miRNA-mRNA integrated analysis reveals roles for miRNAs in primary breast tumors

Screening for possible miRNA-mRNA associations in a colon cancer cell line

MicroRNAs (miRNAs) are small non-coding RNAs mediating the regulation of gene expression in various biological contexts, including carcinogenesis. Here, we screened putative associations between 34, 45, and 103 miRNAs and 164, 391, and 81 mRNAs via Argonaute1 (Ago1) or Ago2 immunoprecipitation (IP) experiments in a colon cancer cell line. We used a combination of RIP Seq analysis. RNAs that were co-immunoprecipitated with Ago1 or Ago2 were used for massively parallel small RNA and mRNA sequencing. The detected miRNAs and mRNAs were further associated with one another based on in silico target predictions. Analysis of the putative associations indicated that, although Ago1 and Ago2 shared a similar repertory of miRNAs, the mRNAs possibly regulated by those miRNAs seemed different. The mRNAs detected with Ago1 IP were indicated to be frequently associated with genes having constitutive cellular functions, regulated by a smaller number of miRNAs, and appeared to receive more stringent translational regulation. In contrast, putative miRNA-mRNA associations detected with Ago2 IP appeared to be related to signal transduction genes, which had a larger number of possible miRNA binding sites. We then conducted a similar analysis using the colon cancer cells cultured under hypoxia and identified potential hypoxia-induced miRNA-mRNA associations, which included several well-characterized cancer-related genes as novel putative miRNA targets.

MicroRNA-antagonism regulates breast cancer stemness and metastasis via TET-family-dependent chromatin remodeling

Tumor cells metastasize to distant organs through genetic and epigenetic alterations, including changes in microRNA (miR) expression. Here we find miR-22 triggers epithelial-mesenchymal transition (EMT), enhances invasiveness and promotes metastasis in mouse xenografts. In a conditional mammary gland-specific transgenic (TG) mouse model, we show that miR-22 enhances mammary gland side-branching, expands the stem cell compartment, and promotes tumor development. Critically, miR-22 promotes aggressive metastatic disease in MMTV-miR-22 TG mice, as well as compound MMTV-neu or -PyVT-miR-22 TG mice. We demonstrate that miR-22 exerts its metastatic potential by silencing antimetastatic miR-200 through direct targeting of the TET (Ten eleven translocation) family of methylcytosine dioxygenases, thereby inhibiting demethylation of the mir-200 promoter. Finally, we show that miR-22 overexpression correlates with poor clinical outcomes and silencing of the TET-miR-200 axis in patients. Taken together, our findings implicate miR-22 as a crucial epigenetic modifier and promoter of EMT and breast cancer stemness toward metastasis.

HMGA2/TET1/HOXA9 signaling pathway regulates breast cancer growth and metastasis

The ten-eleven translocation (TET) family of methylcytosine dioxygenases initiates demethylation of DNA and is associated with tumorigenesis in many cancers; however, the mechanism is mostly unknown. Here we identify upstream activators and downstream effectors of TET1 in breast cancer using human breast cancer cells and a genetically engineered mouse model. We show that depleting the architectural transcription factor high mobility group AT-hook 2 (HMGA2) induces TET1. TET1 binds and demethylates its own promoter and the promoter of homeobox A (HOXA) genes, enhancing its own expression and stimulating expression of HOXA genes including HOXA7 and HOXA9. Both TET1 and HOXA9 suppress breast tumor growth and metastasis in mouse xenografts. The genes comprising the HMGA2-TET1-HOXA9 pathway are coordinately regulated in breast cancer and together encompass a prognostic signature for patient survival. These results implicate the HMGA2-TET1-HOX signaling pathway in the epigenetic regulation of human breast cancer and highlight the importance of targeting methylation in specific subpopulations as a potential therapeutic strategy.

Growth of triple-negative breast cancer cells relies upon coordinate autocrine expression of the proinflammatory cytokines IL-6 and IL-8

Triple-negative breast cancers (TNBC) are aggressive with no effective targeted therapies. A combined database analysis identified 32 inflammation-related genes differentially expressed in TNBCs and 10 proved critical for anchorage-independent growth. In TNBC cells, an LPA-LPAR2-EZH2 NF-κB signaling cascade was essential for expression of interleukin (IL)-6, IL-8, and CXCL1. Concurrent inhibition of IL-6 and IL-8 expression dramatically inhibited colony formation and cell survival in vitro and stanched tumor engraftment and growth in vivo. A Cox multivariable analysis of patient specimens revealed that IL-6 and IL-8 expression predicted patient survival times. Together these findings offer a rationale for dual inhibition of IL-6/IL-8 signaling as a therapeutic strategy to improve outcomes for patients with TNBCs.

The shaping and functional consequences of the microRNA landscape in breast cancer

MicroRNAs (miRNAs) show differential expression across breast cancer subtypes, and have both oncogenic and tumour-suppressive roles. Here we report the miRNA expression profiles of 1,302 breast tumours with matching detailed clinical annotation, long-term follow-up and genomic and messenger RNA expression data. This provides a comprehensive overview of the quantity, distribution and variation of the miRNA population and provides information on the extent to which genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture, suggesting an important role for post-transcriptional regulation. The key clinical parameters and cellular pathways related to the miRNA landscape are characterized, revealing context-dependent interactions, for example with regards to cell adhesion and Wnt signalling. Notably, only prognostic miRNA signatures derived from breast tumours devoid of somatic copy-number aberrations (CNA-devoid) are consistently prognostic across several other subtypes and can be validated in external cohorts. We then use a data-driven approach to seek the effects of miRNAs associated with differential co-expression of mRNAs, and find that miRNAs act as modulators of mRNA-mRNA interactions rather than as on-off molecular switches. We demonstrate such an important modulatory role for miRNAs in the biology of CNA-devoid breast cancers, a common subtype in which the immune response is prominent. These findings represent a new framework for studying the biology of miRNAs in human breast cancer.

Improving breast cancer survival analysis through competition-based multidimensional modeling

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

miR-135b coordinates progression of ErbB2-driven mammary carcinomas through suppression of MID1 and MTCH2

In an attempt to reveal deregulated miRNAs associated with the progression of carcinomas developed in BALB-neuT transgenic mice, we found increased expression of miR-135b during malignancy. Relevantly, we observed that miR-135b is up-regulated in basal or normal-like human breast cancers, and it correlates with patient survival and early metastatization. Therefore, we investigated its biological functions by modulating its expression (up- or down-regulation) in mammary tumor cells. Although no effect was observed on proliferation in cell culture and in orthotopically injected mice, miR-135b was able to control cancer cell stemness in a mammosphere assay, anchorage-independent growth in vitro, and lung cancer cell dissemination in mice after tail vein injections. Focusing on the miR-135b molecular mechanism, we observed that miR-135b controls malignancy via its direct targets, midline 1 (MID1) and mitochondrial carrier homolog 2 (MTCH2), as proved by biochemical and functional rescuing/phenocopying experiments. Consistently, an anti-correlation between miR-135b and MID1 or MTCH2 was found in human primary tumor samples. In conclusion, our research led us to the identification of miR-135b and its targets, MID1 and MTCH2, as relevant coordinators of mammary gland tumor progression.

