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: 10.12). 05/2006; 210(1):67-85. DOI: 10.1111/j.0105-2896.2006.00373.x
Source: PubMed


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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    • "MM tumor profiles from patients enrolled on the APEX Study 039 of BTZ were obtained from NCBI Gene Expression Omnibus (GEO; GSE9782; Mulligan et al., 2007). Three Xbp1 signature gene sets were used: XBP1_Staudt_SigDB reflects Xbp1 overexpression in B cells (Shaffer et al., 2006) and together with other lymphoid transcription factor signatures was obtained from http:// lymphochip.nih.gov/signaturedb/; V$XBP1_01 represents genes with promoters containing a conserved Xbp1 motif and is from the Broad MSigDB at http://www.broadinstitute.org/gsea/msigdb/index.jsp; XBP1_MM and the related Ire1 signature, IRE1_MM, were generated by shRNA knockdown of Xbp1 or Ire1 in MM cells. "
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    ABSTRACT: Proteasome inhibitor (PI) resistance mechanisms in multiple myeloma (MM) remain controversial. We report the existence of a progenitor organization in primary MM that recapitulates maturation stages between B cells and plasma cells and that contributes to clinical PI resistance. Xbp1s(-) tumor B cells and pre-plasmablasts survive therapeutic PI, preventing cure, while maturation arrest of MM before the plasmablast stage enables progressive disease on PI treatment. Mechanistically, suppression of Xbp1s in MM is shown to induce bortezomib resistance via de-commitment to plasma cell maturation and immunoglobulin production, diminishing endoplasmic reticulum (ER) front-loading and cytotoxic susceptibility to PI-induced inhibition of ER-associated degradation. These results reveal the tumor progenitor structure in MM and highlight its role in therapeutic failure.
    Cancer cell 09/2013; 24(3):289-304. DOI:10.1016/j.ccr.2013.08.009 · 23.52 Impact Factor
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    • "An alternative approach is to generate signatures that reflect a specific biological process or outcome [9-11] or sets of coexpressed genes based upon correlation matrices [12-14]. One issue complicating analysis of any cancer gene expression data is the heterogeneity of samples. "
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    ABSTRACT: Biopsies taken from individual tumours exhibit extensive differences in their cellular composition due to the inherent heterogeneity of cancers and vagaries of sample collection. As a result genes expressed in specific cell types, or associated with certain biological processes are detected at widely variable levels across samples in transcriptomic analyses. This heterogeneity also means that the level of expression of genes expressed specifically in a given cell type or process, will vary in line with the number of those cells within samples or activity of the pathway, and will therefore be correlated in their expression. Using a novel 3D network-based approach we have analysed six large human cancer microarray datasets derived from more than 1,000 individuals. Based upon this analysis, and without needing to isolate the individual cells, we have defined a broad spectrum of cell-type and pathway-specific gene signatures present in cancer expression data which were also found to be largely conserved in a number of independent datasets. The conserved signature of the tumour-associated macrophage is shown to be largely-independent of tumour cell type. All stromal cell signatures have some degree of correlation with each other, since they must all be inversely correlated with the tumour component. However, viewed in the context of established tumours, the interactions between stromal components appear to be multifactorial given the level of one component e.g. vasculature, does not correlate tightly with another, such as the macrophage.
    BMC Genomics 07/2013; 14(1):469. DOI:10.1186/1471-2164-14-469 · 3.99 Impact Factor
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    • "They can be complemented by for example host response, stromal or even NF-кB specific gene expression signatures [22-25]. Recent combinations of in vitro cell interventions with systems biology allowed the prediction of potential oncogenic pathways involved in B cell transformation [26-28]. Furthermore, in vitro studies showed that combined STAT3 and NF-кB pathway activities are central to ABC-like lymphoma cells [22,29,30]. "
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    ABSTRACT: Background Aggressive Non-Hodgkin lymphomas (NHL) are a group of lymphomas derived from germinal centre B cells which display a heterogeneous pattern of oncogenic pathway activation. We postulate that specific immune response associated signalling, affecting gene transcription networks, may be associated with the activation of different oncogenic pathways in aggressive Non-Hodgkin lymphomas (NHL). Methodology The B cell receptor (BCR), CD40, B-cell activating factor (BAFF)-receptors and Interleukin (IL) 21 receptor and Toll like receptor 4 (TLR4) were stimulated in human transformed germinal centre B cells by treatment with anti IgM F(ab)2-fragments, CD40L, BAFF, IL21 and LPS respectively. The changes in gene expression following the activation of Jak/STAT, NF-кB, MAPK, Ca2+ and PI3K signalling triggered by these stimuli was assessed using microarray analysis. The expression of top 100 genes which had a change in gene expression following stimulation was investigated in gene expression profiles of patients with Aggressive non-Hodgkin Lymphoma (NHL). Results αIgM stimulation led to the largest number of changes in gene expression, affecting overall 6596 genes. While CD40L stimulation changed the expression of 1194 genes and IL21 stimulation affected 902 genes, only 283 and 129 genes were modulated by lipopolysaccharide or BAFF receptor stimulation, respectively. Interestingly, genes associated with a Burkitt-like phenotype, such as MYC, BCL6 or LEF1, were affected by αIgM. Unique and shared gene expression was delineated. NHL-patients were sorted according to their similarity in the expression of TOP100 affected genes to stimulated transformed germinal centre B cells The αIgM gene module discriminated individual DLBCL in a similar manner to CD40L or IL21 gene modules. DLBCLs with low module activation often carry chromosomal MYC aberrations. DLBCLs with high module activation show strong expression of genes involved in cell-cell communication, immune responses or negative feedback loops. Using chemical inhibitors for selected kinases we show that mitogen activated protein kinase- and phosphoinositide 3 kinase-signalling are dominantly involved in regulating genes included in the αIgM gene module. Conclusion We provide an in vitro model system to investigate pathway activation in lymphomas. We defined the extent to which different immune response associated pathways are responsible for differences in gene expression which distinguish individual DLBCL cases. Our results support the view that tonic or constitutively active MAPK/ERK pathways are an important part of oncogenic signalling in NHL. The experimental model can now be applied to study the therapeutic potential of deregulated oncogenic pathways and to develop individual treatment strategies for lymphoma patients.
    Cell Communication and Signaling 12/2012; 10(1):43. DOI:10.1186/1478-811X-10-43 · 3.38 Impact Factor
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