SUMMARY The tumor stroma is believed to contribute to some of the most malignant characteristics of epithelial tumors. However, signaling between stromal and tumor cells is complex and remains poorly understood. Here we show that the genetic inactivation of Pten in stromal fibroblasts of mouse mammary glands accelerated the initiation, progression and malignant transformation of mammary epithelial tumors. This was associated with the massive remodeling of the extra-cellular matrix (ECM), innate immune cell infiltration and increased angiogenesis. Loss of Pten in stromal fibroblasts led to increased expression, phosphorylation (T72) and recruitment of Ets2 to target promoters known to be involved in these processes. Remarkably, Ets2 inactivation in Pten stroma-deleted tumors ameliorated disruption of the tumor microenvironment and was sufficient to decrease tumor growth and progression. Global gene expression profiling of mammary stromal cells identified a Pten-specific signature that was highly represented in the tumor stroma of breast cancer patients. These findings identify the Pten-Ets2 axis as a critical stroma-specific signaling pathway that suppresses mammary epithelial tumors.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung fibrosis with a high mortality rate. In organ repair and remodeling, epigenetic events are important. MicroRNAs (miRNAs) regulate gene expression post-transcriptionally and can target epigenetic molecules important in DNA methylation. The miR-17z92 miRNA cluster is critical for lung development and lung epithelial cell homeostasis and is predicted to target fibrotic genes and DNA methyltransferase (DNMT)-1 expression. Objectives: We investigated the miR-17z92 cluster expression and its role in regulating DNA methylation events in IPF lung tissue. Methods: Expression and DNA methylation patterns of miR-17z92 were determined in human IPF lung tissue and fibroblasts and fibrotic mouse lung tissue. The relationship between the miR-17z92 cluster and DNMT-1 expression was examined in vitro. Using a murine model of pulmonary fibrosis, we examined the therapeutic potential of the demethylating agent, 59-aza-29-deoxycytidine. Measurements and Main Results: Compared with control samples, miR17z92 expression was reduced in lung biopsies and lung fibroblasts from patients with IPF, whereas DNMT-1 expression and methylation of the miR-17z92 promoter was increased. Several miRNAs from the miR-17z92 cluster targeted DNMT-1 expression resulting in a negative feedback loop. Similarly, miR-17z92 expression was reduced in the lungs of bleomycin-treated mice. Treatment with 59-aza-29-deoxycytidine in a murine bleomycin-induced pulmonary fibrosis model reduced fibrotic gene and DNMT-1 expression, enhanced miR-17z92 cluster expression, and attenuated pulmonary fibrosis. Conclusions: This study provides insight into the pathobiology of IPF and identifies a novel epigenetic feedback loop between miR-17z92 and DNMT-1 in lung fibrosis.Keywords: microRNA; miR-17z92; pulmonary fibrosis; DNA methylation; DNMT-1 Idiopathic pulmonary fibrosis (IPF) represents the most aggressive form of interstitial lung disease with a median survival of 3-5 years (1). Failure to resolve epithelial cell injury in the lung is critical to the pathogenesis of IPF (2-4). In addition, epithelialmesenchymal transition (EMT) (5), fibroblast proliferation and activation (6), and recruitment of inflammatory cells (7,8) all contribute to extracellular matrix accumulation in the lung (7). The current study focused on identifying the molecular mechanisms underlying the pathogenesis of IPF.Because changes in fibrotic gene expression (2, 9-11) and few genetic mutations have been identified in IPF (12, 13), we focused on microRNA (miRNA, miR) expression and epigenetic regulators in lung epithelial cells and fibroblasts. MiRNAs can either block translation or degrade target mRNAs (14,15). Notably, a single miRNA can regulate upward of 30 genes. MiRNAs can be encoded in intronic or exonic DNA regions and encoded in their own open reading frame and controlled by DNA promoter elements, such as DNA methylation by DNA methyltransferases (DNMTs) of CpG islands (15,16). Of the three DNMTs expressed in h...

