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The genome of the fruitfly Drosophila melanogastercontains a single p53-like protein, phylogenetically related to the ancestor of the mammalian p53 family of tumor suppressors. We reasoned that a comprehensive map of the protein interaction profile of Drosophila p53 (Dmp53) might help identify conserved interactions of the entire p53 family in man. Using a genome-scale in vitro expression cloning approach, we identified 91 previously unreported Dmp53 interactors, considerably expanding the current Drosophila p53 interactome. Looking for evolutionary conservation of these interactions, we tested 41 mammalian orthologs and found that 37 bound to one or more p53-family members when overexpressed in human cells. An RNAi-based functional assay for modulation of the p53 pathway returned five positive hits, validating the biological relevance of these interactions. One p53 interactor is GTPBP4, a nucleolar protein involved in 60S ribosome biogenesis. We demonstrate that GTPBP4 knockdown induces p53 accumulation and activation in the absence of nudeolar disruption. In breast tumors with wild-type p53, increased expression of GTPBP4 correlates with reduced patient survival, emphasizing a potential relevance of this regulatory axis in cancer. in vitro expression cloning | p73 | p63 | NOG1 doi/10.1073/pnas.1002447107

The identification of direct targets of transcription factors is a key problem in the study of gene regulatory networks. However, the use of high throughput experimental methods, such as ChiP-chip and ChiP-sequencing, is limited by their high cost and strong dependence on cellular type and context. We developed a computational method for the genome-wide identification of functional transcription factor binding sites based on positional weight matrices, comparative genomics, and gene expression profiling. The method was applied to Stat3, a transcription factor playing crucial roles in inflammation, immunity and oncogenesis, and able to induce distinct subsets of target genes in different cell types or conditions. A newly generated positional weight matrix enabled us to assign affinity scores of high specificity, as measured by EMSA competition assays. Phylogenetic conservation with 7 vertebrate species was used to select the binding sites most likely to be functional. Validation was carried out on predicted sites within genes identified as differentially expressed in the presence or absence of Stat3 by microarray analysis. Twelve of the fourteen sites tested were bound by Stat3 in vivo, as assessed by Chromatin Immunoprecipitation, allowing us to identify 9 Stat3 transcriptional targets. Given its high validation rate, and the availability of large transcription factor-dependent gene expression datasets obtained under diverse experimental conditions, our approach appears to be a valid alternative to high-throughput experimental assays for the discovery of novel direct targets of transcription factors. chromatin immunoprecipitation | phylogenetic footprint | positional weight matrix | Stat3 binding sites | Stat3 target genes

A hallmark of cancer, including pancreatic ductal adenocarcinoma (PDA), is a massive stromal and inflammatory reaction. Many efforts have been made to identify the anti- or protumoral role of cytokines and immune subpopulations within the stroma. Here, we investigated the role of interleukin-17A (IL17A) and its effect on tumor fibroblasts and the tumor microenvironment. We used a spontaneous PDA mouse model (KPC) crossed to IL17A knockout mice to show an extensive desmoplastic reaction, without impaired immune infiltration. Macrophages, especially CD80+ and T cells, were more abundant at the earlier time point. In T cells, a decrease in FoxP3+ cells and an increase in CD8+ T cells were observed in KPC/IL17A-/- mice. Fibroblasts isolated from IL17A+/+ and IL17A-/- KPC mice revealed very different messenger RNA (mRNA) and protein profiles. IL17A-/- fibroblasts displayed the ability to restrain tumor cell invasion by producing factors involved in extracellular matrix remodeling, increasing T cell recruitment, and producing higher levels of cytokines and chemokines favoring T helper 1 cell recruitment and activation and lower levels of those recruiting myeloid/granulocytic immune cells. Single-cell quantitative PCR on isolated fibroblasts confirmed a very divergent profile of IL17A-proficient and -deficient cells. All these features can be ascribed to increased levels of IL17F observed in the sera of IL17A-/- mice, and to the higher expression of its cognate receptor (IL17RC) specifically in IL17A-/- cancer-associated fibroblasts (CAFs). In addition to the known effects on neoplastic cell transformation, the IL17 cytokine family uniquely affects fibroblasts, representing a suitable candidate target for combinatorial immune-based therapies in PDA. [ABSTRACT FROM AUTHOR]

