Coordinated regulation of WNT/ß-catenin, c-Met, and integrin signalling pathways by miR-193b controls triple negative breast cancer metastatic traits.

BACKGROUND: Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). Treatment options for TNBC patients are limited and further insights into disease aetiology are needed to develop better therapeutic approaches. microRNAs' ability to regulate multiple targets could hold a promising discovery approach to pathways relevant for TNBC aggressiveness. Thus, we address the role of miRNAs in controlling three signalling pathways relevant to the biology of TNBC, and their downstream phenotypes. METHODS: To identify miRNAs regulating WNT/ß-catenin, c-Met, and integrin signalling pathways, we performed a high-throughput targeted proteomic approach, investigating the effect of 800 miRNAs on the expression of 62 proteins in the MDA-MB-231 TNBC cell line. We then developed a novel network analysis, Pathway Coregulatory (PC) score, to detect miRNAs regulating these three pathways. Using in vitro assays for cell growth, migration, apoptosis, and stem-cell content, we validated the function of candidate miRNAs. Bioinformatic analyses using BC patients' datasets were employed to assess expression of miRNAs as well as their pathological relevance in TNBC patients. RESULTS: We identified six candidate miRNAs coordinately regulating the three signalling pathways. Quantifying cell growth of three TNBC cell lines upon miRNA gain-of-function experiments, we characterised miR-193b as a strong and consistent repressor of proliferation. Importantly, the effects of miR-193b were stronger than chemical inhibition of the individual pathways. We further demonstrated that miR-193b induced apoptosis, repressed migration, and regulated stem-cell markers in MDA-MB-231 cells. Furthermore, miR-193b expression was the lowest in patients classified as TNBC or Basal compared to other subtypes. Gene Set Enrichment Analysis showed that miR-193b expression was significantly associated with reduced activity of WNT/ß-catenin and c-Met signalling pathways in TNBC patients. CONCLUSIONS: Integrating miRNA-mediated effects and protein functions on networks, we show that miRNAs predominantly act in a coordinated fashion to activate or repress connected signalling pathways responsible for metastatic traits in TNBC. We further demonstrate that our top candidate, miR-193b, regulates these phenotypes to an extent stronger than individual pathway inhibition, thus emphasizing that its effect on TNBC aggressiveness is mediated by the coordinated repression of these functionally interconnected pathways.

Genome-Wide Analysis of the Circulating miRNome After Cerebral Ischemia Reveals a Reperfusion-Induced MicroRNA Cluster.

BACKGROUND AND PURPOSE: Circulating microRNAs (miRNAs) are emerging biomarkers for stroke because of their high stability in the bloodstream and association with pathophysiologic conditions. However, the circulating whole-genome miRNAs (miRNome) has not been characterized comprehensively in the acute phase of stroke. METHODS: We profiled the circulating miRNome in mouse models of acute ischemic and hemorrhagic stroke by next-generation sequencing. Stroke models were compared with sham-operated and naive mice to identify deregulated circulating miRNAs. Top-ranked miRNAs were validated and further characterized by quantitative reverse transcription polymerase chain reaction. RESULTS: We discovered 24 circulating miRNAs with an altered abundance in the circulation 3 hours after ischemia, whereas the circulating miRNome was not altered after intracerebral hemorrhage compared with sham-operated mice. Among the upregulated miRNAs in ischemia, the top-listed miR-1264/1298/448 cluster was strongly dependent on reperfusion in different ischemia models. A time course experiment revealed that the miR-1264/1298/448 cluster peaked in the circulation around 3 hours after reperfusion and gradually decreased thereafter. CONCLUSIONS: Alteration of the miRNome in the circulation is associated with cerebral ischemia/reperfusion, but not hemorrhage, suggesting a potential to serve as biomarkers for reperfusion in the acute phase. The pathophysiological role of reperfusion-inducible miR-1264/1298/448 cluster, which is located on chromosome X within the introns of the serotonin receptor HTR2C, requires further investigation.

Global microRNA level regulation of EGFR-driven cell-cycle protein network in breast cancer.

