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Bioinformatics Analysis and Experimental Validation of Lactylation Related Genes in Lung Adenocarcinoma
Li Gao1, Yadi Zhang2,3, Fengrui Wu2,3
1Department of Respiratory and Critical Care Medicine, Fuyang People's Hospital, Fuyang, Anhui, 236012, People's Republic of China.
Purpose:
Lactylation, a novel post-translational modification, is dysregulated in various tumors and influences lung cancer progression. However, its role in lung adenocarcinoma (LUAD) remains unclear. Based on multi-omics analysis results, this study investigated lactylation levels in LUAD tissues and explored the dual research positioning of lactylation as a prognostic marker and therapeutic target.
Methods:
Lactylation levels in LUAD tissue microarrays were assessed using immunohistochemistry and immunofluorescence. Western blot analysis validated these findings. Differential expression analysis of lactylation-related genes was conducted using The Cancer Genome Atlas (TCGA, n=365), based on |log2 fold-change (FC)|≥2. KEGG pathway analysis identified key biological pathways, and COX regression analysis pinpointed prognostic genes. Single-cell RNA sequencing data from the GEO database validated these genes, with mitochondrial gene threshold <20%.
Results:
Lactylation levels were significantly elevated in LUAD tissues compared to adjacent non-cancerous tissues, as shown by immunohistochemistry and confirmed by Western blot analysis. Differential analysis identified 17 lactylation-related genes enriched in pathways such as AMPK signaling and cellular senescence. COX regression analysis identified five risk genes: KIF2C, MKI67, HMGA1, PFKP, and CCNA2. Validation with single-cell RNA sequencing data revealed high expression levels of these genes in LUAD tissues and the LUAD cell line H1299. Functional validation revealed that the 5 genes panel significantly regulates global lactylation modification in vitro.
Conclusion:
LUAD tissues exhibit elevated lactylation levels, suggesting their potential as prognostic biomarkers. The identified genes-KIF2C, MKI67, HMGA1, PFKP, and CCNA2-are highly expressed in cancerous tissues and correlate with LUAD prognosis. These findings highlight their value as tumor biomarkers and therapeutic targets, offering new opportunities for targeted LUAD treatments.