Prioritizing breast cancer subtype related miRNAs using miRNA-mRNA dysregulated relationships extracted from their dual expression profiling

Identification of miRNA expression-based breast cancer subtypes is considered a critical means of prognostication. So far, the studies on breast cancer subtypes have not been well characterized, and few studies have performed expression profiling of both miRNA and mRNA from the same breast cancer subtypes samples. In this study we analyzed dual expression profiling data of miRNA and mRNA derived from the expression profiling of 489 miRNAs in 41 luminal-A breast tumors samples and 15 basal-like samples. We defined a correlation coefficient ratio (CCR) and used it to examine the correlative dysregulated relationships between miRNAs and mRNAs. A miRNA-mRNA dysregulated network was arisen from 6222 dysregulated relationships, and from this network, miRNA-miRNA networks specialized for luminal-A and basal-like breast cancer subtypes were extracted according to the CCR values. By analyzing the networks, we found that luminal-A trend and basal-like trend miRNA-miRNA network displayed a change in hubs which connected the most miRNAs, and therefore become the potential breast cancer subtype related miRNAs. In addition, we also used other network analysis methods for miRNA expression profiling data, such as weighted correlation network analysis (WGCNA), Bayesian network analysis, and miRNA similarity (MISIM) analysis to validate the identified miRNAs or miRNA clusters. This study provides a new analyzing method to predict candidate miRNAs of breast cancer subtype from a system biology level and help understanding the relationship between miRNA and mRNA in primary breast cancer subtype.

miRNA expression profiling of 51 human breast cancer cell lines reveals subtype and driver mutation-specific miRNAs

Introduction

Breast cancer is a genetically and phenotypically complex disease. To understand the role of miRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer cell lines to identify miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations.

Methods

Using a microarray carrying LNA™ modified oligonucleotide capture probes), expression levels of 725 human miRNAs were measured in 51 breast cancer cell lines. Differential miRNA expression was explored by unsupervised cluster analysis and was then associated with the molecular subtypes and genetic aberrations commonly present in breast cancer.

Results

Unsupervised cluster analysis using the most variably expressed miRNAs divided the 51 breast cancer cell lines into a major and a minor cluster predominantly mirroring the luminal and basal intrinsic subdivision of breast cancer cell lines. One hundred and thirteen miRNAs were differentially expressed between these two main clusters. Forty miRNAs were differentially expressed between basal-like and normal-like/claudin-low cell lines. Within the luminal-group, 39 miRNAs were associated with ERBB2 overexpression and 24 with E-cadherin gene mutations, which are frequent in this subtype of breast cancer cell lines. In contrast, 31 miRNAs were associated with E-cadherin promoter hypermethylation, which, contrary to E-cadherin mutation, is exclusively observed in breast cancer cell lines that are not of luminal origin. Thirty miRNAs were associated with p16^INK4 status while only a few miRNAs were associated with BRCA1, PIK3CA/PTEN and TP53 mutation status. Twelve miRNAs were associated with DNA copy number variation of the respective locus.

Conclusion

Luminal-basal and epithelial-mesenchymal associated miRNAs determine the subdivision of miRNA transcriptome of breast cancer cell lines. Specific sets of miRNAs were associated with ERBB2 overexpression, p16^INK4a or E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of these genetic aberrations. Additionally, miRNAs, which are located in a genomic region showing recurrent genetic aberrations, may themselves play a driver role in breast carcinogenesis or contribute to a driver gene in their vicinity. In short, our study provides detailed molecular miRNA portraits of breast cancer cell lines, which can be exploited for functional studies of clinically important miRNAs.

MicroRNA-31 sensitizes human breast cells to apoptosis by direct targeting of protein kinase C epsilon (PKCepsilon)

MicroRNAs post-transcriptionally regulate gene expression and thereby contribute to the modulation of numerous complex and disease-relevant cellular phenotypes, including cell proliferation, cell motility, apoptosis, and stress response. In breast cancer cell systems, miR-31 has been shown to inhibit cell migration, invasion, and metastasis. Here, we link enhanced expression of miR-31 to the inhibition of the oncogenic NF-κB pathway, thus supporting the tumor-suppressive function of this microRNA. We identified protein kinase C epsilon (PKCε encoded by the PRKCE gene) as a novel direct target of miR-31 and show that down-regulation of PKCε results in impaired NF-κB signaling, enhanced apoptosis, and increased sensitivity of MCF10A breast epithelial and MDA-MB-231 triple-negative breast cancer cells toward ionizing radiation as well as treatment with chemotherapeutics. Mechanistically, we attribute this sensitization to anti-cancer treatments to the PRKCE-mediated down-regulation of the anti-apoptotic factor BCL2. In clinical breast cancer samples, high BCL2 expression was associated with poor prognosis. Furthermore, we found an inverse correlation between miR-31 and BCL2 expression, highlighting the functional relevance of the indirect down-regulation of BCL2 via direct targeting of PRKCE by miR-31.

Influence of DNA copy number and mRNA levels on the expression of breast cancer related proteins

For a panel of cancer related proteins, the aim was to shed light on which molecular level the expression of each protein was mainly regulated in breast tumors, and to investigate whether differences in regulation were reflected in different molecular subtypes. DNA, mRNA and protein lysates from 251 breast tumor specimens were analyzed using appropriate microarray technologies. Data from all three levels were available for 52 proteins selected for their known involvement in cancer, primarily through the PI3K/Akt pathway. For every protein, in cis Spearman rank correlations between the three molecular levels were calculated across all samples and within each intrinsic gene expression subtype, enabling 63 comparisons altogether due to multiple gene probes matching to single proteins. Subtype-specific relationships between the three molecular levels were studied by calculating the variance of subtype-specific correlation and differences between overall and average subtype-specific correlation. The findings were validated in an external dataset comprising 703 breast tumor specimens. The proteins were sorted into four groups based on the calculated rank correlation values between the three molecular levels. Group A consisted of eight proteins with significant correlation between DNA copy number levels and mRNA expression, and between mRNA expression and protein expression (Bonferroni adjusted p < 0.05). Group B consisted of 14 proteins with significant correlation between mRNA expression and protein expression. Group C consisted of 15 proteins with significant correlation between copy number levels and mRNA expression. For the remaining 25 proteins (group D), no significant correlations was observed. Stratification of tumors according to intrinsic subtype enabled identification of positive correlations between copy number levels, mRNA and protein expression that were undetectable when considering the entire sample set. Protein pairings that either demonstrated high variance in correlation values between subtypes, or between subtypes and the total dataset were studied in particular. The protein expression of cleaved caspase 7 was most highly expressed, and correlated highest to CASP7 gene expression within the basal-like subtype, accompanied by the lowest amounts of hsa-miR-29c. Luminal A-like subtype demonstrated highest amounts of hsa-miR-29c (a miRNA with a putative target sequence in CASP7 mRNA), low expression of cleaved caspase 7 and low correlation to CASP7 gene expression. Such pattern might be an indication of hsa-miR-29c miRNA functioning as a repressor of translation of CASP7 within the luminal-A subtype. Across the entire cohort no correlation was found between CCNB1 copy number and gene expression. However, within most gene intrinsic subtypes, mRNA and protein expression of cyclin B1 was found positively correlated to copy number data, suggesting that copy number can affect the overall expression of this protein. Aberrations of cyclin B1 copy number also identified patients with reduced overall survival within each subtype. Based on correlation between the three molecular levels, genes and their products could be sorted into four groups for which the expression was likely to be regulated at different molecular levels. Further stratification suggested subtype-specific regulation that was not evident across the entire sample set.

