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Formalin fixed paraffin-embedded (FFPE) tumor specimens are the conventionally archived material in clinical practice, representing an invaluable tissue source for biomarkers development, validation and routine implementation. For many prospective clinical trials, this material has been collected allowing for a prospective-retrospective study design which represents a successful strategy to define clinical utility for candidate markers. Gene expression data can be obtained even from FFPE specimens with the broadly used Affymetrix HG-U133 Plus 2.0 microarray platform. Nevertheless, important major discrepancies remain in expression data obtained from FFPE compared to fresh-frozen samples, prompting the need for appropriate data processing which could help to obtain more consistent results in downstream analyses. In a publicly available dataset of matched frozen and FFPE expression data, the performances of different normalization methods and specifically designed Chip Description Files (CDFs) were compared. The use of an alternative CDFs together with fRMA normalization significantly improved frozen-FFPE sample correlations, frozen-FFPE probeset correlations and agreement of differential analysis between different tumor subtypes. The relevance of our optimized data processing was assessed and validated using two independent datasets. In this study we demonstrated that an appropriate data processing can significantly improve the reliability of gene expression data derived from FFPE tissues using the standard Affymetrix platform. Tools for the implementation of our data processing algorithm are made publicly available at http://www.biocut.unito.it/cdf-ffpe/.

In pluripotent stem cells, there is increasing evidence for crosstalk between post-transcriptional and transcriptional networks, offering multifold steps at which pluripotency can be controlled. In addition to well-studied transcription factors, chromatin modifiers and miRNAs, RNA-binding proteins are emerging as fundamental players in pluripotency regulation. Here, we report a new role for the RNA-binding protein ESRP1 in the control of pluripotency. Knockdown of Esrp1 in mouse embryonic stem cells induces, other than the well-documented epithelial to mesenchymal-like state, also an increase in expression of the core transcription factors Oct4, Nanog and Sox2, thereby enhancing self-renewal of these cells. Esrp1-depleted embryonic stem cells displayed impaired early differentiation in vitro and formed larger teratomas in vivo when compared to control embryonic stem cells. We also show that ESRP1 binds to Oct4 and Sox2 mRNAs and decreases their polysomal loading. ESRP1 thus acts as a physiological regulator of the finely-tuned balance between self-renewal and commitment to a restricted developmental fate. Importantly, both mouse and human epithelial stem cells highly express ESRP1, pinpointing the importance of this RNA-binding protein in stem cell biology.

Background: High-throughput gene expression data can predict gene function through the "guilt by association" principle: coexpressed genes are likely to be functionally associated., Methodology/principal Findings: We analyzed publicly available expression data on normal human tissues. The analysis is based on the integration of data obtained with two experimental platforms (microarrays and SAGE) and of various measures of dissimilarity between expression profiles. The building blocks of the procedure are the Ranked Coexpression Groups (RCG), small sets of tightly coexpressed genes which are analyzed in terms of functional annotation. Functionally characterized RCGs are selected by means of the majority rule and used to predict new functional annotations. Functionally characterized RCGs are enriched in groups of genes associated to similar phenotypes. We exploit this fact to find new candidate disease genes for many OMIM phenotypes of unknown molecular origin., Conclusions/significance: We predict new functional annotations for many human genes, showing that the integration of different data sets and coexpression measures significantly improves the scope of the results. Combining gene expression data, functional annotation and known phenotype-gene associations we provide candidate genes for several genetic diseases of unknown molecular basis.

In the last decades, genome-wide association studies (GWAS) have uncovered tens of thousands of associations between common genetic variants and complex diseases. However, these statistical associations can rarely be interpreted functionally and mechanistically. As the majority of the disease-associated variants are located far from coding sequences, even the relevant gene is often unclear. A way to gain insight into the relevant mechanisms is to study the genetic determinants of intermediate molecular phenotypes, such as gene expression and transcript structure. We propose a computational strategy to discover genetic variants affecting the relative expression of alternative 3′ untranslated region (UTR) isoforms, generated through alternative polyadenylation, a widespread posttranscriptional regulatory mechanism known to have relevant functional consequences. When applied to a large dataset in which whole genome and RNA sequencing data are available for 373 European individuals, 2,530 genes with alternative polyadenylation quantitative trait loci (apaQTL) were identified. We analyze and discuss possible mechanisms of action of these variants, and we show that they are significantly enriched in GWAS hits, in particular those concerning immune-related and neurological disorders. Our results point to an important role for genetically determined alternative polyadenylation in affecting predisposition to complex diseases, and suggest new ways to extract functional information from GWAS data. [ABSTRACT FROM AUTHOR]

