Novel prognostic genes and subclasses of acute myeloid leukemia revealed by survival analysis of gene expression data

• Published in: BMC medical genomics Vol. 14; no. 1; pp. 39 - 10
• Main Authors: Lai, Yanli, OuYang, Guifang, Sheng, Lixia, Zhang, Yanli, Lai, Binbin, Zhou, Miao
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 03.02.2021; BioMed Central; BMC
• Subjects: Acute myeloid leukemia; Adult; Aged; Biomarkers; Biomarkers, Tumor - genetics; Bone marrow; Cancer; Cytogenetics; Decision making; Female; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Leukemic; Gene Regulatory Networks; Genomes; Humans; Leukemia; Leukemia, Myeloid, Acute - genetics; Leukemia, Myeloid, Acute - mortality; Leukemia, Myeloid, Acute - pathology; Male; Medical prognosis; Middle Aged; Mortality; Mutation; Myeloid leukemia; Nucleophosmin; Oncology, Experimental; Overall survival; Prognosis; Ribonucleic acid; Risk score; RNA; RNA sequencing; Survival; Survival Analysis; The cancer genome atlas database; Weighted gene co-expression network analysis; China; The cancer genome atlas database; Risk score; Overall survival; Acute myeloid leukemia; Weighted gene co-expression network analysis

Acute myeloid leukemia (AML) is biologically heterogeneous diseases with adverse prognosis. This study was conducted to find prognostic biomarkers that could effectively classify AML patients and provide guidance for treatment decision making. Weighted gene co-expression network analysis was applied...