A library of gene expression signatures to illuminate normal and pathological lymphoid biology

Metabolism Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Immunological Reviews (Impact Factor: 12.91). 05/2006; 210:67-85. DOI: 10.1111/j.0105-2896.2006.00373.x
Source: PubMed

ABSTRACT Genomics has provided a lever to pry open lymphoid cells and examine their regulatory biology. The large body of available gene expression data has also allowed us to define the of coordinately expressed genes, termed gene expression signatures, which characterize the states of cellular physiology that reflect cellular differentiation, activation of signaling pathways, and the action of transcription factors. Gene expression signatures that reflect the action of individual transcription factors can be defined by perturbing transcription factor function using RNA interference (RNAi), small-molecule inhibition, and dominant-negative approaches. We have used this methodology to define gene expression signatures of various transcription factors controlling B-cell differentiation and activation, including BCL-6, B lymphocyte-induced maturation protein-1 (Blimp-1), X-box binding protein-1 (XBP1), nuclear factor-kappaB (NF-kappaB), and c-myc. We have also curated a wide variety of gene expression signatures from the literature and assembled these into a signature database. Statistical methods can define whether any signature in this database is differentially expressed in independent biological samples, an approach we have used to gain mechanistic insights into the origin and clinical behavior of B-cell lymphomas. We also discuss the use of genomic-scale RNAi libraries to identify genes and pathways that may serve as therapeutic targets in B-cell malignancies.

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Available from: Lloyd T Lam, Aug 17, 2015
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    • ". IRF4 Controls Essential Gene-Expression Programs in ABC DLBCL (A) IRF4 direct target genes grouped according to gene-expression signatures (Shaffer et al., 2006). Signatures with significant enrichment for IRF4 targets were grouped by function (Table S3A "
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    • "However, the mechanisms leading to this up-regulation is poorly understood. Previous reports had highlighted a correlation between NS expression and the presence of the active Myc oncogene (Dave et al 2006, Rosenwald et al 2002, Shaffer et al 2006). In this manuscript we further extend such a correlation to a large panel of human cancer cell lines (NC60) and show dramatic accumulation of NS in Myc-driven Bcell lymphomas isolated from Eu-Myc mice. "
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