Identification of Targeted Pathogenic Markers in Acute Myeloid Leukemia through Integrative Bioinformatics Analysis and Clinical Validation.

Acute myeloid leukemia (AML) is a type of hematological malignancy with diverse genetic pathogenesis. Identification of the targeted pathogenic markers could be useful for AML diagnosis and potential therapy. We collected 751 targeted and AML-related genes by integrating the results of multiple databases and then used the expression profile of TCGA-LAML to construct a coexpression function network of AML WGCNA. Based on the clinical phenotype and module trait relationship, we identified two modules (brown and yellow) as interesting dysfunction modules, which have a significant association with cytogenetics risk and FAB classification systems. GO enrichment and KEGG analysis showed that these modules are mainly involved with cancer-associated pathways, including MAPK signal pathway, p53 signal pathway, JAK-STAT signal pathway, TGF-beta signaling pathway, mTOR signaling pathway, VEGF signaling pathway, both associated with the occurrence of AML. Besides, using the STRING database, we discovered the top 10 hub genes in each module, including and in the brown module and and in the yellow module. The prognosis analysis result showed that six key pathogens have significantly affected the overall survival and prognosis in AML. Interestingly, with the most significant regulatory relationship in the yellow modules significantly positively correlated with the clinical phenotype of AML. We used qPCR and ELISA to verify and expression in our clinical samples. The results exhibited that and were both highly expressed in AML.