Invariant natural killer T cells (iNKT) cells are T lymphocytes displaying innate effector functions, acquired through a distinct thymic developmental program regulated by microRNAs (miRNAs). Deleting miRNAs by Dicer ablation (Dicer KO) in thymocytes selectively impairs iNKT cell survival and functional differentiation. To unravel this miRNA-dependent program, we systemically identified transcripts that were differentially expressed between WT and Dicer KO iNKT cells at different differentiation stages and predicted to be targeted by the iNKT cell-specific miRNAs. TGF-β receptor II (TGF-βRII), critically implicated in iNKT cell differentiation, was found up-regulated in iNKT Dicer KO cells together with enhanced TGF-β signaling. miRNA members of the miR-17~92 family clusters were predicted to target Tgfbr2 mRNA upon iNKT cell development. iNKT cells lacking all three miR-17~92 family clusters (miR-17~92, miR-106a~363, miR-106b~25) phenocopied both increased TGF-βRII expression and signaling, and defective effector differentiation, displayed by iNKT Dicer KO cells. Consistently, genetic ablation of TGF-β signaling in the absence of miRNAs rescued iNKT cell differentiation. These results elucidate the global impact of miRNAs on the iNKT cell developmental program and uncover the targeting of a lineage-specific cytokine signaling by miRNAs as a mechanism regulating innate-like T-cell development and effector differentiation. [ABSTRACT FROM AUTHOR]

Competitive endogenous (ce)RNAs cross-regulate each other through sequestration of shared microRNAs and form complex regulatory networks based on their microRNA signature. However, the molecular requirements for ceRNA cross-regulation and the extent of ceRNA networks remain unknown. Here, we present a mathematical mass-action model to determine the optimal conditions for ceRNA activity in silico. This model was validated using phosphatase and tensin homolog (PTEN) and its ceRNA VAMP (vesicle-associated membrane protein)-associated protein A (VAPA) as paradigmatic examples. A computational assessment of the complexity of ceRNA networks revealed that transcription factor and ceRNA networks are intimately intertwined. Notably, we found that ceRNA networks are responsive to transcription factor up-regulation or their aberrant expression in cancer. Thus, given optimal molecular conditions, alterations of one ceRNA can have striking effects on integrated ceRNA and transcriptional networks. [ABSTRACT FROM AUTHOR]

The identification of direct targets of transcription factors is a key problem in the study of gene regulatory networks. However, the use of high throughput experimental methods, such as ChIP-chip and ChIP-sequencing, is limited by their high cost and strong dependence on cellular type and context. We developed a computational method for the genome-wide identification of functional transcription factor binding sites based on positional weight matrices, comparative genomics, and gene expression profiling. The method was applied to Stat3, a transcription factor playing crucial roles in inflammation, immunity and oncogenesis, and able to induce distinct subsets of target genes in different cell types or conditions. A newly generated positional weight matrix enabled us to assign affinity scores of high specificity, as measured by EMSA competition assays. Phylogenetic conservation with 7 vertebrate species was used to select the binding sites most likely to be functional. Validation was carried out on predicted sites within genes identified as differentially expressed in the presence or absence of Stat3 by microarray analysis. Twelve of the fourteen sites tested were bound by Stat3 in vivo, as assessed by Chromatin Immunoprecipitation, allowing us to identify 9 Stat3 transcriptional targets. Given its high validation rate, and the availability of large transcription factor-dependent gene expression datasets obtained under diverse experimental conditions, our approach appears to be a valid alternative to high-throughput experimental assays for the discovery of novel direct targets of transcription factors. [ABSTRACT FROM AUTHOR]