Background: In recent years long non coding RNAs (lncRNAs) have been the subject of increasing interest. Thanks to many recent functional studies, the existence of a large class of lncRNAs with potential regulatory functions is now widely accepted. Although an increasing number of lncRNAs is being characterized and shown to be involved in many biological processes, the functions of the vast majority lncRNA genes is still unknown. Therefore computational methods able to take advantage of the increasing amount of publicly available data to predict lncRNA functions could be very useful. Results: Since coding genes are much better annotated than lncRNAs, we attempted to project known functional information regarding proteins onto non coding genes using the guilt by association principle: if a gene shows an expression profile that correlates with those of a set of coding genes involved in a given function, that gene is probably involved in the same function. We computed gene coexpression for 30 human tissues and 9 vertebrates and mined the resulting networks with a methodology inspired by the rank product algorithm used to identify differentially expressed genes. Using different types of reference data we can predict putative new annotations for thousands of lncRNAs and proteins, ranging from cellular localization to relevance for disease and cancer. Conclusions: New function of coding genes and lncRNA can be profitably predicted using tissue specific coexpression, as well as expression of orthologous genes in different species. The data are available for download and through a user-friendly web interface at www.funcpred.com. [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]

Transcription factors regulate gene expression by binding regulatory DNA. Understanding the rules governing such binding is an essential step in describing the network of regulatory interactions, and its pathological alterations. We show that describing regulatory regions in terms of their profile of total binding affinities for transcription factors leads to increased predictive power compared to methods based on the identification of discrete binding sites. This applies both to the prediction of transcription factor binding as revealed by ChIP-seq experiments and to the prediction of gene expression through RNA-seq. Further significant improvements in predictive power are obtained when regulatory regions are defined based on chromatin states inferred from histone modification data. [ABSTRACT FROM AUTHOR]

MicroRNAs are single-stranded non-coding RNAs that simultaneously down-modulate the expression of multiple genes post-transcriptionally by binding to the 3′UTRs of target mRNAs. Here we used computational methods to predict microRNAs relevant in breast cancer progression. Specifically, we applied different microRNA target prediction algorithms to various groups of differentially expressed protein-coding genes obtained from four breast cancer datasets. Six potential candidates were identified, among them miR-223, previously described to be highly expressed in the tumor microenvironment and known to be actively transferred into breast cancer cells. To investigate the function of miR-223 in tumorigenesis and to define its molecular mechanism, we overexpressed miR-223 in breast cancer cells in a transient or stable manner. Alternatively we overexpressed miR-223 in mouse embryonic fibroblasts or HEK293 cells and used their conditioned medium to treat tumor cells. With both approaches, we obtained elevated levels of miR-223 in tumor cells and observed decreased migration, increased cell death in anoikis conditions and augmented sensitivity to chemotherapy but no effect on adhesion and proliferation. The analysis of miR-223 predicted targets revealed enrichment in cell death and survival-related genes and in pathways frequently altered in breast cancer. Among these genes, we showed that protein levels for STAT5A, ITGA3 and NRAS were modulated by miR-223. In addition, we proved that STAT5A is a direct miR-223 target and highlighted a possible correlation between miR-223 and STAT5A in migration and chemotherapy response. Our investigation revealed that a computational analysis of cancer gene expression datasets can be a relevant tool to identify microRNAs involved in cancer progression and that miR-223 has a prominent role in breast malignancy that could potentially be exploited therapeutically. [ABSTRACT FROM AUTHOR]

Background: The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of 'ad hoc' gene expression data-sets. Results: By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. Conclusions: Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation. [ABSTRACT FROM AUTHOR]

It has recently been proposed that defective differentiation of mammary luminal progenitors predisposes to basal-like breast cancer. However, the molecular and cellular mechanisms involved are still unclear. Here, we describe that the adaptor protein p130Cas is a crucial regulator of mouse mammary epithelial cell (MMEC) differentiation. Using a transgenic mouse model, we show that forced p130Cas overexpression in the luminal progenitor cell compartment results in the expansion of luminal cells, which aberrantly display basal cell features and reduced differentiation in response to lactogenic stimuli. Interestingly, MMECs overexpressing p130Cas exhibit hyperactivation of the tyrosine kinase receptor c-Kit. In addition, we demonstrate that the constitutive c-Kit activation alone mimics p130Cas overexpression, whereas c-Kit downregulation is sufficient to re-establish proper differentiation of p130Cas overexpressing cells. Overall, our data indicate that high levels of p130Cas, via abnormal c-Kit activation, promote mammary luminal cell plasticity, thus providing the conditions for the development of basal-like breast cancer. Consistently, p130Cas is overexpressed in human triple-negative breast cancer, further suggesting that p130Cas upregulation may be a priming event for the onset of basal-like breast cancer. S TEM C ells 2013;31:1422-1433 [ABSTRACT FROM AUTHOR]