A systematic evaluation of miRNA:mRNA interactions involved in the migration and invasion of breast cancer cells

In this study we performed a systematic evaluation of functional miRNA-mRNA interactions associated with the invasiveness of breast cancer cells using a combination of integrated miRNA and mRNA expression profiling, bioinformatics prediction, and functional assays. Analysis of the miRNA expression identified 11 miRNAs that were differentially expressed, including 7 down-regulated (miR-200c, miR-205, miR-203, miR-141, miR-34a, miR-183, and miR-375) and 4 up-regulated miRNAs (miR-146a, miR-138, miR-125b1 and miR-100), in invasive cell lines when compared to normal and less invasive cell lines. Transfection of miR-200c, miR-205, and miR-375 mimics into MDA-MB-231 cells led to the inhibition of in vitro cell migration and invasion. The integrated analysis of miRNA and mRNA expression identified 35 known and novel target genes of miR-200c, miR-205, and mir-375, including CFL2, LAMC1, TIMP2, ZEB1, CDH11, PRKCA, PTPRJ, PTPRM, LDHB, and SEC23A. Surprisingly, the majority of these genes (27 genes) were target genes of miR-200c, suggesting that miR-200c plays a pivotal role in regulating the invasiveness of breast cancer cells. We characterized one of the target genes of miR-200c, CFL2, and demonstrated that CFL2 is overexpressed in aggressive breast cancer cell lines and can be significantly down-regulated by exogenous miR-200c. Tissue microarray analysis further revealed that CFL2 expression in primary breast cancer tissue correlated with tumor grade. The results obtained from this study may improve our understanding of the role of these candidate miRNAs and their target genes in relation to breast cancer invasiveness and ultimately lead to the identification of novel biomarkers associated with prognosis.

Identifying in-trans process associated genes in breast cancer by integrated analysis of copy number and expression data

Genomic copy number alterations are common in cancer. Finding the genes causally implicated in oncogenesis is challenging because the gain or loss of a chromosomal region may affect a few key driver genes and many passengers. Integrative analyses have opened new vistas for addressing this issue. One approach is to identify genes with frequent copy number alterations and corresponding changes in expression. Several methods also analyse effects of transcriptional changes on known pathways. Here, we propose a method that analyses in-cis correlated genes for evidence of in-trans association to biological processes, with no bias towards processes of a particular type or function. The method aims to identify cis-regulated genes for which the expression correlation to other genes provides further evidence of a network-perturbing role in cancer. The proposed unsupervised approach involves a sequence of statistical tests to systematically narrow down the list of relevant genes, based on integrative analysis of copy number and gene expression data. A novel adjustment method handles confounding effects of co-occurring copy number aberrations, potentially a large source of false positives in such studies. Applying the method to whole-genome copy number and expression data from 100 primary breast carcinomas, 6373 genes were identified as commonly aberrant, 578 were highly in-cis correlated, and 56 were in addition associated in-trans to biological processes. Among these in-trans process associated and cis-correlated (iPAC) genes, 28% have previously been reported as breast cancer associated, and 64% as cancer associated. By combining statistical evidence from three separate subanalyses that focus respectively on copy number, gene expression and the combination of the two, the proposed method identifies several known and novel cancer driver candidates. Validation in an independent data set supports the conclusion that the method identifies genes implicated in cancer.

GATA3 suppresses metastasis and modulates the tumour microenvironment by regulating microRNA-29b expression

Despite advances in our understanding of breast cancer, patients with metastatic disease have poor prognoses. GATA3 is a transcription factor that specifies and maintains mammary luminal epithelial cell fate, and its expression is lost in breast cancer, correlating with a worse prognosis in human patients. Here, we show that GATA3 promotes differentiation, suppresses metastasis and alters the tumour microenvironment in breast cancer by inducing microRNA-29b (miR-29b) expression. Accordingly, miR-29b is enriched in luminal breast cancers and loss of miR-29b, even in GATA3-expressing cells, increases metastasis and promotes a mesenchymal phenotype. Mechanistically, miR-29b inhibits metastasis by targeting a network of pro-metastatic regulators involved in angiogenesis, collagen remodelling and proteolysis, including VEGFA, ANGPTL4, PDGF, LOX and MMP9, and targeting ITGA6, ITGB1 and TGFB, thereby indirectly affecting differentiation and epithelial plasticity. The discovery that a GATA3-miR-29b axis regulates the tumour microenvironment and inhibits metastasis opens up possibilities for therapeutic intervention in breast cancer.

Downregulation of miR-34a in breast tumors is not associated with either p53 mutations or promoter hypermethylation while it correlates with metastasis

MicroRNA-34 family has anti-proliferative and apoptotic roles. Recent studies have shown that p53 upregulates miR-34 family leading to direct repression of several key oncogenes. Inactivation of miR-34a has been reported in multiple types of malignancies including breast cancer. The critical role of miR-34a in p53-mediated cell cycle arrest and apoptosis invokes studies focusing on the specific role of miR-34a dysregulation in carcinogenesis. While presence of p53 mutations has frequently been described in breast cancer, still most of the breast tumors do not show any variation in the p53 coding sequence or protein expression. Therefore, it is important to clarify possible involvement of other mediators of p53 pathway in breast cancer. In this study, expression of mature miR-34a in breast tumors with wild-type p53 was investigated in order to find any correlation between dysregulation of miR-34a expression and breast cancer. In about 40 % of the wild-type p53 samples, miR-34a was significantly downregulated. Neither hypermethylation of the miR-34a promoter nor genetic variations of the p53-binding site were detected in tumor samples with downregulated miR-34a. This study has provided evidence that miR-34a expression can be affected in a significant proportion of breast tumors independent of p53. Furthermore, downregulation of miR-34a was significantly associated with metastasis, while there was a significant correlation between upregulation of miR-34a and non-metastatic condition indicating a protective role for miR-34a against more invasive disease. Knowledge of miR-34a status may provide additional useful information regarding the nature of breast tumors, especially when p53 testing does not show any aberration.

TGF-β upregulates miR-181a expression to promote breast cancer metastasis

Late-stage breast cancer metastasis is driven by dysregulated TGF-β signaling, but the underlying molecular mechanisms have not been fully elucidated. We attempted to recapitulate tumor and metastatic microenvironments via the use of biomechanically compliant or rigid 3D organotypic cultures and combined them with global microRNA (miR) profiling analyses to identify miRs that were upregulated in metastatic breast cancer cells by TGF-β. Here we establish miR-181a as a TGF-β-regulated "metastamir" that enhanced the metastatic potential of breast cancers by promoting epithelial-mesenchymal transition, migratory, and invasive phenotypes. Mechanistically, inactivation of miR-181a elevated the expression of the proapoptotic molecule Bim, which sensitized metastatic cells to anoikis. Along these lines, miR-181a expression was essential in driving pulmonary micrometastatic outgrowth and enhancing the lethality of late-stage mammary tumors in mice. Finally, miR-181a expression was dramatically and selectively upregulated in metastatic breast tumors, particularly triple-negative breast cancers, and was highly predictive for decreased overall survival in human breast cancer patients. Collectively, our findings strongly implicate miR-181a as a predictive biomarker for breast cancer metastasis and patient survival, and consequently, as a potential therapeutic target in metastatic breast cancer.

miRNA target enrichment analysis reveals directly active miRNAs in health and disease

microRNAs (miRNAs) are short non-coding regulatory RNA molecules. The activity of a miRNA in a biological process can often be reflected in the expression program that characterizes the outcome of the activity. We introduce a computational approach that infers such activity from high-throughput data using a novel statistical methodology, called minimum-mHG (mmHG), that examines mutual enrichment in two ranked lists. Based on this methodology, we provide a user-friendly web application that supports the statistical assessment of miRNA target enrichment analysis (miTEA) in the top of a ranked list of genes or proteins. Using miTEA, we analyze several target prediction tools by examining performance on public miRNA constitutive expression data. We also apply miTEA to analyze several integrative biology data sets, including a novel matched miRNA/mRNA data set covering nine human tissue types. Our novel findings include proposed direct activity of miR-519 in placenta, a direct activity of the oncogenic miR-15 in different healthy tissue types and a direct activity of the poorly characterized miR-768 in both healthy tissue types and cancer cell lines. The miTEA web application is available at http://cbl-gorilla.cs.technion.ac.il/miTEA/.

