疗药物。最后，我们通过实验验证了这些关键预后基因的表达水平。
我们开发了一个包含9个GT基因（C1GALT1、FUT1、GALNT2、PLOD2、POMK、PYGB、ST3GAL6、UGT2B11、UGT3A1）的风险评分。然后根据该评分将患者分为低风险组和高风险组。低风险组的总生存期（OS）优于高风险组。两组之间观察到明显不同的肿瘤免疫微环境状态。我们确定了潜在的治疗药物，包括MEK抑制剂（PD-184352）。最后，我们通过免疫组织化学（IHC）染色和定量实时PCR（qPCR）验证了这9个GT基因的表达。
我们确定了一个独特的LUAD GT基因特征，这些差异表达的mRNA可作为有价值的预后生物标志物和治疗靶点。此外，我们通过实验验证了它们的表达水平并确定了潜在的治疗药物。
