title: 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.
abstract: OBJECTIVE
  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.
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.
authors.forename: Kerry J
authors.initials: KJ
authors.lastname: Welsh
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.
authors.forename: Elena
authors.initials: E
authors.lastname: Nedelcu
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.
authors.forename: Amer
authors.initials: A
authors.lastname: Wahed
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.
authors.forename: Yu
authors.initials: Y
authors.lastname: Bai
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA.
authors.forename: Amitava
authors.initials: A
authors.lastname: Dasgupta
authors.affiliation: Department of Pathology and Laboratory Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA Nghia.D.Nguyen@uth.tmc.edu.
authors.forename: Andy
authors.initials: A
authors.lastname: Nguyen
mesh_terms: D000368:Aged; D016000:Cluster Analysis; D020732:Cytogenetic Analysis; D030541:Databases, Genetic; D005260:Female; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000235:genetics* / Q000401:mortality; D008297:Male; D008875:Middle Aged; D009154:Mutation; D000090243:Nucleophosmin; D011379:Prognosis
keywords: The Cancer Genome Atlas; acute myeloid leukemia; prognostic mutations