Non-canonical Notch signaling activates IL-6/JAK/STAT signaling in breast tumor cells and is controlled by p53 and IKKα/IKKβ

Notch signaling is frequently hyperactivated in breast cancer, but how the enhanced signaling contributes to the tumor process is less well understood. In this report, we identify the proinflammatory cytokine interleukin-6 (IL-6) as a novel Notch target in breast tumor cells. Enhanced Notch signaling upregulated IL-6 expression, leading to activation of autocrine and paracrine Janus kinase/signal transducers and activators of transcription signaling. IL-6 upregulation was mediated by non-canonical Notch signaling, as it could be effectuated by a cytoplasmically localized Notch intracellular domain and was independent of the DNA-binding protein CSL. Instead, Notch-mediated IL-6 upregulation was controlled by two proteins in the nuclear factor (NF)-κB signaling cascade, IKKα and IKKβ (inhibitor of nuclear factor kappa-B kinase subunit alpha and beta, respectively), as well as by p53. Activation of IL-6 by Notch required IKKα/IKKβ function, but interestingly, did not engage canonical NF-κB signaling, in contrast to IL-6 activation by inflammatory agents such as lipopolysaccharide. With regard to p53 status, IL-6 expression was upregulated by Notch when p53 was mutated or lost, and restoring wild-type p53 into p53-mutated or -deficient cells abrogated the IL-6 upregulation. Furthermore, Notch-induced transcriptomes from p53 wild-type and -mutated breast tumor cell lines differed extensively, and for a subset of genes upregulated by Notch in a p53-mutant cell line, this upregulation was reduced by wild-type p53. In conclusion, we identify IL-6 as a novel non-canonical Notch target gene, and reveal roles for p53 and IKKα/IKKβ in non-canonical Notch signaling in breast cancer and in the generation of cell context-dependent diversity in the Notch signaling output.

miR-10b*, a master inhibitor of the cell cycle, is down-regulated in human breast tumours

Deregulated proliferation is a hallmark of cancer cells. Here, we show that microRNA-10b* is a master regulator of breast cancer cell proliferation and is downregulated in tumoural samples versus matched peritumoural counterparts. Two canonical CpG islands (5 kb) upstream from the precursor sequence are hypermethylated in the analysed breast cancer tissues. Ectopic delivery of synthetic microRNA-10b* in breast cancer cell lines or into xenograft mouse breast tumours inhibits cell proliferation and impairs tumour growth in vivo, respectively. We identified and validated in vitro and in vivo three novel target mRNAs of miR-10b* (BUB1, PLK1 and CCNA2), which play a remarkable role in cell cycle regulation and whose high expression in breast cancer patients is associated with reduced disease-free survival, relapse-free survival and metastasis-free survival when compared to patients with low expression. This also suggests that restoration of microRNA-10b* expression might have therapeutic promise.

Subtype-specific response to bevacizumab is reflected in the metabolome and transcriptome of breast cancer xenografts

Antiangiogenic therapy with bevacizumab has shown varying results in breast cancer clinical trials. Identifying robust biomarkers for selecting patients who may benefit from such treatment and for monitoring response is important for the future use of bevacizumab. Two established xenograft models representing basal-like and luminal-like breast cancer were used to study bevacizumab treatment response on the metabolic and gene expression levels. Tumor samples were obtained from mice treated with bevacizumab, doxorubicin or a combination of the two drugs, and high resolution magic angle spinning magnetic resonance spectroscopy and gene expression microarray analysis was performed. Combination treatment with bevacizumab showed the strongest growth inhibiting effect in basal-like tumors, and this was reflected by a significant change in the metabolomic and transcriptomic profiles. In the luminal-like xenografts, addition of bevacizumab did not improve the effect of doxorubicin. On the global transcriptomic level, the largest gene expression changes were observed for the most efficient treatment in both models. Glycerophosphocholine showed opposite response in the treated xenografts compared with untreated controls; lower in basal-like and higher in luminal-like tumors. Comparing combination therapy with doxorubicin monotherapy in basal-like xenografts, 14 genes showed significant differential expression, including very low density lipoprotein receptor (VLDLR) and hemoglobin, theta 1 (HBQ1). Bevacizumab-treated tumors were associated with a more hypoxic phenotype, while no evidence was found for associations between bevacizumab treatment and vascular invasion or tumor grade. This study underlines the importance of characterizing biological differences between subtypes of breast cancer to identify personalized biomarkers for improved patient stratification and evaluation of response to therapy.

Potential tumorigenic programs associated with TP53 mutation status reveal role of VEGF pathway

Background:

Targeting differentially activated or perturbed tumour pathways is the key idea in individualised cancer therapy, which is emerging as an important option in treating cancers with poor prognostic profiles. TP53 mutation status is known as a core determinant of survival in breast cancer. The pathways disrupted in association with TP53 mutation status in tumours are not well characterised.

Method:

In this study, we stratify breast cancers based on their TP53 mutation status and identify the set of dysregulated tumorigenic pathways and corresponding candidate driver genes using breast cancer gene expression profiles. Expressions of these genes were evaluated for their effect on patient survival first in univariate models, followed by multivariate models with TP53 status as a covariate.

Results:

The most strongly differentially enriched pathways between breast cancers stratified by TP53 mutation status include in addition to TP53 signalling, several known cancer pathways involved in renal, prostate, pancreatic, colorectal, lung and other cancers, and signalling pathways such as calcium signalling, MAPK, ERBB and vascular endothelial growth factor (VEGF) signalling pathways. We found that mutant TP53 in conjunction with active estrogen receptor (ER) signalling significantly influence survival. We also found that upregulation of VEGFA mRNA levels in association with active ER signalling is a significant marker for poor survival, even in the presence of wild-type TP53.

Conclusion:

Mutation status of TP53 in breast cancer involves wide ranging derangement of several pathways. Among the candidate genes of the significantly deranged pathways, we identified VEGFA expression as an important marker of survival even when controlled by TP53 mutation status. Interestingly, independent of the TP53 mutation status, the survival effect of VEGFA was found significant in patients with active ER signalling (ER/PgR+), but not in those with ER/PgR− status. Therefore, we propose more studies to focus on the role of complex interplay between TP53, ER and VEGF signalling from therapeutic and prognostic context in breast cancer.