ABSTRACT Polymorphisms in regulatory DNA regions are believed to play an important role in determining phenotype, including disease, and in providing raw material for evolution. We devised a new pipeline for the systematic identification of functional variation in human regulatory sequences. The algorithm is based on the identification of SNPs leading to significant changes in both the affinity of a regulatory region for transcription factors ( TFs) and the expression in vivo of the regulated gene. We tested the algorithm by identifying SNPs leading to altered regulation by STAT3 in human promoters and introns, and experimentally validated the top-scoring ones, showing that most of the SNPs identified by the algorithm indeed correspond to differential binding of STAT3 and differential induction of the target gene upon stimulation with IL6. Using the same computational approach, we compiled a database of thousands of predicted functional regulatory SNPs for hundreds of human TFs, which we provide as online Supporting Information. We discuss possible applications to the interpretation of noncoding SNPs associated with human diseases. The method we propose and the database of predicted functional cis-regulatory polymorphisms will be useful in future studies of regulatory variation and in particular to interpret the results of past and future genome-wide association studies. [ABSTRACT FROM AUTHOR]

A major part of the post-transcriptional regulation of gene expression is affected by trans-acting elements, such as microRNAs, binding the 3' untraslated region (UTR) of their target mRNAs. Proliferating cells partly escape this type of negative regulation by expressing shorter 3' UTRs, depleted of microRNA binding sites, compared to non-proliferating cells. Using large-scale gene expression datasets, we show that a similar phenomenon takes place in breast and lung cancer: tumors expressing shorter 3' UTRs tend to be more aggressive and to result in shorter patient survival. Moreover, we show that a gene expression signature based only on the expression ratio of alternative 3' UTRs is a strong predictor of survival in both tumors. Genes undergoing 3'UTR shortening in aggressive tumors of the two tissues significantly overlap, and several of them are known to be involved in tumor progression. However the pattern of 3' UTR shortening in aggressive tumors in vivo is clearly distinct from analogous patterns involved in proliferation and transformation. [ABSTRACT FROM AUTHOR]

Gene coexpression relationships that are phylogenetically conserved between human and mouse have been shown to provide important clues about gene function that can be efficiently used to identify promising candidate genes for human hereditary disorders. In the past, such approaches have considered mostly generic gene expression profiles that cover multiple tissues and organs. The individual genes of multicellular organisms, however, can participate in different transcriptional programs, operating at scales as different as single-cell types, tissues, organs, body regions or the entire organism. Therefore, systematic analysis of tissue-specific coexpression could be, in principle, a very powerful strategy to dissect those functional relationships among genes that emerge only in particular tissues or organs. In this report, we show that, in fact, conserved coexpression as determined from tissue-specific and condition-specific data sets can predict many functional relationships that are not detected by analyzing heterogeneous microarray data sets. More importantly, we find that, when combined with disease networks, the simultaneous use of both generic (multi-tissue) and tissue-specific conserved coexpression allows a more efficient prediction of human disease genes than the use of generic conserved coexpression alone. Using this strategy, we were able to identify high-probability candidates for 238 orphan disease loci. We provide proof of concept that this combined use of generic and tissue-specific conserved coexpression can be very useful to prioritize the mutational candidates obtained from deep-sequencing projects, even in the case of genetic disorders as heterogeneous as XLMR. [ABSTRACT FROM AUTHOR]

