mirConnX: condition-specific mRNA-microRNA network integrator

mirConnX is a user-friendly web interface for inferring, displaying and parsing mRNA and microRNA (miRNA) gene regulatory networks. mirConnX combines sequence information with gene expression data analysis to create a disease-specific, genome-wide regulatory network. A prior, static network has been constructed for all human and mouse genes. It consists of computationally predicted transcription factor (TF)-gene associations and miRNA target predictions. The prior network is supplemented with known interactions from the literature. Dynamic TF- and miRNA-gene associations are inferred from user-provided expression data using an association measure of choice. The static and dynamic networks are then combined using an integration function with user-specified weights. Visualization of the network and subsequent analysis are provided via a very responsive graphic user interface. Two organisms are currently supported: Homo sapiens and Mus musculus. The intuitive user interface and large database make mirConnX a useful tool for clinical scientists for hypothesis generation and explorations. mirConnX is freely available for academic use at http://www.benoslab.pitt.edu/mirconnx

Environment Impacts the Metabolic Dependencies of Ras-Driven Non-Small Cell Lung Cancer

Cultured cells convert glucose to lactate, and glutamine is the major source of tricarboxylic acid (TCA)-cycle carbon, but whether the same metabolic phenotype is found in tumors is less studied. We infused mice with lung cancers with isotope-labeled glucose or glutamine and compared the fate of these nutrients in tumor and normal tissue. As expected, lung tumors exhibit increased lactate production from glucose. However, glutamine utilization by both lung tumors and normal lung was minimal, with lung tumors showing increased glucose contribution to the TCA cycle relative to normal lung tissue. Deletion of enzymes involved in glucose oxidation demonstrates that glucose carbon contribution to the TCA cycle is required for tumor formation. These data suggest that understanding nutrient utilization by tumors can predict metabolic dependencies of cancers in vivo. Furthermore, these data argue that the in vivo environment is an important determinant of the metabolic phenotype of cancer cells.National Science Foundation (U.S.) (Grant T32GM007287

Serial selection for invasiveness increases expression of miR-143/miR-145 in glioblastoma cell lines

<p>Abstract</p> <p>Background</p> <p>Glioblastoma multiforme (GBM) is the most common primary central nervous system malignancy and its unique invasiveness renders it difficult to treat. This invasive phenotype, like other cellular processes, may be controlled in part by microRNAs - a class of small non-coding RNAs that act by altering the expression of targeted messenger RNAs. In this report, we demonstrate a straightforward method for creating invasive subpopulations of glioblastoma cells (IM3 cells). To understand the correlation between the expression of miRNAs and the invasion, we fully profiled 1263 miRNAs on six different cell lines and two miRNAs, miR-143 and miR-145, were selected for validation of their biological properties contributing to invasion. Further, we investigated an ensemble effect of both miR-143 and miR-145 in promoting invasion.</p> <p>Methods</p> <p>By repeated serial invasion through Matrigel^®-coated membranes, we isolated highly invasive subpopulations of glioma cell lines. Phenotypic characterization of these cells included <it>in vitro </it>assays for proliferation, attachment, and invasion. Micro-RNA expression was compared using miRCURY arrays (Exiqon). In situ hybridization allowed visualization of the regional expression of miR-143 and miR-145 in tumor samples, and antisense probes were used investigate <it>in vitro </it>phenotypic changes seen with knockdown in their expression.</p> <p>Results</p> <p>The phenotype we created in these selected cells proved stable over multiple passages, and their microRNA expression profiles were measurably different. We found that two specific microRNAs expressed from the same genetic locus, miR-143 and miR-145, were over-expressed in our invasive subpopulations. Further, we also found that combinatorial treatment of these cells with both antisense-miRNAs (antimiR-143 and -145) will abrogated their invasion without decreasing cell attachment or proliferation.</p> <p>Conclusions</p> <p>To best of our knowledge, these data demonstrate for the first time that miR-143 and miR-145 regulate the invasion of glioblastoma and that miR-143 and -145 could be potential therapeutic target for anti-invasion therapies of glioblastoma patients.</p

Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations

MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental conditions

A Local Proinflammatory Signalling Loop Facilitates Adverse Age-Associated Arterial Remodeling

