Metabolic reprogramming plays a significant role in the advancement of lung adenocarcinoma (LUAD), yet the precise metabolic changes remain incompletely understood. This study aims to uncover metabolic indicators associated with the progression of LUAD.
A total of 1083 subjects were recruited, including 670 LUAD, 135 benign lung nodules (BLN) and 278 healthy controls (HC). Gas chromatography-mass spectrometry (GC/MS) was used to identify and quantify plasma metabolites. Odds ratios (ORs) were calculated to determine LUAD risk factors, and machine learning algorithms were utilized to differentiate LUAD from BLN.
High levels of oxalate, glycolate, glycine, glyceric acid, aminomalonic acid, and creatinine were identified as risk factors for LUAD (adjusted ORs>1.2, P<0.03). Remarkably, oxalate emerged as a distinctive metabolic risk factor exhibiting a strong correlation with the progression of LUAD (adjusted OR=5.107, P<0.001; advanced-stage vs. early-stage). The Random Forest (RF) model demonstrated a high degree of efficacy in distinguishing between LUAD and BLN (accuracy = 1.00 and 0.73, F1-score= 1.00 and 0.79, and AUC = 1.00 and 0.76 in the training and validation sets, respectively). TCGA and GTEx gene expression data have shown that lactate dehydrogenase A (LDHA), a crucial enzyme involved in oxalate metabolism, is increasingly expressed in the progression of LUAD. High LDHA expression levels in LUAD patients are also linked to poor prognoses (HR=1.66, 95% CI=1.34-2.07, P<0.001).
This study reveals risk factors associated with LUAD.