title: Network-based expression analysis reveals key genes related to glucocorticoid resistance in infant acute lymphoblastic leukemia.
abstract: OBJECTIVE
  Despite vast improvements that have been made in the treatment of children with acute lymphoblastic leukemia (ALL), the majority of infant ALL patients (~80 %, < 1 year of age) that carry a chromosomal translocation involving the mixed lineage leukemia (MLL) gene shows a poor response to chemotherapeutic drugs, especially glucocorticoids (GCs), which are essential components of all current treatment regimens. Although addressed in several studies, the mechanism(s) underlying this phenomenon have remained largely unknown. A major drawback of most previous studies is their primary focus on individual genes, thereby neglecting the putative significance of inter-gene correlations. Here, we aimed at studying GC resistance in MLL-rearranged infant ALL patients by inferring an associated module of genes using co-expression network analysis. The implications of newly identified candidate genes with associations to other well-known relevant genes from the same module, or with associations to known transcription factor or microRNA interactions, were substantiated using literature data.
  
  
  METHODS
  A weighted gene co-expression network was constructed to identify gene modules associated with GC resistance in MLL-rearranged infant ALL patients. Significant gene ontology (GO) terms and signaling pathways enriched in relevant modules were used to provide guidance towards which module(s) consisted of promising candidates suitable for further analysis.
  
  
  RESULTS
  Through gene co-expression network analysis a novel set of genes (module) related to GC-resistance was identified. The presence in this module of the S100 and ANXA genes, both well-known biomarkers for GC resistance in MLL-rearranged infant ALL, supports its validity. Subsequent gene set net correlation analyses of the novel module provided further support for its validity by showing that the S100 and ANXA genes act as 'hub' genes with potentially major regulatory roles in GC sensitivity, but having lost this role in the GC resistant phenotype. The detected module implicates new genes as being candidates for further analysis through associations with known GC resistance-related genes.
  
  
  CONCLUSIONS
  From our data we conclude that available systems biology approaches can be employed to detect new candidate genes that may provide further insights into drug resistance of MLL-rearranged infant ALL cases. Such approaches complement conventional gene-wise approaches by taking putative functional interactions between genes into account.
authors: Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
authors: Zaynab
authors: Z
authors: Mousavian
authors: School of Mathematics and Computer Science, University of Tehran, Tehran, Iran.
authors: Abbas
authors: A
authors: Nowzari-Dalini
authors: Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands.
authors: Ronald W
authors: RW
authors: Stam
authors: Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA.
authors: Yasir
authors: Y
authors: Rahmatallah
authors: Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. amasoudin@ut.ac.ir.
authors: Ali
authors: A
authors: Masoudi-Nejad
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use*; D019008:Drug Resistance, Neoplasm / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D005938:Glucocorticoids / Q000627:therapeutic use*; D011495:Histone-Lysine N-Methyltransferase / Q000235:genetics; D006801:Humans; D007223:Infant; D051788:Myeloid-Lymphoid Leukemia Protein / Q000235:genetics; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000188:drug therapy* / Q000235:genetics*
chemical_list: D000970:Antineoplastic Agents; D005938:Glucocorticoids; C497422:KMT2A protein, human; D051788:Myeloid-Lymphoid Leukemia Protein; D011495:Histone-Lysine N-Methyltransferase
keywords: Acute lymphoblastic leukemia; Drug resistance; Gene co-expression network; Glucocorticoid treatment; Systems biology