title: Transcriptomic response to differentiation induction.
abstract: BACKGROUND
  Microarrays used for gene expression studies yield large amounts of data. The processing of such data typically leads to lists of differentially-regulated genes. A common terminal data analysis step is to map pathways of potentially interrelated genes.
  
  
  METHODS
  We applied a transcriptomics analysis tool to elucidate the underlying pathways of leukocyte maturation at the genomic level in an established cellular model of leukemia by examining time-course data in two subclones of U-937 cells. Leukemias such as Acute Promyelocytic Leukemia (APL) are characterized by a block in the hematopoietic stem cell maturation program at a point when expansion of clones which should be destined to mature into terminally-differentiated effector cells get locked into endless proliferation with few cells reaching maturation. Treatment with retinoic acid, depending on the precise genomic abnormality, often releases the responsible promyelocytes from this blockade but clinically can yield adverse sequellae in terms of potentially lethal side effects, referred to as retinoic acid syndrome.
  
  
  RESULTS
  Briefly, the list of genes for temporal patterns of expression was pasted into the ABCC GRID Promoter TFSite Comparison Page website tool and the outputs for each pattern were examined for possible coordinated regulation by shared regelems (regulatory elements). We found it informative to use this novel web tool for identifying, on a genomic scale, genes regulated by drug treatment.
  
  
  CONCLUSIONS
  Improvement is needed in understanding the nature of the mutations responsible for controlling the maturation process and how these genes regulate downstream effects if there is to be better targeting of chemical interventions. Expanded implementation of the techniques and results reported here may better direct future efforts to improve treatment for diseases not restricted to APL.
authors.affiliation: Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov
authors.forename: G W
authors.initials: GW
authors.lastname: Patton
authors.forename: R
authors.initials: R
authors.lastname: Stephens
authors.forename: I A
authors.initials: IA
authors.lastname: Sidorov
authors.forename: X
authors.initials: X
authors.lastname: Xiao
authors.forename: R A
authors.initials: RA
authors.lastname: Lempicki
authors.forename: D S
authors.initials: DS
authors.lastname: Dimitrov
authors.forename: R H
authors.initials: RH
authors.lastname: Shoemaker
authors.forename: G
authors.initials: G
authors.lastname: Tudor
mesh_terms: D002454:Cell Differentiation; D045744:Cell Line, Tumor; D049109:Cell Proliferation; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D015536:Down-Regulation; D015972:Gene Expression Regulation, Neoplastic; D005809:Genes, Regulator; D042381:Granulocyte Precursor Cells / Q000378:metabolism; D006801:Humans; D020407:Internet; D007938:Leukemia / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011506:Proteins / Q000737:chemistry; D012333:RNA, Messenger / Q000378:metabolism; D013997:Time Factors; D014157:Transcription Factors / Q000378:metabolism; D014158:Transcription, Genetic; D014212:Tretinoin / Q000494:pharmacology / Q000633:toxicity; D020298:U937 Cells; D015854:Up-Regulation
chemical_list: D011506:Proteins; D012333:RNA, Messenger; D014157:Transcription Factors; D014212:Tretinoin