To study the diagnostic and prognostic value of GADD45α in AML based on bioinformatics and its preliminary experimental validation

Abstract

Abstract Objectives Exploring the expression status, prognostic value, immune infiltration, potential functions, and mechanisms of GADD45α in AML using bioinformatics. Methods Using the GEPIA2 database to analyze the expression levels of GADD45α in AML and other cancers, and to assess the correlation between GADD45α levels and prognosis in AML. Conducting immune regulation gene analysis, immune checkpoint analysis, and immune infiltration analysis of GADD45α in AML in Sangerbox. Obtaining the protein interaction network with GADD45α from the STRING database and conducting GO and KEGG analysis in Sangerbox. By establishing stable overexpression of GADD45α in AML cells, using CCK-8 and Annexin V-FITC/APC to respectively detect the effects of overexpression and knockdown of GADD45α on cell proliferation and apoptosis in AML cells. Validating the diagnostic and prognostic value of GADD45α in AML. All data were statistically analyzed using SPSS 23.0 software. Results GADD45α is mostly downregulated in cancer, and is downregulated in AML, which is associated with poor prognosis. We found significant correlation between GADD45α and immune cells in AML in Sangerbox. We also found that GADD45α expression in AML is closely related to 43 checkpoints, including VEGFB, ARG1, KIR2DL1, KIR2DL3, TIGIT, and is closely related to five types of immune cells, including chemokines, receptors, MHC, immune inhibitors, and immune stimulators. This indicates that GADD45α may coordinate the activity of these ICP genes in different signaling pathways and may become an ideal immunotherapy target. We found that GADD45α interacts with TDG, FOXO3, TP53, CDKN1A, CDK1, AURKA, CCNB1, PCNA, MAP2K6, and MAP3K4 proteins, and after GO and KEGG analysis, we found that its biological function may be involved in cell cycle arrest, mitotic G1/S checkpoint, and other processes. KEGG enrichment of GADD45α is related to cell senescence, cell cycle, p53 signaling pathway, and FoxO signaling pathway. Overexpression of GADD45α can inhibit the proliferation of leukemia cells, promote apoptosis, and after GADD45α knockdown, it can promote the proliferation of leukemia cells and inhibit apoptosis. Conclusions GADD45α is a prognostic marker for AML, and its expression levels are associated with various immune cell molecules, immune checkpoints, and immune regulatory genes. Detecting GADD45α levels helps predict the prognosis of AML, providing a new method for optimizing and monitoring the effectiveness of anti-AML immunotherapy. Further validation of the GADD45α signaling pathway is more conducive to the discovery of occurrence and development mechanisms, and is more beneficial for patient treatment.