TFPI alpha and beta regulate mRNAs and microRNAs involved in cancer biology and in the immune system in breast cancer cells

Emerging evidence indicate a new role of TFPI in cancer biology. We recently reported that both isoforms of TFPI induced apoptosis and inhibited proliferation of cancer cells. The signaling pathway(s) mediating the effects of TFPI is, however, presently still unclear. Our goal was to further investigate the cellular processes affected by TFPI and to get insight into the molecular mechanisms involved in the effects of TFPI, using a global gene expression study approach. TFPIα or TFPIβ cDNA were transfected into SK-BR-3 breast cancer cells for stable overexpression. Global mRNA and microRNA (miRNA) expressions were measured and functional annotation of the differentially expressed genes and miRNAs according to gene ontology terms was conducted. Selected results were validated using qRT-PCR and Western blot. A total of 242 and 801 mRNA transcripts and 120 and 46 miRNAs were differentially expressed in cells overexpressing TFPIα or TFPIβ, respectively. Overexpression of either isoform significantly affected the expression of genes involved in cell development (apoptosis, cell movement, migration, invasion, colony formation, growth, and adhesion) and immune response. Network analyses revealed biological interactions between these genes and implied that several of the genes may be involved in both processes. The expression profiles also correlated significantly with clinical phenotype and outcome. Functional cluster analyses indicated altered activity of the epidermal growth factor receptor, small GTPases, and the NF-κB and JAK/STAT cascades when TFPI was overexpressed, and increased activity of the transcription factors NF-κB and Elk-1 and phospho-Akt levels was observed. Integrated mRNA-miRNA analyses showed that 19% and 32% of the differentially expressed genes in cells overexpressing TFPIα or TFPIβ, respectively, may have been regulated by miRNAs. Overexpression of TFPI in breast cancer cells affected the expression of mRNAs and miRNAs involved in processes facilitating cancer cell growth and immunologic response, possibly by signal transduction involving the EGFR pathway.

Cancer classification: Mutual information, target network and strategies of therapy

Background

Cancer therapy is a challenging research area because side effects often occur in chemo and radiation therapy. We intend to study a multi-targets and multi-components design that will provide synergistic results to improve efficiency of cancer therapy.

Methods

We have developed a general methodology, AMFES (Adaptive Multiple FEature Selection), for ranking and selecting important cancer biomarkers based on SVM (Support Vector Machine) classification. In particular, we exemplify this method by three datasets: a prostate cancer (three stages), a breast cancer (four subtypes), and another prostate cancer (normal vs. cancerous). Moreover, we have computed the target networks of these biomarkers as the signatures of the cancers with additional information (mutual information between biomarkers of the network). Then, we proposed a robust framework for synergistic therapy design approach which includes varies existing mechanisms.

Results

These methodologies were applied to three GEO datasets: GSE18655 (three prostate stages), GSE19536 (4 subtypes breast cancers) and GSE21036 (prostate cancer cells and normal cells) shown in. We selected 96 biomarkers for first prostate cancer dataset (three prostate stages), 72 for breast cancer (luminal A vs. luminal B), 68 for breast cancer (basal-like vs. normal-like), and 22 for another prostate cancer (cancerous vs. normal. In addition, we obtained statistically significant results of mutual information, which demonstrate that the dependencies among these biomarkers can be positive or negative.

Conclusions

We proposed an efficient feature ranking and selection scheme, AMFES, to select an important subset from a large number of features for any cancer dataset. Thus, we obtained the signatures of these cancers by building their target networks. Finally, we proposed a robust framework of synergistic therapy for cancer patients. Our framework is not only supported by real GEO datasets but also aim to a multi-targets/multi-components drug design tool, which improves the traditional single target/single component analysis methods. This framework builds a computational foundation which can provide a clear classification of cancers and lead to an efficient cancer therapy.

Circulating microRNAs: new biomarkers in diagnosis, prognosis and treatment of cancer (review)

MicroRNAs (miRNAs) are small non-coding, endogenous, single-stranded RNAs. MiRNAs have been implicated in different areas such as the immune response, neural development, DNA repair, apoptosis, oxidative stress response and cancer. However, while the majority of miRNAs are found intracellularly, a significant number of miRNAs have been observed outside of cells, including various body fluids. Circulating miRNAs function as 'extracellular communication RNAs' that play an important role in cell proliferation and differentiation. MiRNA regulation is essential to many cellular processes, and escape from this regulatory network seems to be a common characteristic of several disease processes and malignant transformation. The interest in circulating miRNAs reflects in fact their central role in regulation of gene expression and the implication of miRNA-specific aberrant expression in the pathogenesis of cancer, cardiac, metabolic, neurologic, immune-related diseases as well as others. In our review we aimed to summarize the data related to the action of cellular miRNAs on the onset of various diseases, thus bringing together some of the latest information available on the role of circulating miRNAs. Additionally, the role of circulating miRNAs could be particularly relevant in the context of neoplastic diseases. At least 79 miRNAs have been reported as plasma or serum miRNA biomarkers of solid and hematologic tumors. Circulating miRNA profiling could improve the diagnosis of cancer, and could predict outcome for cancer patients, while the profiling of alterations in circulating miRNA that may signal a predisposition to cancer, could also be a therapeutic target in these patients.

Differential gene expression pattern in early gastric cancer by an integrative systematic approach

To elucidate the molecular basis of early gastric cancer (EGC), the genome-wide expression pattern of cancer and normal tissues from 27 patients were analyzed by a microarray-based method. Using an integrative systematic bioinformatics approach, we classified the differentially expressed genes in EGC. Interestingly, the more highly expressed genes in EGC exhibited the most significant correlation with cell migration and metastasis. This implies that, even at the early stage of gastric cancer, the molecular properties usually observed in late-stage cancer are already present. Furthermore, we have found a novel association between the expression pattern and molecular pathways of EGC and estrogen receptor α (ERα)-negative breast cancer through cross-experimental analysis. These results provide new insights into the biological properties of EGC, as well as yielding useful basic data for the study of molecular mechanisms of EGC carcinogenesis.

miRSystem: an integrated system for characterizing enriched functions and pathways of microRNA targets

Background

Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses.

Results

First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted.

Conclusions

MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.

Antagonism pattern detection between microRNA and target expression in Ewing's sarcoma

MicroRNAs (miRNAs) have emerged as fundamental regulators that silence gene expression at the post-transcriptional and translational levels. The identification of their targets is a major challenge to elucidate the regulated biological processes. The overall effect of miRNA is reflected on target mRNA expression, suggesting the design of new investigative methods based on high-throughput experimental data such as miRNA and transcriptome profiles. We propose a novel statistical measure of non-linear dependence between miRNA and mRNA expression, in order to infer miRNA-target interactions. This approach, which we name antagonism pattern detection, is based on the statistical recognition of a triangular-shaped pattern in miRNA-target expression profiles. This pattern is observed in miRNA-target expression measurements since their simultaneously elevated expression is statistically under-represented in the case of miRNA silencing effect. The proposed method enables miRNA target prediction to strongly rely on cellular context and physiological conditions reflected by expression data. The procedure has been assessed on synthetic datasets and tested on a set of real positive controls. Then it has been applied to analyze expression data from Ewing’s sarcoma patients. The antagonism relationship is evaluated as a good indicator of real miRNA-target biological interaction. The predicted targets are consistently enriched for miRNA binding site motifs in their 3′UTR. Moreover, we reveal sets of predicted targets for each miRNA sharing important biological function. The procedure allows us to infer crucial miRNA regulators and their potential targets in Ewing’s sarcoma disease. It can be considered as a valid statistical approach to discover new insights in the miRNA regulatory mechanisms.

