Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data.
Deciphering transcription factor networks from microarray data remains difficult. This study presents a simple method to infer the regulation of transcription factors from microarray data based on well-characterized target genes. We generated a catalog containing transcription factors associated with 2720 target genes and 6401 experimentally validated regulations. When it was available, a distinction between transcriptional activation and inhibition was included for each regulation. Next, we built a tool (www.tfacts.org) that compares submitted gene lists with target genes in the catalog to detect regulated transcription factors. TFactS was validated with published lists of regulated genes in various models and compared to tools based on in silico promoter analysis. We next analyzed the NCI60 cancer microarray data set and showed the regulation of SOX10, MITF and JUN in melanomas. We then performed microarray experiments comparing gene expression response of human fibroblasts stimulated by different growth factors. TFactS predicted the specific activation of Signal transducer and activator of transcription factors by PDGF-BB, which was confirmed experimentally. Our results show that the expression levels of transcription factor target genes constitute a robust signature for transcription factor regulation, and can be efficiently used for microarray data mining.
Essaghir
Ahmed
A
de Duve Institute, Université Catholique de Louvain, MEXP74.30, avenue Hippocrates 74-75, B-1200 Brussels, Belgium.
Toffalini
Federica
F
Knoops
Laurent
L
Kallin
Anders
A
van Helden
Jacques
J
Demoulin
Jean-Baptiste
JB
D000077214:Becaplermin; D002377:Catalogs as Topic; D045744:Cell Line, Tumor; D002478:Cells, Cultured; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D010982:Platelet-Derived Growth Factor / Q000494:pharmacology; D020574:Proto-Oncogene Proteins c-sis; D015203:Reproducibility of Results; D050791:STAT Transcription Factors / Q000378:metabolism; D012984:Software; D014157:Transcription Factors / Q000378:metabolism*; D014584:User-Computer Interface
D010982:Platelet-Derived Growth Factor; D020574:Proto-Oncogene Proteins c-sis; D050791:STAT Transcription Factors; D014157:Transcription Factors; D000077214:Becaplermin