Abstract
The increasing incidence and mortality of thyroid cancer (THCA) exacerbates the global cancer burden. Glutamine metabolism is a hallmark metabolic feature of tumors, but its impact on the pathogenesis and progression of THCA remains unclear. Studies retrieved THCA data from TCGA and GEO databases. Cluster analysis, differential expression analysis, and weighted gene co-expression network analysis were used to identify key glutamine metabolism-related genes (GMRGs) in THCA. Identification of key genes through protein-protein interaction network construction, based on expression and diagnosis of internal and external datasets. Their functional role was systematically evaluated by competitive endogenous RNA network analysis, genomic alteration analysis, immune-related studies, and immune checkpoint analysis. Using GMRGs and differentially expressed genes in THCA, 6 markers (NOS2, OTC, NOS1, GLS2, UCP2, RIMKLA) were selected as references for THCA clustering. Differential analysis combined with weighted gene co-expression network analysis identified 173 GMRGs in THCA. The CytoHubba algorithm in the protein-protein interaction network identified 4 hub genes: MUC1, KIT, COMP, and MMP7. Subsequent validation showed a significant decrease in the expression of KIT in tumor samples (P < .05). Receiver operating characteristic curve (ROC) analysis showed excellent diagnostic performance with area under the curve values of 0.925, 0.945, 0.965, and 0.996 in the internal and external validation cohorts. Notably, KIT expression showed a significant difference between T and N phases (P < .05). In addition, we delineate a regulatory network of competitive endogenous RNAs that control KIT expression. Genomic alteration analysis reveals frequent KIT modifications in anaplastic thyroid carcinoma. Tumors with low KIT expression exhibited enhanced immune infiltration and significant correlation with immune checkpoint genes, including PDCD1LG2 and PDCD1 (P < .05). This study identifies KIT as a key GMRG in THCA, positioning it as a novel diagnostic biomarker and a potential therapeutic evaluation marker for tumor progression.