Abstract C213: Protein interaction analysis of mll-aff4 and mll-fel oncogenic fusion proteins using data mining approach.

Abstract

Abstract Mixed-lineage leukemia (MLL) is a transcriptional co-activator that plays an essential role in early development and hematopoiesis. MLL H3K4 methyltransferase activity mediates chromatin remodeling associated with epigenetic regulation of transcription activation. Multiple chromosomal translocations of MLL gene lead to its fusion to numerous partner genes and production of chimeric proteins, which are enrolled in progression of similar phenotypes of leukemia [5]. However, protein interaction models of different MLL fusions are still debated. To assess the pattern of protein interactions of MLL chimeras, we have performed protein-protein interaction (PPI) network analysis for two MLL fusion proteins, MLL-FEL - t(4;11)(q21;q23) and MLL-AFF4 - ins(5;11)(q31;q13q23), which are involved in acute leukemia progression [2]. Protein interaction data was extracted from data mining software GPS-Prot v. 2.0 [4]. PPI network visualization and network parameters evaluation were performed using Cytoscape v. 2.8 [7]. Cluster analysis was made by MCODE plug-in. The statistical significance of cluster extraction was assessed as described [3]. Comparative experimental interaction data taken from previously published papers were manually discarded from our analysis. Our results show that each of the components of studied fusion proteins in native form compose highly interconnected distinct regions. MLL PPI network analysis reveals a clique cluster with cluster density equal to 1, indicating that MLL interacters are united in protein macromolecular complex, which is in a good accordance with previously published experimental data [6]. Worth of mention, that FEL and AFF4 proteins form the same clique clusters, which also is in a good congruence with experimentally obtained data [1]. Therefore, we assume that the MLL-AFF4 and MLL-FEL fusion proteins generate the identical PPI network, which underlie the manifestation of similar malignancy. Further corroboration of this result will confirm the assumption that different fusions can bring to the same disease network, which could possibly has its impact in leukemia therapeutical approaches. To obtain more detailed pattern of protein interactions of MLL-caused leukemias further network analysis is required. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C213. Citation Format: Grant Henry Hovhannisyan, Ashot Vardan Marqaryan. Protein interaction analysis of mll-aff4 and mll-fel oncogenic fusion proteins using data mining approach. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C213.