Pluripotent Stem Cell-Derived Hematopoietic Progenitors Are Unable to Downregulate Key Epithelial-Mesenchymal Transition-Associated miRNAs.

Hematopoietic stem cells derived from pluripotent stem cells could be used as an alternative to bone marrow transplants. Deriving these has been a long-term goal for researchers. However, the success of these efforts has been limited with the cells produced able to engraft in the bone marrow of recipient animals only in very low numbers. There is evidence that defects in the migratory and homing capacity of the cells are due to mis-regulation of miRNA expression and are responsible for their failure to engraft. We compared the miRNA expression profile of hematopoietic progenitors derived from pluripotent stem cells to those derived from bone marrow and found that numerous miRNAs are too highly expressed in hematopoietic progenitors derived from pluripotent stem cells, and that most of these are inhibitors of epithelial-mesenchymal transition or metastasis (including miR-200b, miR-200c, miR-205, miR-148a, and miR-424). We hypothesize that the high expression of these factors, which promote an adherent phenotype, may be causing the defect in hematopoietic differentiation. However, inhibiting these miRNAs, individually or in multiplex, was insufficient to improve hematopoietic differentiation in vitro, suggesting that other miRNAs and/or genes may be involved in this process. Stem Cells 2018;36:55-64.

MicroRNA profiling associated with non-small cell lung cancer: next generation sequencing detection, experimental validation, and prognostic value.

BACKGROUND: The average five-year survival for non-small cell lung cancer (NSCLC) patients is approximately 15%. Emerging evidence indicates that microRNAs (miRNAs) constitute a new class of gene regulators in humans that may play an important role in tumorigenesis. Hence, there is growing interest in studying their role as possible new biomarkers whose expression is aberrant in cancer. Therefore, in this study we identified dysregulated miRNAs by next generation sequencing (NGS) and analyzed their prognostic value. METHODS: Sequencing by oligo ligation detection technology was used to identify dysregulated miRNAs in a training cohort comprising paired tumor/normal tissue samples (N = 32). We validated 22 randomly selected differentially-expressed miRNAs by quantitative real time PCR in tumor and adjacent normal tissue samples (N = 178). Kaplan-Meier survival analysis and Cox regression were used in multivariate analysis to identify independent prognostic biomarkers. RESULTS: NGS analysis revealed that 39 miRNAs were dysregulated in NSCLC: 28 were upregulated and 11 were downregulated. Twenty-two miRNAs were validated in an independent cohort. Interestingly, the group of patients with high expression of both miRNAs (miR-21high and miR-188high) showed shorter relapse-free survival (RFS) and overall survival (OS) times. Multivariate analysis confirmed that this combined signature is an independent prognostic marker for RFS and OS (p = 0.001 and p < 0.0001, respectively). CONCLUSIONS: NGS technology can specifically identify dysregulated miRNA profiles in resectable NSCLC samples. MiR-21 or miR-188 overexpression correlated with a negative prognosis, and their combined signature may represent a new independent prognostic biomarker for RFS and OS.

Integrated gene set analysis for microRNA studies.

MOTIVATION: Functional interpretation of miRNA expression data is currently done in a three step procedure: select differentially expressed miRNAs, find their target genes, and carry out gene set overrepresentation analysis Nevertheless, major limitations of this approach have already been described at the gene level, while some newer arise in the miRNA scenario.Here, we propose an enhanced methodology that builds on the well-established gene set analysis paradigm. Evidence for differential expression at the miRNA level is transferred to a gene differential inhibition score which is easily interpretable in terms of gene sets or pathways. Such transferred indexes account for the additive effect of several miRNAs targeting the same gene, and also incorporate cancellation effects between cases and controls. Together, these two desirable characteristics allow for more accurate modeling of regulatory processes. RESULTS: We analyze high-throughput sequencing data from 20 different cancer types and provide exhaustive reports of gene and Gene Ontology-term deregulation by miRNA action. AVAILABILITY AND IMPLEMENTATION: The proposed methodology was implemented in the Bioconductor library mdgsa http://bioconductor.org/packages/mdgsa For the purpose of reproducibility all of the scripts are available at https://github.com/dmontaner-papers/gsa4mirna CONTACT: : david.montaner@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Babelomics 5.0: functional interpretation for new generations of genomic data.

