Bioinformatics analysis to determine prognostic mutations of 72 de novo acute myeloid leukemia cases from the Cancer Genome Atlas (TCGA) with 23 most common mutations and no abnormal cytogenetics

Objectives. Up to 40% of acute myeloid leukemia (AML) patients have normal cytogenetics (CN-AML) but they may have gene mutations. An important issue in the treatment of CN-AML is how gene mutation patterns may help with patient management. The Cancer Genome Atlas (TCGA) database has data from 200 cases of de novo AML including cytogenetics, gene mutations, and survival duration (prognosis). Methods. Cases with the most common mutations and no cytogenetic abnormalities were selected from the TCGA. Unsupervised neural network analysis was performed to group them into clusters according to their pattern of mutations and survival. Results. 72 cases of CN-AML with the 23 most common mutations were obtained from TCGA. Clustering was found to be based on 6 mutations, with the following prognostic groups: (a) good: NPM1, CEBPA, or TET2, (b) intermediate: NPM1/DNMT3A, or other mutations, (c) poor: RUNX1, FLT3-ITD, FLT3-ITD/NPM1, or FLT3-ITD/CEBPA. Some discrepancy between our results and those from previous studies is most likely due to inclusion of AML cases transformed from myeloproliferative neoplasms or myelodysplastic syndrome in previous studies. Conclusions. This study provides further molecular characterization and prognostic data most specific for the de novo subgroup of CN-AML patients.