Ewing's sarcoma family tumors (ESFT) are the second most common bone malignancy in children and young adults, characterized by unique chromosomal translocations that in 85% of cases lead to expression of the EWS-FLI-1 fusion protein. EWS-FLI-1 functions as an aberrant transcription factor that can both induce and suppress members of its target gene repertoire. We have recently demonstrated that EWS-FLI-1 can alter microRNA (miRNA) expression and that miRNA145 is a direct EWS-FLI-1 target whose suppression is implicated in ESFT development. Here, we use miRNA arrays to compare the global miRNA expression profile of human mesenchymal stem cells (MSC) and ESFT cell lines, and show that ESFT display a distinct miRNA signature that includes induction of the oncogenic miRNA 17-92 cluster and repression of the tumor suppressor let-7 family. We demonstrate that direct repression of let-7a by EWS-FLI-1 participates in the tumorigenic potential of ESFT cells in vivo. The mechanism whereby let-7a expression regulates ESFT growth is shown to be mediated by its target gene HMGA2, as let-7a overexpression and HMGA2 repression both block ESFT cell tumorigenicity. Consistent with these observations, systemic delivery of synthetic let-7a into ESFT-bearing mice restored its expression in tumor cells, decreased HMGA2 expression levels and resulted in ESFT growth inhibition in vivo. Our observations provide evidence that deregulation of let-7a target gene expression participates in ESFT development and identify let-7a as promising new therapeutic target for one of the most aggressive pediatric malignancies. [ABSTRACT FROM AUTHOR]

Malignant melanoma is fatal in its metastatic stage. It is therefore essential to unravel the molecular mechanisms that govern disease progression to metastasis. MicroRNAs (miRs) are endogenous non-coding RNAs involved in tumourigenesis. Using a melanoma progression model, we identified a novel pathway controlled by miR-214 that coordinates metastatic capability. Pathway components include TFAP2C, homologue of a well-established melanoma tumour suppressor, the adhesion receptor ITGA3 and multiple surface molecules. Modulation of miR-214 influences in vitro tumour cell movement and survival to anoikis as well as extravasation from blood vessels and lung metastasis formation in vivo. Considering that miR-214 is known to be highly expressed in human melanomas, our data suggest a critical role for this miRNA in disease progression and the establishment of distant metastases. [ABSTRACT FROM AUTHOR]

Introduction: The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. Methods: We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). Results: The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. Conclusion: This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies. [ABSTRACT FROM AUTHOR]

Background: The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results: We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions: Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data. [ABSTRACT FROM AUTHOR]

The genome of the fruitfly Drosophila melanogaster contains 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 605 ribosome biogenesis. We demonstrate that GTPBP4 knockdown induces p53 accumulation and activation in the absence of nucleolardisruption. In breasttumors with wild-type p53. increased expression of GTPBP4 correlates with reduced patient survival. emphasizing a potential relevance of this regulatory axis in cancer. [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]

Background: The EWS-FLI-1 fusion protein is associated with 85-90% of Ewing's sarcoma family tumors (ESFT), the remaining 10-15% of cases expressing chimeric genes encoding EWS or FUS fused to one of several ets transcription factor family members, including ERG-1, FEV, ETV1 and ETV6. ESFT are dependent on insulin-like growth factor-1 (IGF-1) for growth and survival and recent evidence suggests that mesenchymal progenitor/stem cells constitute a candidate ESFT origin. Methodology/Principal Findings: To address the functional relatedness between ESFT-associated fusion proteins, we compared mouse progenitor cell (MPC) permissiveness for EWS-FLI-1, EWS-ERG and FUS-ERG expression and assessed the corresponding expression profile changes. Whereas all MPC isolates tested could stably express EWS-FLI-1, only some sustained stable EWS-ERG expression and none could express FUS-ERG for more than 3-5 days. Only 14% and 4% of the total number of genes that were respectively induced and repressed in MPCs by the three fusion proteins were shared. However, all three fusion proteins, but neither FLI-1 nor ERG-1 alone, activated the IGF1 promoter and induced IGF1 expression. Conclusion/Significance: Whereas expression of different ESFT-associated fusion proteins may require distinct cellular microenvironments and induce transcriptome changes of limited similarity, IGF1 induction may provide one common mechanism for their implication in ESFT pathogenesis. [ABSTRACT FROM AUTHOR]

Background: Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings: We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion: Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. [ABSTRACT FROM AUTHOR]

Background: Gene regulation in eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding region. We present a novel computational method to identify regulatory elements in the upstream region of eukaryotic genes. The genes are grouped in sets sharing an overrepresented short motif in their upstream sequence. For each set, the average expression level from a microarray experiment is determined: If this level is significantly higher or lower than the average taken over the whole genome, then the overerpresented motif shared by the genes in the set is likely to play a role in their regulation. Results: The method was tested by applying it to the genome of Saccharomyces cerevisiae, using the publicly available results of a DNA microarray experiment, in which expression levels for virtually all the genes were measured during the diauxic shift from fermentation to respiration. Several known motifs were correctly identified, and a new candidate regulatory sequence was determined. Conclusions: We have described and successfully tested a simple computational method to identify upstream motifs relevant to gene regulation in eukaryotes by studying the statistical correlation between overepresented upstream motifs and gene expression levels. [ABSTRACT FROM AUTHOR]