Babelomics has been running for more than one decade offering a user-friendly interface for the functional analysis of gene expression and genomic data. Here we present its fifth release, which includes support for Next Generation Sequencing data including gene expression (RNA-seq), exome or genome resequencing. Babelomics has simplified its interface, being now more intuitive. Improved visualization options, such as a genome viewer as well as an interactive network viewer, have been implemented. New technical enhancements at both, client and server sides, makes the user experience faster and more dynamic. Babelomics offers user-friendly access to a full range of methods that cover: (i) primary data analysis, (ii) a variety of tests for different experimental designs and (iii) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context. In addition to the public server, local copies of Babelomics can be downloaded and installed. Babelomics is freely available at: http://www.babelomics.org.

Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.

BACKGROUND: Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. METHODS: A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. RESULTS: New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. CONCLUSION: The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

The protease MT1-MMP drives a combinatorial proteolytic program in activated endothelial cells.

The mechanism by which proteolytic events translate into biological responses is not well understood. To explore the link of pericellular proteolysis to events relevant to capillary sprouting within the inflammatory context, we aimed at the identification of the collection of substrates of the protease MT1-MMP in endothelial tip cells induced by inflammatory stimuli. We applied quantitative proteomics to endothelial cells (ECs) derived from wild-type and MT1-MMP-null mice to identify the substrate repertoire of this protease in TNF-α-activated ECs. Bioinformatics analysis revealed a combinatorial MT1-MMP proteolytic program, in which combined rather than single substrate processing would determine biological decisions by activated ECs, including chemotaxis, cell motility and adhesion, and vasculature development. MT1-MMP-deficient ECs inefficiently processed several of these substrates (TSP1, CYR61, NID1, and SEM3C), validating the model. This novel concept of MT1-MMP-driven combinatorial proteolysis in angiogenesis might be extendable to proteolytic actions in other cellular contexts.

Large-scale transcriptional profiling and functional assays reveal important roles for Rho-GTPase signalling and SCL during haematopoietic differentiation of human embryonic stem cells.

Understanding the transcriptional cues that direct differentiation of human embryonic stem cells (hESCs) and human-induced pluripotent stem cells to defined and functional cell types is essential for future clinical applications. In this study, we have compared transcriptional profiles of haematopoietic progenitors derived from hESCs at various developmental stages of a feeder- and serum-free differentiation method and show that the largest transcriptional changes occur during the first 4 days of differentiation. Data mining on the basis of molecular function revealed Rho-GTPase signalling as a key regulator of differentiation. Inhibition of this pathway resulted in a significant reduction in the numbers of emerging haematopoietic progenitors throughout the differentiation window, thereby uncovering a previously unappreciated role for Rho-GTPase signalling during human haematopoietic development. Our analysis indicated that SCL was the 11th most upregulated transcript during the first 4 days of the hESC differentiation process. Overexpression of SCL in hESCs promoted differentiation to meso-endodermal lineages, the emergence of haematopoietic and erythro-megakaryocytic progenitors and accelerated erythroid differentiation. Importantly, intrasplenic transplantation of SCL-overexpressing hESC-derived haematopoietic cells enhanced recovery from induced acute anaemia without significant cell engraftment, suggesting a paracrine-mediated effect.

Differential lipid partitioning between adipocytes and tissue macrophages modulates macrophage lipotoxicity and M2/M1 polarization in obese mice.

OBJECTIVE: Obesity-associated insulin resistance is characterized by a state of chronic, low-grade inflammation that is associated with the accumulation of M1 proinflammatory macrophages in adipose tissue. Although different evidence explains the mechanisms linking the expansion of adipose tissue and adipose tissue macrophage (ATM) polarization, in the current study we investigated the concept of lipid-induced toxicity as the pathogenic link that could explain the trigger of this response. RESEARCH DESIGN AND METHODS: We addressed this question using isolated ATMs and adipocytes from genetic and diet-induced murine models of obesity. Through transcriptomic and lipidomic analysis, we created a model integrating transcript and lipid species networks simultaneously occurring in adipocytes and ATMs and their reversibility by thiazolidinedione treatment. RESULTS: We show that polarization of ATMs is associated with lipid accumulation and the consequent formation of foam cell-like cells in adipose tissue. Our study reveals that early stages of adipose tissue expansion are characterized by M2-polarized ATMs and that progressive lipid accumulation within ATMs heralds the M1 polarization, a macrophage phenotype associated with severe obesity and insulin resistance. Furthermore, rosiglitazone treatment, which promotes redistribution of lipids toward adipocytes and extends the M2 ATM polarization state, prevents the lipid alterations associated with M1 ATM polarization. CONCLUSIONS: Our data indicate that the M1 ATM polarization in obesity might be a macrophage-specific manifestation of a more general lipotoxic pathogenic mechanism. This indicates that strategies to optimize fat deposition and repartitioning toward adipocytes might improve insulin sensitivity by preventing ATM lipotoxicity and M1 polarization.