Identifying transcription factors and microRNAs as key regulators of pathways using Bayesian inference on known pathway structures

Background

Transcription factors and microRNAs act in concert to regulate gene expression in eukaryotes. Numerous computational methods based on sequence information are available for the prediction of target genes of transcription factors and microRNAs. Although these methods provide a static snapshot of how genes may be regulated, they are not effective for the identification of condition-specific regulators.

Results

We propose a new method that combines: a) transcription factors and microRNAs that are predicted to target genes in pathways, with b) microarray expression profiles of microRNAs and mRNAs, in conjunction with c) the known structure of molecular pathways. These elements are integrated into a Bayesian network derived from each pathway that, through probability inference, allows for the prediction of the key regulators in the pathway. We demonstrate 1) the steps to discretize the expression data for the computation of conditional probabilities in a Bayesian network, 2) the procedure to construct a Bayesian network using the structure of a known pathway and the transcription factors and microRNAs predicted to target genes in that pathway, and 3) the inference results as potential regulators of three signaling pathways using microarray expression profiles of microRNA and mRNA in estrogen receptor positive and estrogen receptor negative tumors.

Conclusions

We displayed the ability of our framework to integrate multiple sets of microRNA and mRNA expression data, from two phenotypes, with curated molecular pathway structures by creating Bayesian networks. Moreover, by performing inference on the network using known evidence, e.g., status of differentially expressed genes, or by entering hypotheses to be tested, we obtain a list of potential regulators of the pathways. This, in turn, will help increase our understanding about the regulatory mechanisms relevant to the two phenotypes.

Deregulated miRNAs in hereditary breast cancer revealed a role for miR-30c in regulating KRAS oncogene

Aberrant miRNA expression has been previously established in breast cancer and has clinical relevance. However, no studies so far have defined miRNAs deregulated in hereditary breast tumors. In this study we investigated the role of miRNAs in hereditary breast tumors comparing with normal breast tissue. Global miRNA expression profiling using Exiqon microarrays was performed on 22 hereditary breast tumors and 15 non-tumoral breast tissues. We identified 19 miRNAs differentially expressed, most of them down-regulated in tumors. An important proportion of deregulated miRNAs in hereditary tumors were previously identified commonly deregulated in sporadic breast tumors. Under-expression of these miRNAs was validated by qRT-PCR in additional 18 sporadic breast tumors and their normal breast tissue counterparts. Pathway enrichment analysis revealed that deregulated miRNAs collectively targeted a number of genes belonging to signaling pathways such as MAPK, ErbB, mTOR, and those regulating cell motility or adhesion. In silico prediction detected KRAS oncogene as target of several deregulated miRNAs. In particular, we experimentally validated KRAS as a miR-30c target. Luciferase assays confirmed that miR-30c binds the 3′UTR of KRAS transcripts and expression of pre-miR-30c down-regulated KRAS mRNA and protein. Furthermore, miR-30c overexpression inhibited proliferation of breast cancer cells. Our results identify miRNAs associated to hereditary breast cancer, as well as miRNAs commonly miss-expressed in hereditary and sporadic tumors, suggesting common underlying mechanisms of tumor progression. In addition, we provide evidence that KRAS is a target of miR-30c, and that this miRNA suppresses breast cancer cell growth potentially through inhibition of KRAS signaling.

The clinico-pathologic role of microRNAs miR-9 and miR-151-5p in breast cancer metastasis

BACKGROUND

MicroRNAs (miRNAs) may function as suppressors or promoters of tumor metastasis according to their messenger RNA targets. Previous studies have suggested that miR-9 and miR-151-5p are associated with metastasis in breast cancer and hepatocellular carcinoma, respectively. We aimed to further establish the potential roles of miR-9 and miR-151-5p in tumor invasion and metastasis and investigate their use as biomarkers.

METHODS

We used quantitative real-time PCR (qRT-PCR) to measure differences in miR-9 and miR-151-5p expression between primary breast tumors and their lymph-node metastases in 194 paired tumor samples from 97 patients. We also correlated expression levels with histologic data to investigate their utility as biomarkers.

RESULTS

There were no significant differences in miR-9 expression between the primary tumors and lymph nodes; however, miR-151-5p expression was significantly lower in the lymph-node metastases than in their corresponding tumors (p < 0.05). miR-9 levels were elevated in primary breast tumors from patients diagnosed with higher-grade tumors (p < 0.05); however, no differences were observed in miR-151-5p levels between different grades of tumor. Interestingly, miR-9 levels were elevated in invasive lobular carcinomas (ILC) compared with invasive ductal carcinomas (IDC; p < 0.01).

CONCLUSIONS

In aggregate, these data suggest that miR-151-5p upregulation may suppress metastasis in primary breast tumors. Both miRNAs may serve as useful biomarkers in future clinical trials in breast cancer.

Overrepresentation of transcription factor families in the genesets underlying breast cancer subtypes

Background

The human genome contains a large amount of cis-regulatory DNA elements responsible for directing both spatial and temporal gene-expression patterns. Previous studies have shown that based on their mRNA expression breast tumors could be divided into five subgroups (Luminal A, Luminal B, Basal, ErbB2⁺ and Normal-like), each with a distinct molecular portrait. Whole genome gene expression analysis of independent sets of breast tumors reveals repeatedly the robustness of this classification. Furthermore, breast tumors carrying a TP53 mutation show a distinct gene expression profile, which is in strong association to the distinct molecular portraits. The mRNA expression of 552 genes, which varied considerably among the different tumors, but little between two samples of the same tumor, has been shown to be sufficient to separate these tumor subgroups.

Results

We analyzed in silico the transcriptional regulation of genes defining the subgroups at 3 different levels: 1. We studied the pathways in which the genes distinguishing the subgroups of breast cancer may be jointly involved including upstream regulators (1^st and 2^nd level of regulation) as well as downstream targets of these genes. 2. Then we analyzed the promoter areas of these genes (−500 bp tp +100 bp relative to the transcription start site) for canonical transcription binding sites using Genomatix. 3. We looked for the actual expression levels of the identified TF and how they correlate with the overrepresentation of their TF binding sites in the separate groups. We report that promoter composition of the genes that most strongly predict the patient subgroups is distinct. The class-predictive genes showed a clearly different degree of overrepresentation of transcription factor families in their promoter sequences.

Conclusion

The study suggests that transcription factors responsible for the observed expression pattern in breast cancers may lead us to important biological pathways.

Re-expression of microRNA-375 reverses both tamoxifen resistance and accompanying EMT-like properties in breast cancer

Epithelial-mesenchymal transition (EMT) is an initiating event in tumor cell invasion and metastasis. It has been shown to occur in resistance to a range of cancer therapies, including tamoxifen. MicroRNAs (miRNAs) have been associated with EMT as well as resistance to standard therapies. To investigate the role of miRNAs in the development of resistance to tamoxifen as well as accompanying EMT-like properties, we established a tamoxifen-resistant (TamR) model by continually exposing MCF-7 breast cancer cells to tamoxifen. In addition to the molecular changes known to be involved in acquired tamoxifen resistance, TamR cells displayed mesenchymal features and had increased invasiveness. Genome-wide miRNA microarray analysis revealed that miRNA-375 was among the top downregulated miRNAs in resistant cells. Re-expression of miR-375 was sufficient to sensitize TamR cells to tamoxifen and partly reversed EMT. A combination of mRNA profiling, bioinformatics analysis and experimental validation identified metadherin (MTDH) as a direct target of miR-375. Knockdown of MTDH partially phenocopied the effects of miR-375 on the sensitivity to tamoxifen and the reversal of EMT. We observed an inverse correlation between the expression of miR-375 and its target MTDH in primary breast cancer samples, implying the pathological relevance of targeting. Finally, tamoxifen-treated patients with higher expression of MTDH had a shorter disease-free survival and higher risk of relapse. As most cancer-related deaths occur because of resistance to standard therapies and metastasis, re-expression of miR-375 or targeting MTDH might serve as potential therapeutic approaches for the treatment of TamR breast cancer.