Biological systems respond to perturbations through the rewiring of molecular interactions, organised in gene regulatory networks (GRNs). Among these, the increasingly high availability of transcriptomic data makes gene co-expression networks the most exploited ones. Differential co-expression networks are useful tools to identify changes in response to an external perturbation, such as mutations predisposing to cancer development, and leading to changes in the activity of gene expression regulators or signalling. They can help explain the robustness of cancer cells to perturbations and identify promising candidates for targeted therapy, moreover providing higher specificity with respect to standard co-expression methods. Here, we comprehensively review the literature about the methods developed to assess differential co-expression and their applications to cancer biology. Via the comparison of normal and diseased conditions and of different tumour stages, studies based on these methods led to the definition of pathways involved in gene network reorganisation upon oncogenes' mutations and tumour progression, often converging on immune system signalling. A relevant implementation still lagging behind is the integration of different data types, which would greatly improve network interpretability. Most importantly, performance and predictivity evaluation of the large variety of mathematical models proposed would urgently require experimental validations and systematic comparisons. We believe that future work on differential gene co-expression networks, complemented with additional omics data and experimentally tested, will considerably improve our insights into the biology of tumours. [ABSTRACT FROM AUTHOR]

Breast cancer is a heterogeneous disease whose clinical management is very challenging. Although specific molecular features characterize breast cancer subtypes with different prognosis, the identification of specific markers predicting disease outcome within the single subtypes still lags behind. Both the non-canonical Wingless-type MMTV Integration site (WNT) and the Signal Transducer and Activator of Transcription (STAT)3 pathways are often constitutively activated in breast tumors, and both can induce the small GTPase Ras Homolog Family Member U RhoU. Here we show that RhoU transcription can be triggered by both canonical and non-canonical WNT ligands via the activation of c-JUN N-terminal kinase (JNK) and the recruitment of the Specificity Protein 1 (SP1) transcription factor to the RhoU promoter, identifying for the first time SP1 as a JNK-dependent mediator of WNT signaling. RhoU down-regulation by silencing or treatment with JNK, SP1 or STAT3 inhibitors leads to impaired migration and invasion in basal-like MDA-MB-231 and BT-549 cells, suggesting that STAT3 and SP1 can cooperate to induce high RhoU expression and enhance breast cancer cells migration. Moreover, in vivo concomitant binding of STAT3 and SP1 defines a subclass of genes belonging to the non-canonical WNT and the Interleukin (IL)-6/STAT3 pathways and contributing to breast cancer aggressiveness, suggesting the relevance of developing novel targeted therapies combining inhibitors of the STAT3 and WNT pathways or of their downstream mediators. [ABSTRACT FROM AUTHOR]

Motivation: The identification of genes involved in specific phenotypes, such as human hereditary diseases, often requires the time-consuming and expensive examination of a large number of positional candidates selected by genome-wide techniques such as linkage analysis and association studies. Even considering the positive impact of next-generation sequencing technologies, the prioritization of these positional candidates may be an important step for disease-gene identification. Results: Here, we report a large-scale analysis of spatial, i.e. 3D, gene-expression data from an entire organ (the mouse brain) for the purpose of evaluating and ranking positional candidate genes, showing that the spatial gene-expression patterns can be successfully exploited for the prediction of gene-phenotype associations not only for mouse phenotypes, but also for human central nervous system-related Mendelian disorders. We apply our method to the case of X-linked mental retardation, compare the predictions to the results obtained from a previous large-scale resequencing study of chromosome X and discuss some promising novel candidates. [ABSTRACT FROM AUTHOR]

Targeting of the most aggressive tumor cell subpopulations is key for effective management of most solid malignancies. However, the metastable nature of tumor heterogeneity, which allows cells to transition between strong and weak tumorigenic phenotypes, and the lack of reliable markers of tumor-promoting properties hamper identification of the most relevant cells. To overcome these obstacles, we designed a functional microRNA (miR)-based live-cell reporter assay to identify highly tumorigenic cells in xenotransplants of primary Ewing sarcoma (EwS) 3D cultures. Leveraging the inverse relationship between cell pluripotency and miR-145 expression, we successfully separated highly tumorigenic, metastasis-prone (miR-145low) cells from poorly tumorigenic, nonmetastatic (miR-145high) counterparts. Gene expression and functional studies of the two cell populations identified the EPHB2 receptor as a prognostic biomarker in patients with EwS and a major promoter of metastasis. Our study provides a simple and powerful means to identify and isolate tumor cells that display aggressive behavior. [ABSTRACT FROM AUTHOR]