DNA methylation epigenotypes in breast cancer molecular subtypes.

INTRODUCTION: Identification of gene expression based breast cancer subtypes is considered as a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and there is only a limited understanding of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and deliver specific epigenotypes associated with particular breast cancer subtypes. METHODS: Using a microarray approach we analyzed DNA methylation in regulatory regions of 806 cancer related genes in 28 breast cancer paired samples. We subsequently performed substantial technical and biological validation by Pyrosequencing, investigating the top qualifying 19 CpG regions in independent cohorts encompassing 47 basal-like, 44 ERBB2+ overexpressing, 48 luminal A and 48 luminal B paired breast cancer/adjacent tissues. Using all-subset selection method, we identified the most subtype predictive methylation profiles in multivariable logistic regression analysis. RESULTS: The approach efficiently recognized 15 individual CpG loci differentially methylated in breast cancer tumor subtypes. We further identify novel subtype specific epigenotypes which clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors. CONCLUSIONS: Our results provide evidence that well defined DNA methylation profiles enables breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.

Hypoxia promotes efficient differentiation of human embryonic stem cells to functional endothelium.

Early development of mammalian embryos occurs in an environment of relative hypoxia. Nevertheless, human embryonic stem cells (hESC), which are derived from the inner cell mass of blastocyst, are routinely cultured under the same atmospheric conditions (21% O(2)) as somatic cells. We hypothesized that O(2) levels modulate gene expression and differentiation potential of hESC, and thus, we performed gene profiling of hESC maintained under normoxic or hypoxic (1% or 5% O(2)) conditions. Our analysis revealed that hypoxia downregulates expression of pluripotency markers in hESC but increases significantly the expression of genes associated with angio- and vasculogenesis including vascular endothelial growth factor and angiopoitein-like proteins. Consequently, we were able to efficiently differentiate hESC to functional endothelial cells (EC) by varying O(2) levels; after 24 hours at 5% O(2), more than 50% of cells were CD34+. Transplantation of resulting endothelial-like cells improved both systolic function and fractional shortening in a rodent model of myocardial infarction. Moreover, analysis of the infarcted zone revealed that transplanted EC reduced the area of fibrous scar tissue by 50%. Thus, use of hypoxic conditions to specify the endothelial lineage suggests a novel strategy for cellular therapies aimed at repair of damaged vasculature in pathologies such as cerebral ischemia and myocardial infarction.

FM19G11, a new hypoxia-inducible factor (HIF) modulator, affects stem cell differentiation status.

The biology of the alpha subunits of hypoxia-inducible factors (HIFalpha) has expanded from their role in angiogenesis to their current position in the self-renewal and differentiation of stem cells. The results reported in this article show the discovery of FM19G11, a novel chemical entity that inhibits HIFalpha proteins that repress target genes of the two alpha subunits, in various tumor cell lines as well as in adult and embryonic stem cell models from rodents and humans, respectively. FM19G11 inhibits at nanomolar range the transcriptional and protein expression of Oct4, Sox2, Nanog, and Tgf-alpha undifferentiating factors, in adult rat and human embryonic stem cells, FM19G11 activity occurs in ependymal progenitor stem cells from rats (epSPC), a cell model reported for spinal cord regeneration, which allows the progression of oligodendrocyte cell differentiation in a hypoxic environment, has created interest in its characterization for pharmacological research. Experiments using small interfering RNA showed a significant depletion in Sox2 protein only in the case of HIF2alpha silencing, but not in HIF1alpha-mediated ablation. Moreover, chromatin immunoprecipitation data, together with the significant presence of functional hypoxia response element consensus sequences in the promoter region of Sox2, strongly validated that this factor behaves as a target gene of HIF2alpha in epSPCs. FM19G11 causes a reduction of overall histone acetylation with significant repression of p300, a histone acetyltransferase required as a co-factor for HIF-transcription activation. Arrays carried out in the presence and absence of the inhibitor showed the predominant involvement of epigenetic-associated events mediated by the drug.

Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies.

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/.

Gene set internal coherence in the context of functional profiling.

BACKGROUND: Functional profiling methods have been extensively used in the context of high-throughput experiments and, in particular, in microarray data analysis. Such methods use available biological information to define different types of functional gene modules (e.g. gene ontology -GO-, KEGG pathways, etc.) whose representation in a pre-defined list of genes is further studied. In the most popular type of microarray experimental designs (e.g. up- or down-regulated genes, clusters of co-expressing genes, etc.) or in other genomic experiments (e.g. Chip-on-chip, epigenomics, etc.) these lists are composed by genes with a high degree of co-expression. Therefore, an implicit assumption in the application of functional profiling methods within this context is that the genes corresponding to the modules tested are effectively defining sets of co-expressing genes. Nevertheless not all the functional modules are biologically coherent entities in terms of co-expression, which will eventually hinder its detection with conventional methods of functional enrichment. RESULTS: Using a large collection of microarray data we have carried out a detailed survey of internal correlation in GO terms and KEGG pathways, providing a coherence index to be used for measuring functional module co-regulation. An unexpected low level of internal correlation was found among the modules studied. Only around 30% of the modules defined by GO terms and 57% of the modules defined by KEGG pathways display an internal correlation higher than the expected by chance.This information on the internal correlation of the genes within the functional modules can be used in the context of a logistic regression model in a simple way to improve their detection in gene expression experiments. CONCLUSION: For the first time, an exhaustive study on the internal co-expression of the most popular functional categories has been carried out. Interestingly, the real level of coexpression within many of them is lower than expected (or even inexistent), which will preclude its detection by means of most conventional functional profiling methods. If the gene-to-function correlation information is used in functional profiling methods, the results obtained improve the ones obtained by conventional enrichment methods.

Cryptochrome-1 expression: a new prognostic marker in B-cell chronic lymphocytic leukemia.

Chronic lymphocytic leukemia is an adult-onset leukemia with a heterogeneous clinical behavior. When chronic lymphocytic leukemia cases were divided on the basis of IgV(H) mutational status, widely differing clinical courses were revealed. Since IgV(H) sequencing is difficult to perform in a routine diagnostic laboratory, finding a surrogate for IgV(H) mutational status seems an important priority. In the present study, we proposed the use of Cryptochrome-1 as a new prognostic marker in early-stage chronic lymphocytic leukemia. Seventy patients (Binet stage A, without treatment) were included in the study. We correlated Cryptochrome-1 mRNA with well established prognostic markers such as IgV(H) mutations, ZAP70, LPL or CD38 expression and chromosomal abnormalities. High Cryptochrome-1 expression correlated with IgV(H) unmutated samples. In addition, Cryptochrome-1 was a valuable predictor of disease progression in early-stage chronic lymphocytic leukemia, therefore it can be introduced in clinical practice with the advantage of a simplified method of quantification.

Analysis of chronic lymphotic leukemia transcriptomic profile: differences between molecular subgroups.

B cell chronic lymphocytic leukemia (CLL) is a lymphoproliferative disorder with a variable clinical course. Patients with unmutated IgV(H) gene show a shorter progression-free and overall survival than patients with immunoglobulin heavy chain variable regions (IgV(H)) gene mutated. In addition, BCL6 mutations identify a subgroup of patients with high risk of progression. Gene expression was analysed in 36 early-stage patients using high-density microarrays. Around 150 genes differentially expressed were found according to IgV(H) mutations, whereas no difference was found according to BCL6 mutations. Functional profiling methods allowed us to distinguish KEGG and gene ontology terms showing coordinated gene expression changes across subgroups of CLL. We validated a set of differentially expressed genes according to IgV(H) status, scoring them as putative prognostic markers in CLL. Among them, CRY1, LPL, CD82 and DUSP22 are the ones with at least equal or superior performance to ZAP70 which is actually the most used surrogate marker of IgV(H) status.

Direct functional assessment of the composite phenotype through multivariate projection strategies.

