OBJECTIVE: Nucleotide excision repair (NER) has been associated with various types of malignant tumors. However, the precise roles of nucleotide excision repair-related genes (NERGs) in acute myeloid leukemia (AML) remain incompletely understood. Hence, this study aimed to develop a prognostic signature incorporating NERGs in AML, which could potentially predict patient outcomes.
MATERIALS AND METHODS: By querying the Genotype-Tissue Expression (GTEx), The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) databases, we acquired RNA-seq data and clinical information pertaining to AML. To identify differentially expressed NERGs (DE-NERGs), we employed the Wilcoxon rank-sum test. Based on the expression patterns of DE-NERGs with prognostic significance, patients were categorized into two subgroups. A prognostic signature was developed through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses to compare the differentially expressed genes (DEGs) between these two groups. Additionally, a nomogram was constructed using multivariate analysis. The biological pathways involved were elucidated through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA).
RESULTS: We developed a prognostic model based on an 11-gene signature. Furthermore, the risk score derived from this model was demonstrated to independently serve as a prognostic marker for patients diagnosed with AML.
CONCLUSIONS: Our prognostic model, based on NERGs, was developed and validated to provide insights into the onset and progression of AML and establish a foundation for more effective treatment. Our findings not only contribute to clinical decision-making but also underscore the significance of nucleotide excision repair. Furthermore, they may pave the way for the development of targeted therapeutic strategies specifically focused on this process.
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