Background: The coincidence of vascular smooth muscle cells (VSMC) infiltration and collagen deposition within a diffusely thickened intima is a salient feature of central arterial wall inflammation that accompanies advancing age. However, the molecular mechanisms involved remain undefined. Methodology/Principal Findings: Immunostaining and immunoblotting of rat aortae demonstrate that a triad of proinflammatory molecules, MCP-1, TGF-b1, and MMP-2 increases within the aortic wall with aging. Exposure of VSMC isolated from 8-mo-old rats (young) to MCP-1 effects, via CCR-2 signaling, both an increase in TGF-b1 activity, up to levels of untreated VSMC from 30-mo-old (old) rats, and a concurrent increase in MMP-2 activation. Furthermore, exposure of young VSMC to TGF-b1 increases levels of MCP-1, and MMP-2 activation, to levels of untreated VSMC from old rats. This autocatalytic signaling loop that enhances collagen production and invasiveness of VSMC is effectively suppressed by si-MCP-1, a CCR2 antagonist, or MMP-2 inhibition. Conclusions/Significance: Threshold levels of MCP-1, MMP-2, or TGF-b1 activity trigger a feed-forward signaling mechanism that is implicated in the initiation and progression of adverse age-associated arterial wall remodeling. Intervention that suppressed this signaling loop may potentially retard age-associated adverse arterial remodeling

MicroRNA miR-34 Inhibits Human Pancreatic Cancer Tumor-Initiating Cells

Our results demonstrate that miR-34 may restore, at least in part, the tumor suppressing function of the p53 in p53-deficient human pancreatic cancer cells. Our data support the view that miR-34 may be involved in pancreatic cancer stem cell self-renewal, potentially via the direct modulation of downstream targets Bcl-2 and Notch, implying that miR-34 may play an important role in pancreatic cancer stem cell self-renewal and/or cell fate determination. Restoration of miR-34 may hold significant promise as a novel molecular therapy for human pancreatic cancer with loss of p53-miR34, potentially via inhibiting pancreatic cancer stem cells

A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma

Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio [HR] = 2.4; 95% CI = 1.4–3.8; p<0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1–2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4–2.8; p<0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04–1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy

Inflammation in the Tumor-Adjacent Lung as a Predictor of Clinical Outcome in Lung Adenocarcinoma

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression

MicroRNA-21 targets tumor suppressor genes ANP32A and SMARCA4

MicroRNA-21 (miR-21) is a key regulator of oncogenic processes. It is significantly elevated in the majority of human tumors and functionally linked to cellular proliferation, survival and migration. In this study, we used two experimental-based strategies to search for novel miR-21 targets. On the one hand, we performed a proteomic approach using two-dimensional differential gel electrophoresis (2D-DIGE) to identify proteins suppressed upon enhanced miR-21 expression in LNCaP human prostate carcinoma cells. The tumor suppressor acidic nuclear phosphoprotein 32 family, member A (ANP32A) (alias pp32 or LANP) emerged as the most strongly downregulated protein. On the other hand, we applied a mathematical approach to select correlated gene sets that are negatively correlated with primary-miR-21 (pri-miR-21) expression in published transcriptome data from 114 B-cell lymphoma cases. Among these candidates, we found tumor suppressor SMARCA4 (alias BRG1) together with the already validated miR-21 target, PDCD4. ANP32A and SMARCA4, which are both involved in chromatin remodeling processes, were confirmed as direct miR-21 targets by immunoblot analysis and reporter gene assays. Furthermore, knock down of ANP32A mimicked the effect of enforced miR-21 expression by enhancing LNCaP cell viability, whereas overexpression of ANP32A in the presence of high miR-21 levels abrogated the miR-21-mediated effect. In A172 glioblastoma cells, enhanced ANP32A expression compensated for the effects of anti-miR-21 treatment on cell viability and apoptosis. In addition, miR-21 expression clearly increased the invasiveness of LNCaP cells, an effect also seen in part upon downregulation of ANP32A. In conclusion, these results suggest that downregulation of ANP32A contributes to the oncogenic function of miR-21

ULK1 inhibition overcomes compromised antigen presentation and restores antitumor immunity in LKB1-mutant lung cancer

Inactivating mutations in LKB1/STK11 are present in roughly 20% of nonsmall cell lung cancers (NSCLC) and portend poor response to anti-PD-1 immunotherapy. Unexpectedly, we found that LKB1 deficiency correlated with elevated tumor mutational burden (TMB) in NSCLCs from nonsmokers and genetically engineered mouse models, despite the frequent association between high-TMB and anti-PD-1 treatment efficacy. However, LKB1 deficiency also suppressed antigen processing and presentation, which are associated with compromised immunoproteasome activity and increased autophagic flux. Immunoproteasome activity and antigen presentation were restored by inhibiting autophagy through targeting the ATG1/ULK1 pathway. Accordingly, ULK1 inhibition synergized with PD-1 antibody blockade, provoking effector T-cell expansion and tumor regression in Lkb1-mutant tumor models. This study reveals an interplay between the immunoproteasome and autophagic catabolism in antigen processing and immune recognition, and proposes the therapeutic potential of dual ULK1 and PD-1 inhibition in LKB1-mutant NSCLC as a strategy to enhance antigen presentation and to promote antitumor immunity