We present a novel approach for the analysis of transcriptomics data that integrates functional annotation of gene sets with expression values in a multivariate fashion, and directly assesses the relation of functional features to a multivariate space of response phenotypical variables. Multivariate projection methods are used to obtain new correlated variables for a set of genes that share a given function. These new functional variables are then related to the response variables of interest. The analysis of the principal directions of the multivariate regression allows for the identification of gene function features correlated with the phenotype. Two different transcriptomics studies are used to illustrate the statistical and interpretative aspects of the methodology. We demonstrate the superiority of the proposed method over equivalent approaches.

Evidence for systems-level molecular mechanisms of tumorigenesis.

BACKGROUND: Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth. RESULTS: Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs") defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree) and global (betweenness and closeness) measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis. CONCLUSION: Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.

Functional profiling and gene expression analysis of chromosomal copy number alterations.

Contrarily to the traditional view in which only one or a few key genes were supposed to be the causative factors of diseases, we discuss the importance of considering groups of functionally related genes in the study of pathologies characterised by chromosomal copy number alterations. Recent observations have reported the existence of regions in higher eukaryotic chromosomes (including humans) containing genes of related function that show a high degree of coregulation. Copy number alterations will consequently affect to clusters of functionally related genes, which will be the final causative agents of the diseased phenotype, in many cases. Therefore, we propose that the functional profiling of the regions affected by copy number alterations must be an important aspect to take into account in the understanding of this type of pathologies. To illustrate this, we present an integrated study of DNA copy number variations, gene expression along with the functional profiling of chromosomal regions in a case of multiple myeloma.

Self-reported smoking cessation interventions were not associated with quitting in older women.

OBJECTIVE: To determine the extent to which smoking cessation interventions are used in the community and their relative success in older women. STUDY DESIGN AND SETTING: Prospective cohort study located in 23 general practices in England, Scotland. and Wales and including 3,622 women aged 60 to 79 years at recruitment from the British Women's Heart and Health Study. RESULTS: Of the 370 smokers at baseline, 77 (21%) had stopped smoking at 3 years, reducing the prevalence of smoking from 10.2% to 8.8%. Women who were light smokers (<10 per day) at baseline were more likely to have quit than heavier smokers. The most common interventions reported by women who smoked at baseline were advice from a general practitioner (GP), family or friend's advice, and use of nicotine replacement, but 42% of the women reported having no intervention to help them to stop smoking. None of the individual interventions were associated with increased odds of quitting smoking over the follow-up period. Women reported finding a GP's advice, referral to a clinic, and nicotine replacement more useful than complementary treatments (acupuncture and hypnotherapy) or advice from family and friends. CONCLUSION: Smoking cessation rates in this study were in line with national targets and surveys. Self-reports of ever receiving interventions were not associated with quitting smoking among these older women. Different and innovative approaches to smoking cessation may need to be developed, and evaluated in future randomized clinical trials, for individuals who have smoked for a long period of time and for whom other smoking cessation interventions have not proved successful.

Selective pressures at a codon-level predict deleterious mutations in human disease genes.

Deleterious mutations affecting biological function of proteins are constantly being rejected by purifying selection from the gene pool. The non-synonymous/synonymous substitution rate ratio (omega) is a measure of selective pressure on amino acid replacement mutations for protein-coding genes. Different methods have been developed in order to predict non-synonymous changes affecting gene function. However, none has considered the estimation of selective constraints acting on protein residues. Here, we have used codon-based maximum likelihood models in order to estimate the selective pressures on the individual amino acid residues of a well-known model protein: p53. We demonstrate that the number of residues under strong purifying selection in p53 is much higher than those that are strictly conserved during the evolution of the species. In agreement with theoretical expectations, residues that have been noted to be of structural relevance, or in direct association with DNA, were among those showing the highest signals of purifying selection. Conversely, those changing according to a neutral, or nearly neutral mode of evolution, were observed to be irrelevant for protein function. Finally, using more than 40 human disease genes, we demonstrate that residues evolving under strong selective pressures (omega<0.1) are significantly associated (p<0.01) with human disease. We hypothesize that non-synonymous change on amino acids showing omega<0.1 will most likely affect protein function. The application of this evolutionary prediction at a genomic scale will provide an a priori hypothesis of the phenotypic effect of non-synonymous coding single nucleotide polymorphisms (SNPs) in the human genome.