Abstract

Alterations of RUNX1 in acute myeloid leukemia (AML) are associated with either a more favorable outcome in the case of the RUNX1/RUNX1T1 fusion or unfavorable prognosis in the case of point mutations. In this project we aimed to identify genes responsible for the observed differences in outcome that are common to both RUNX1 alterations. Analyzing four AML gene expression data sets (n = 1514), a total of 80 patients with RUNX1/RUNX1T1 and 156 patients with point mutations in RUNX1 were compared. Using the statistical tool of mediation analysis we identified the genes CD109, HOPX, and KIAA0125 as candidates for mediator genes. In an analysis of an independent validation cohort, KIAA0125 again showed a significant influence with respect to the impact of the RUNX1/RUNX1T1 fusion. While there were no significant results for the other two genes in this smaller validation cohort, the observed relations linked with mediation effects (i.e., those between alterations, gene expression and survival) were almost without exception as strong as in the main analysis. Our analysis demonstrates that mediation analysis is a powerful tool in the identification of regulative networks in AML subgroups and could be further used to characterize the influence of genetic alterations.

Details

Title
Mediation analysis reveals common mechanisms of RUNX1 point mutations and RUNX1/RUNX1T1 fusions influencing survival of patients with acute myeloid leukemia
Author
Hornung, Roman 1   VIAFID ORCID Logo  ; Jurinovic, Vindi 1 ; Batcha, Aarif M N 2 ; Bamopoulos, Stefanos A 3 ; Rothenberg-Thurley, Maja 3 ; Amler, Susanne 4 ; Sauerland, Maria Cristina 4 ; Berdel, Wolfgang E 5 ; Wörmann, Bernhard J 6 ; Bohlander, Stefan K 7 ; Braess, Jan 8 ; Hiddemann, Wolfgang 9 ; Lehmann, Sören 10 ; Mareschal, Sylvain 11   VIAFID ORCID Logo  ; Spiekermann, Karsten 9 ; Metzeler, Klaus H 9 ; Herold, Tobias 9   VIAFID ORCID Logo  ; Boulesteix, Anne-Laure 1 

 Institute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany 
 Institute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich, Munich, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany 
 Department of Medicine III, University Hospital, LMU Munich, Munich, Germany 
 Institute of Biostatistics and Clinical Research, University of Muenster, Muenster, Germany 
 Department of Medicine A, Hematology and Oncology, University of Muenster, Muenster, Germany 
 German Society of Hematology and Oncology, Berlin, Germany 
 Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand 
 Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany 
 German Cancer Consortium (DKTK), partner site Munich, Munich, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Medicine III, University Hospital, LMU Munich, Munich, Germany 
10  Department of Medical Sciences, Uppsala University Hospital, Uppsala, Sweden; Department of Medicine, Karolinska Institute, Stockholm, Sweden 
11  Department of Medical Sciences, Uppsala University Hospital, Uppsala, Sweden; Department of Biosciences and Nutrition, Karolinska Institute, Stockholm, Sweden 
Pages
1-13
Publication year
2018
Publication date
Jul 2018
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2076901094
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.