Mutant p53 disrupts mammary tissue architecture via the mevalonate pathway

p53 is a frequent target for mutation in human tumors, and mutant p53 proteins can actively contribute to tumorigenesis. We employed a three-dimensional culture model in which nonmalignant breast epithelial cells form spheroids reminiscent of acinar structures found in vivo, whereas breast cancer cells display highly disorganized morphology. We found that mutant p53 depletion is sufficient to phenotypically revert breast cancer cells to a more acinar-like morphology. Genome-wide expression analysis identified the mevalonate pathway as significantly upregulated by mutant p53. Statins and sterol biosynthesis intermediates reveal that this pathway is both necessary and sufficient for the phenotypic effects of mutant p53 on breast tissue architecture. Mutant p53 associates with sterol gene promoters at least partly via SREBP transcription factors. Finally, p53 mutation correlates with highly expressed sterol biosynthesis genes in human breast tumors. These findings implicate the mevalonate pathway as a therapeutic target for tumors bearing mutations in p53.

Efficient motif search in ranked lists and applications to variable gap motifs

Sequence elements, at all levels—DNA, RNA and protein, play a central role in mediating molecular recognition and thereby molecular regulation and signaling. Studies that focus on measuring and investigating sequence-based recognition make use of statistical and computational tools, including approaches to searching sequence motifs. State-of-the-art motif searching tools are limited in their coverage and ability to address large motif spaces. We develop and present statistical and algorithmic approaches that take as input ranked lists of sequences and return significant motifs. The efficiency of our approach, based on suffix trees, allows searches over motif spaces that are not covered by existing tools. This includes searching variable gap motifs—two half sites with a flexible length gap in between—and searching long motifs over large alphabets. We used our approach to analyze several high-throughput measurement data sets and report some validation results as well as novel suggested motifs and motif refinements. We suggest a refinement of the known estrogen receptor 1 motif in humans, where we observe gaps other than three nucleotides that also serve as significant recognition sites, as well as a variable length motif related to potential tyrosine phosphorylation.

Integrated Analysis Reveals hsa-miR-142 as a Representative of a Lymphocyte-Specific Gene Expression and Methylation Signature

Gene expression profiling has provided insights into different cancer types and revealed tissue-specific expression signatures. Alterations in microRNA expression contribute to the pathogenesis of many types of human diseases. Few studies have integrated all levels of gene expression, miRNA and methylation to uncover correlations between these data types. We performed an integrated profiling to discover instances of miRNAs associated with a gene expression and DNA methylation signature across multiple cancer types. Using data from The Cancer Genome Atlas (TCGA), we revealed a concordant gene expression and methylation signature associated with the microRNA hsa-miR-142 across the same samples. In all cancer types examined, we found a signature of co-expression of a gene set R and methylated sites M, which correlate positively (M+) or negatively (M−) with the expression of hsa-miR-142. The set R consistently contains many genes, such as TRAF3IP3, NCKAP1L, CD53, LAPTM5, PTPRC, EVI2B, DOCK2, LCP2, CYBB and FYB. The signature is preserved across glioblastoma, ovarian, breast, colon, kidney, lung, uterine and rectum cancer. There is 28% overlap of methylation sites in M between glioblastoma (GBM) and ovarian cancer. There is 60% overlap of genes in R between GBM and ovarian (P = 1.3e⁻¹¹). Most of the genes in R are known to be expressed in lymphocytes and haematopoietic stem cells, while M reflects membrane proteins involved in cell-cell adhesion functions. We speculate that the hsa-miR-142 associated signature may signal haematopoietic-specific processes and an accumulation of methylation events triggering a progressive loss of cell-cell adhesion. We also observed that GBM samples belonging to the proneural subtype tend to have underexpressed hsa-miR-142 and R genes, hypomethylated M+ and hypermethylated M−, while the mesenchymal samples have the opposite profile.

Integrated analysis of miRNA and mRNA profiles enables target acquisition in human cancers

miRNAs play a role in post-transcriptional gene regulation by translational repression and/or mRNA degradation in a very tissue-specific manner. In order to understand the function of a miRNA, it is best to identify the genes that it regulates. Putative mRNA targets of miRNAs identified from seed sequence matches are available using computational algorithms in various web-based databases. However, these tend to have high false-positive rates and, owing to a whole-genome approach, cannot identify tissue/tumor specificity of regulation. The evaluated article presents a large amount of data analyzing global RNA expression in breast cancer and examines whether miRNAs are prognostic due to their effects on mRNA targets. This valuable and important resource of combined miRNA and mRNA expression in breast cancer and its subtypes has been summarized. Many studies have now investigated the integrated analysis of miRNA:mRNA profiles in human malignancies, the goal as always being to identify novel biomarkers and therapeutic targets for each tumor.

Young intragenic miRNAs are less coexpressed with host genes than old ones: implications of miRNA-host gene coevolution

MicroRNAs (miRNAs) have emerged as key regulators of gene expression. Intragenic miRNAs account for ∼50% of mammalian miRNAs. Classic studies reported that they are usually coexpressed with host genes. Here, using genome-wide miRNA and gene expression profiles from five sample sets, we show that evolutionarily conserved (‘old’) intragenic miRNAs tend to be coexpressed with host genes, but non-conserved (‘young’) ones rarely do so. This result is robust: in all sample sets, the coexpression rate of young miRNAs is significantly lower than that of conserved ones even after controlling for abundance. As a result, although young miRNAs dominate in human genome, the majority of intragenic miRNAs that show coexpression with host genes are phylogenetically old ones. For younger miRNAs, extrapolation of their expression profiles from those of their host genes should be treated with caution. We propose a model to explain this phenomenon in which the majority of young miRNAs are unlikely to be coexpressed with host genes; however, for some fraction of young miRNAs coexpression with their host genes, initially imbued by chromatin level effects, is advantageous and these are the ones likely to embed into the system and evolve ever higher levels of coexpression, possibly by evolving piggybacking mechanisms.