The ras/Raf/Mek/Erk pathway plays a central role in coordinating endothelial cell activities during angiogenesis. Transcription factors Ets1 and Ets2 are targets of ras/Erk signaling pathways that have been implicated in endothelial cell function in vitro, but their precise role in vascular formation and function in vivo remains ill-defined. In this work, mutation of both Ets1 and Ets2 resulted in embryonic lethality at midgestation, with striking defects in vascular branching having been observed. The action of these factors was endothelial cell autonomous as demonstrated using Cre/loxP technology. Analysis of Ets1/Ets2 target genes in isolated embryonic endothelial cells demonstrated down-regulation of Mmp9, Bcl-X L , and cIAP2 in double mutants versus controls, and chromatin immunoprecipitation revealed that both Ets1 and Ets2 were loaded at target promoters. Consistent with these observations, endothelial cell apoptosis was significantly increased both in vivo and in vitro when both Ets1 and Ets2 were mutated. These results establish essential and overlapping functions for Ets1 and Ets2 in coordinating endothelial cell functions with survival during embryonic angiogenesis. (Blood. 2009;114:1123-1130) IntroductionAngiogenesis, the biologic process by which endothelial cells (ECs) form new blood vessels from an existing vascular network, is a critical process in normal vertebrate embryonic development, as well as in processes like wound healing and inflammation in adults. Angiogenesis is also an essential element in many pathologic conditions, including cancer. 1,2 Angiogenesis is regulated by a balance of both positive and negative signaling events mediated by growth factors and their receptors as well as by cell adhesion to the extracellular matrix. [1][2][3][4] These complex signaling and cell adhesion interactions alter the growth, migration, survival, and differentiation of ECs through modulation of the intracellular signaling pathways that control these processes. [1][2][3][4][5] Among these pathways, the ras/Raf/Mek/Erk pathway has been proposed to play a central role in coordinating these cellular activities during development and tumor angiogenesis. For example, gene knockouts of B-raf and Mek-1 point to their role in placental vascular formation during extraembryonic development, although their action in embryonic development is redundant. 6,7 Expression of dominant-negative Raf in the tumor vasculature in a transplantation model increases EC apoptosis and decreases tumor growth, 8 and sustained Erk activity is critical for EC migration and angiogenesis in the chick chorioallantoic membrane assay. 9 In cell culture studies, Erk signaling has been implicated in EC survival. [10][11][12] ECs are especially sensitive to apoptotic signals during angiogenesis, and the sustained activation of Erk signaling by the combination of growth factor receptors and integrin adhesion may be important in preventing cell death during this process. 9,10 The downstream targets of Erks that mediate these effects on ECs re...

BackgroundIntegration of transcriptomic and metabolomic data improves functional interpretation of disease-related metabolomic phenotypes, and facilitates discovery of putative metabolite biomarkers and gene targets. For this reason, these data are increasingly collected in large (> 100 participants) cohorts, thereby driving a need for the development of user-friendly and open-source methods/tools for their integration. Of note, clinical/translational studies typically provide snapshot (e.g. one time point) gene and metabolite profiles and, oftentimes, most metabolites measured are not identified. Thus, in these types of studies, pathway/network approaches that take into account the complexity of transcript-metabolite relationships may neither be applicable nor readily uncover novel relationships. With this in mind, we propose a simple linear modeling approach to capture disease-(or other phenotype) specific gene-metabolite associations, with the assumption that co-regulation patterns reflect functionally related genes and metabolites.ResultsThe proposed linear model, metabolite ~ gene + phenotype + gene:phenotype, specifically evaluates whether gene-metabolite relationships differ by phenotype, by testing whether the relationship in one phenotype is significantly different from the relationship in another phenotype (via a statistical interaction gene:phenotype p-value). Statistical interaction p-values for all possible gene-metabolite pairs are computed and significant pairs are then clustered by the directionality of associations (e.g. strong positive association in one phenotype, strong negative association in another phenotype). We implemented our approach as an R package, IntLIM, which includes a user-friendly R Shiny web interface, thereby making the integrative analyses accessible to non-computational experts. We applied IntLIM to two previously published datasets, collected in the NCI-60 cancer cell lines and in human breast tumor and non-tumor tissue, for which transcriptomic and metabolomic data are available. We demonstrate that IntLIM captures relevant tumor-specific gene-metabolite associations involved in known cancer-related pathways, including glutamine metabolism. Using IntLIM, we also uncover biologically relevant novel relationships that could be further tested experimentally.ConclusionsIntLIM provides a user-friendly, reproducible framework to integrate transcriptomic and metabolomic data and help interpret metabolomic data and uncover novel gene-metabolite relationships. The IntLIM R package is publicly available in GitHub (https://github.com/mathelab/IntLIM) and includes a user-friendly web application, vignettes, sample data and data/code to reproduce results.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2085-6) contains supplementary material, which is available to authorized users.