Summary: We have recently demonstrated that human pediatric mesenchymal stem cells can be reprogrammed toward a Ewing sarcoma family tumor (ESFT) cancer stem cell (CSC) phenotype by mechanisms that implicate microRNAs (miRNAs). Here, we show that the miRNA profile of ESFT CSCs is shared by embryonic stem cells and CSCs from divergent tumor types. We also provide evidence that the miRNA profile of ESFT CSCs is the result of reversible disruption of TARBP2-dependent miRNA maturation. Restoration of TARBP2 activity and systemic delivery of synthetic forms of either of two of its targets, miRNA-143 or miRNA-145, inhibited ESFT CSC clonogenicity and tumor growth in vivo. Our observations suggest that CSC self-renewal and tumor maintenance may depend on deregulation of TARBP2-dependent miRNA expression. [Copyright &y& Elsevier]

Summary: Here, we demonstrate that protein-coding RNA transcripts can crosstalk by competing for common microRNAs, with microRNA response elements as the foundation of this interaction. We have termed such RNA transcripts as competing endogenous RNAs (ceRNAs). We tested this hypothesis in the context of PTEN, a key tumor suppressor whose abundance determines critical outcomes in tumorigenesis. By a combined computational and experimental approach, we identified and validated endogenous protein-coding transcripts that regulate PTEN, antagonize PI3K/AKT signaling, and possess growth- and tumor-suppressive properties. Notably, we also show that these genes display concordant expression patterns with PTEN and copy number loss in cancers. Our study presents a road map for the prediction and validation of ceRNA activity and networks and thus imparts a trans-regulatory function to protein-coding mRNAs. [ABSTRACT FROM AUTHOR]

Abstract: ErbB2 over-expression is detected in approximately 25% of invasive breast cancers and is strongly associated with poor patient survival. We have previously demonstrated that p130Cas adaptor is a crucial mediator of ErbB2 transformation. Here, we analysed the molecular mechanisms through which p130Cas controls ErbB2-dependent invasion in three-dimensional cultures of mammary epithelial cells. Concomitant p130Cas over-expression and ErbB2 activation enhance PI3K/Akt and Erk1/2 MAPK signalling pathways and promote invasion of mammary acini. By using pharmacological inhibitors, we demonstrate that both signalling cascades are required for the invasive behaviour of p130Cas over-expressing and ErbB2 activated acini. Erk1/2 MAPK and PI3K/Akt signalling triggers invasion through distinct downstream effectors involving mTOR/p70S6K and Rac1 activation, respectively. Moreover, in silico analyses indicate that p130Cas expression in ErbB2 positive human breast cancers significantly correlates with higher risk to develop distant metastasis, thus underlying the value of the p130Cas/ErbB2 synergism in regulating breast cancer invasion. In conclusion, high levels of p130Cas favour progression of ErbB2-transformed cells towards an invasive phenotype. [Copyright &y& Elsevier]

Cancer stem cells (CSCs) display plasticity and self-renewal properties reminiscent of normal tissue stem cells, but the events responsible for their emergence remain obscure. We recently identified CSCs in Ewing sarcoma family tumors (ESFTs) and showed that they retain mesenchymal stem cell (MSC) plasticity. In the present study, we addressed the mechanisms that underlie ESFT CSC development. We show that the EWS-FLI-1 fusion gene, associated with 85%·90% of ESFTs and believed to initiate their pathogenesis, induces expression of the embryonic stem cell (ESC) genes OCT4, SOX2, and NANOG in human pediatric MSCs (hpMSCs) but not in their adult counterparts. Moreover, under appropriate culture conditions, hpMSCs expressing EWS-FLI-1 generate a cell subpopulation displaying ESFT CSC features in vitro. We further demonstrate that induction of the ESFT CSC phenotype is the result of the combined effect of EWS-FLI-1 on its target gene expression and repression of microRNA-145 (miRNA145) promoter activity. Finally, we provide evidence that EWS-FLI-1 and miRNA-145 function in a mutually repressive feedback loop and identify their common target gene, SOX2, in addition to miRNA145 itself, as key players in ESFT cell differentiation and tumorigenicity. Our observations provide insight for the first time into the mechanisms whereby a single oncogene can reprogram primary cells to display a CSC phenotype. [ABSTRACT FROM AUTHOR]