Objective: Necroptosis has been reported to play an important role in different cancers, including leukemia. However, biomarkers of necroptosis-related genes (NRGs) that help predict the prognosis of AML are still lacking. Our research aims to build a novel signature of NRGs that could enhance our understanding of the molecular heterogeneity in leukemia.
Method: Gene expression profiles as well as clinical features were downloaded from TCGA and GEO databases. Data analysis were executed using R software version 4.2.1 and GraphPad Prism version 9.0.0.
Result: Univariate cox regression and lasso regression were applied to identify survival-specific genes. Four genes including FADD, PLA2G4A, PYCARD and ZBP1 were considered as independent risk factors that affect the prognosis of patients. Risk scores were calculated according to the coefficient of four genes. Then clinical characteristics and risk scores were enrolled to construct a nomogram. CellMiner was also used to screen potential drugs and analyze the correlations between genes and drug sensitivity.
Conclusion: In general, we established a signature of four genes related to necroptosis that could be helpful for future risk stratification in patients with AML.
Keywords: Acute myeloid leukemia; mRNA; necroptosis; prognostic signature.