Identification and verification of prognostic genes related to sialic acid metabolism in non- small cell lung cancer

Sialic acid metabolism (SiaM) may regulate multiple pathological processes of non-small cell lung cancer (NSCLC) through sialyltransferase-mediated sialylation. This study aimed to identify SiaM-related prognostic genes. The transcriptome data and SiaM-related genes (SRGs) were obtained from public databases. Prognostic genes were identified using consensus clustering, differential expression, protein interaction, and regression analyses to build a model. Immune infiltration, somatic mutation, and enrichment analyses explored underlying mechanisms. Finally, gene expression levels were validated with clinical NSCLC samples. NEUROD1, CALB2, HNF4A, CDX2, CDH2, CALB1, and CDH17 were recognized as prognostic genes to build the prognostic model. Furthermore, six differential immune cells manifested remarkable dissimilarities in cell abundance between the high-risk group (HRG) and the low-risk group (LRG) such as resting mast cells. Next, enrichment analysis showed that enriched pathways might affect the progression of NSCLC. Moreover, the HRG patients were more prone to mutations. CDH17 exhibited the highest mutation frequency in NSCLC patients, and one of the most common types of mutations was amplification. In vitro experiments verified prognostic genes’ expression levels in NSCLC. This seven-gene model provides potential biomarkers and a theoretical basis for prognosis and therapy in NSCLC.