背景:气虚痰湿(QPD)是肺腺癌(LUAD)最常见的中医证型之一。本研究旨在确定LUAD与QPD综合征的综合征特异性生物标志物。
方法:LUADQPD患者外周血单核细胞(PBMC),患有非QPD(N-QPD)的LUAD患者,收集和健康对照(H)并用RNA-seq分析以鉴定差异表达基因(DEGs)。计算每个DEG的受试者操作特征曲线下面积(AUC),和前10个最高AUCDEGs通过qRT-PCR进行验证。使用Logistic回归分析来建立用AUC评估的诊断模型。
结果:本研究共纳入135名个体(训练集:15个QPD,15N-QPD,15小时;验证集:30QPD,30N-QPD,30小时)。在QPD和N-QPD之间总共鉴定出1480个DEG。qRT-PCR结果显示DDR2的表达下调,PPARG上调,这与训练集的发现是一致的。我们用这两个基因开发了一个诊断模型。训练队列和验证队列中诊断模型的AUC分别为0.891和0.777。
结论:我们确定了两个基因(DDR2和PPARG)作为LUAD伴QPD综合征的综合征特异性生物标志物,并开发了一种新的诊断模型,有助于提高临床诊断的准确性和敏感性,为天然药物治疗LUAD提供新的靶点。
BACKGROUND: Qi deficiency and phlegm dampness (QPD) is one of the most common traditional Chinese medicine (TCM) syndromes in lung adenocarcinoma (LUAD). This study aimed to identify syndrome-specific biomarkers for LUAD with QPD syndrome.
METHODS: Peripheral blood mononuclear cells (PBMCs) from LUAD patients with QPD, LUAD patients with non-QPD (N-QPD), and healthy control (H) were collected and analyzed with RNA-seq to identify differentially expressed genes (DEGs). The area under the receiver operator characteristic curve (AUC) of each DEG was calculated, and the top 10 highest AUC DEGs were validated by qRT-PCR. Logistic regression analysis was used to develop a diagnostic model evaluated with AUC.
RESULTS: A total of 135 individuals were enrolled in this study (training set: 15 QPD, 15 N-QPD, 15 H; validation set: 30 QPD, 30 N-QPD, 30 H). A total of 1480 DEGs were identified between QPD and N-QPD. The qRT-PCR results showed that the expression of DDR2 was downregulated, and PPARG was upregulated, which was in line with the finding of the training set. We developed a diagnostic model with these two genes. The AUC of the diagnostic model in the training cohort and validation cohort was 0.891 and 0.777, respectively.
CONCLUSIONS: We identified the two genes (DDR2 and PPARG) as syndrome-specific biomarkers for LUAD with QPD syndrome and developed a novel diagnostic model, which may help to improve the accuracy and sensibility of clinical diagnosis and provide a new target for natural drug treatment of LUAD.