MicroRNA-200c represses migration and invasion of breast cancer cells by targeting actin-regulatory proteins FHOD1 and PPM1F

MicroRNA-200c (miR-200c) has been shown to suppress epithelial-mesenchymal transition (EMT), which is attributed mainly to targeting of ZEB1/ZEB2, repressors of the cell-cell contact protein E-cadherin. Here we demonstrated that modulation of miR-200c in breast cancer cells regulates cell migration, cell elongation, and transforming growth factor β (TGF-β)-induced stress fiber formation by impacting the reorganization of cytoskeleton that is independent of the ZEB/E-cadherin axis. We identified FHOD1 and PPM1F, direct regulators of the actin cytoskeleton, as novel targets of miR-200c. Remarkably, expression levels of FHOD1 and PPM1F were inversely correlated with the level of miR-200c in breast cancer cell lines, breast cancer patient samples, and 58 cancer cell lines of various origins. Furthermore, individual knockdown/overexpression of these target genes phenocopied the effects of miR-200c overexpression/inhibition on cell elongation, stress fiber formation, migration, and invasion. Mechanistically, targeting of FHOD1 by miR-200c resulted in decreased expression and transcriptional activity of serum response factor (SRF), mediated by interference with the translocation of the SRF coactivator mycocardin-related transcription factor A (MRTF-A). This finally led to downregulation of the expression and phosphorylation of the SRF target myosin light chain 2 (MLC2) gene, required for stress fiber formation and contractility. Thus, miR-200c impacts on metastasis by regulating several EMT-related processes, including a novel mechanism involving the direct targeting of actin-regulatory proteins.

Subcellular fate and off-target effects of siRNA, shRNA, and miRNA

RNA interference (RNAi) strategies include double-stranded RNA (dsRNA), small interfering RNA (siRNA), short hairpin RNA (shRNA), and microRNA (miRNA). As this is a highly specific technique, efforts have been made to utilize RNAi towards potential knock down of disease-causing genes in a targeted fashion. RNAi has the potential to selectively inhibit gene expression by degrading or blocking the translation of the target mRNA. However, delivering these RNAs to specific cells presents a significant challenge. Some of these challenges result from the necessity of traversing the circulatory system while avoiding kidney filtration, degradation by endonucleases, aggregation with serum proteins, and uptake by phagocytes. Further, non-specific delivery may result in side-effects, including the activation of immune response. We discuss the challenges in the systemic delivery to target cells, cellular uptake, endosomal release and intracellular transport of RNAi drugs and recent progress in overcoming these barriers. We also discuss approaches that increase the specificity and metabolic stability and reduce the off-target effects of RNAi strategy.

Breast cancer - one term, many entities?

Breast cancer, rather than constituting a monolithic entity, comprises heterogeneous tumors with different clinical characteristics, disease courses, and responses to specific treatments. Tumor-intrinsic features, including classical histological and immunopathological classifications as well as more recently described molecular subtypes, separate breast tumors into multiple groups. Tumor-extrinsic features, including microenvironmental configuration, also have prognostic significance and further expand the list of tumor-defining variables. A better understanding of the features underlying heterogeneity, as well as of the mechanisms and consequences of their interactions, is essential to improve targeting of existing therapies and to develop novel agents addressing specific combinations of features.

Integrated molecular profiles of invasive breast tumors and ductal carcinoma in situ (DCIS) reveal differential vascular and interleukin signaling

We use an integrated approach to understand breast cancer heterogeneity by modeling mRNA, copy number alterations, microRNAs, and methylation in a pathway context utilizing the pathway recognition algorithm using data integration on genomic models (PARADIGM). We demonstrate that combining mRNA expression and DNA copy number classified the patients in groups that provide the best predictive value with respect to prognosis and identified key molecular and stromal signatures. A chronic inflammatory signature, which promotes the development and/or progression of various epithelial tumors, is uniformly present in all breast cancers. We further demonstrate that within the adaptive immune lineage, the strongest predictor of good outcome is the acquisition of a gene signature that favors a high T-helper 1 (Th1)/cytotoxic T-lymphocyte response at the expense of Th2-driven humoral immunity. Patients who have breast cancer with a basal HER2-negative molecular profile (PDGM2) are characterized by high expression of protumorigenic Th2/humoral-related genes (24-38%) and a low Th1/Th2 ratio. The luminal molecular subtypes are again differentiated by low or high FOXM1 and ERBB4 signaling. We show that the interleukin signaling profiles observed in invasive cancers are absent or weakly expressed in healthy tissue but already prominent in ductal carcinoma in situ, together with ECM and cell-cell adhesion regulating pathways. The most prominent difference between low and high mammographic density in healthy breast tissue by PARADIGM was that of STAT4 signaling. In conclusion, by means of a pathway-based modeling methodology (PARADIGM) integrating different layers of molecular data from whole-tumor samples, we demonstrate that we can stratify immune signatures that predict patient survival.

Signalling pathway for RKIP and Let-7 regulates and predicts metastatic breast cancer

Tumour metastasis suppressors are inhibitors of metastasis but their mechanisms of action are generally not understood. We previously showed that the suppressor Raf kinase inhibitory protein (RKIP) inhibits breast tumour metastasis in part via let-7. Here, we demonstrate an integrated approach combining statistical analysis of breast tumour gene expression data and experimental validation to extend the signalling pathway for RKIP. We show that RKIP inhibits let-7 targets (HMGA2, BACH1) that in turn upregulate bone metastasis genes (MMP1, OPN, CXCR4). Our results reveal BACH1 as a novel let-7-regulated transcription factor that induces matrix metalloproteinase1 (MMP1) expression and promotes metastasis. An RKIP pathway metastasis signature (designated RPMS) derived from the complete signalling cascade predicts high metastatic risk better than the individual genes. These results highlight a powerful approach for identifying signalling pathways downstream of a key metastasis suppressor and indicate that analysis of genes in the context of their signalling environment is critical for understanding their predictive and therapeutic potential.

A Parallel Study of mRNA and microRNA Profiling of Peripheral Blood in Young Adult Women

BACKGROUND

Aging is a complex process that involves the interplay of genetic, epigenetic, and environmental factors. Identifying aging-related biomarkers holds great potential for improving our understanding of complex physiological changes, thereby providing a means to investigate the mechanism by which aging influences various diseases.

METHOD AND RESULTS

We performed a parallel study of microRNA and gene expression profiling of peripheral blood in a group of healthy young adult women, among which 13 were aged 22-25 and 9 were aged 36-39 years old. We identified a significantly distinct pattern of microRNA, but not gene expression profiling, between these two young adult women groups. We also performed correlation analysis of expression levels between all pairs of age-associated microRNAs and genes and identified a weak global correlation between these two types of expression levels. A significant involvement of estrogen regulation was observed by pathway analysis of the most differentially expressed microRNAs that included miR-155, -18a, -142, -340, -363, -195, and -24.

CONCLUSION

Our results suggest that the change in global microRNA expression in the peripheral blood is associated with normal aging in young adult women. This change may precede global gene expression changes. Future studies are needed to investigate the regulatory mechanism of the estrogen-related microRNAs and associated diseases.

Divide and conquer: the genetic basis of molecular subclassification of breast cancer

Since the luminal B tumours are associated with poor recurrence-free and disease-specific survivals in all adjuvant systemic treatment categories including hormone therapy, the identification of specific signalling pathways driving luminal B biology is paramount to improve treatment. Sircoulomb et al. and Holland et al. have independently identified the ZNF703 gene, located in chromosomal region 8p12, as preferentially amplified in luminal B tumours.

Analyzing mRNA and microRNA co-expression profiles to identify pathways and their potential regulators in ER+ and ER- breast tumors

Transcription factors and microRNAs are both considered pivotal regulators of gene expression. Numerous computational methods have been developed to predict their targets. These methods, although powerful, provide a static snapshot of how genes may be regulated by transcription factors and microRNAs. We propose a method that combines these prediction data with co-expression analysis and a supervised learning algorithm to determine the main regulators in different pathways of ER+ and ER- tumors.