The EGFR-driven cell-cycle pathway has been extensively studied due to its pivotal role in breast cancer proliferation and pathogenesis. Although several studies reported regulation of individual pathway components by microRNAs (miRNAs), little is known about how miRNAs coordinate the EGFR protein network on a global miRNA (miRNome) level. Here, we combined a large-scale miRNA screening approach with a high-throughput proteomic readout and network-based data analysis to identify which miRNAs are involved, and to uncover potential regulatory patterns. Our results indicated that the regulation of proteins by miRNAs is dominated by the nucleotide matching mechanism between seed sequences of the miRNAs and 3'-UTR of target genes. Furthermore, the novel network-analysis methodology we developed implied the existence of consistent intrinsic regulatory patterns where miRNAs simultaneously co-regulate several proteins acting in the same functional module. Finally, our approach led us to identify and validate three miRNAs (miR-124, miR-147 and miR-193a-3p) as novel tumor suppressors that co-target EGFR-driven cell-cycle network proteins and inhibit cell-cycle progression and proliferation in breast cancer.

Collective Network of Binary Classifier Framework for Polarimetric SAR Image Classification: An Evolutionary Approach.

Terrain classification over polarimetric synthetic aperture radar (SAR) images has been an active research field where several features and classifiers have been proposed up to date. However, some key questions, e.g., 1) how to select certain features so as to achieve highest discrimination over certain classes?, 2) how to combine them in the most effective way?, 3) which distance metric to apply?, 4) how to find the optimal classifier configuration for the classification problem in hand?, 5) how to scale/adapt the classifier if large number of classes/features are present?, and finally, 6) how to train the classifier efficiently to maximize the classification accuracy?, still remain unanswered. In this paper, we propose a collective network of (evolutionary) binary classifier (CNBC) framework to address all these problems and to achieve high classification performance. The CNBC framework adapts a "Divide and Conquer" type approach by allocating several NBCs to discriminate each class and performs evolutionary search to find the optimal BC in each NBC. In such an (incremental) evolution session, the CNBC body can further dynamically adapt itself with each new incoming class/feature set without a full-scale retraining or reconfiguration. Both visual and numerical performance evaluations of the proposed framework over two benchmark SAR images demonstrate its superiority and a significant performance gap against several major classifiers in this field.

RNAi-based validation of antibodies for reverse phase protein arrays.

BACKGROUND: Reverse phase protein arrays (RPPA) have been demonstrated to be a useful experimental platform for quantitative protein profiling in a high-throughput format. Target protein detection relies on the readout obtained from a single detection antibody. For this reason, antibody specificity is a key factor for RPPA. RNAi allows the specific knockdown of a target protein in complex samples and was therefore examined for its utility to assess antibody performance for RPPA applications. RESULTS: To proof the feasibility of our strategy, two different anti-EGFR antibodies were compared by RPPA. Both detected the knockdown of EGFR but at a different rate. Western blot data were used to identify the most reliable antibody. The RNAi approach was also used to characterize commercial anti-STAT3 antibodies. Out of ten tested anti-STAT3 antibodies, four antibodies detected the STAT3-knockdown at 80-85%, and the most sensitive anti-STAT3 antibody was identified by comparing detection limits. Thus, the use of RNAi for RPPA antibody validation was demonstrated to be a stringent approach to identify highly specific and highly sensitive antibodies. Furthermore, the RNAi/RPPA strategy is also useful for the validation of isoform-specific antibodies as shown for the identification of AKT1/AKT2 and CCND1/CCND3-specific antibodies. CONCLUSIONS: RNAi is a valuable tool for the identification of very specific and highly sensitive antibodies, and is therefore especially useful for the validation of RPPA-suitable detection antibodies. On the other hand, when a set of well-characterized RPPA-antibodies is available, large-scale RNAi experiments analyzed by RPPA might deliver useful information for network reconstruction.

Arctic-alpine distributions--metapopulations on a continental scale?

Cold-adapted species in the Northern Hemisphere frequently show arctic-alpine discontinuous ranges at high latitudes and on mountains farther south, but area connectivity through current and historical gene flow remains unclear. We used the coalescent-based program IMa (Isolation with Migration-analytic) to test for migration among disjunct European areas of arctic-alpine wolf spiders of the Pardosa saltuaria group. Mitochondrial (ND1) and nuclear (ITS1, 5.8S rDNA, ITS2) markers were analyzed simultaneously. Gene flow was unidirectional from Scandinavia to the Alps and the Carpathians, complex with respect to intermediate relict areas in central Europe, and very limited in outlying areas in the Balkans and Pyrenees. Population connectivity may have been greater during glacial events that might alternatively account for the inferred arctic-alpine links. A simulation study under various demographic histories (using a new module in the Mesquite package, which models episodic migration) showed that the empirical results are equally consistent with moderate levels of ongoing (continuous) migration or, alternatively, with strong migration bursts at the last glacial maximum but not at earlier times. Habitat connectivity was probably maximal during glacial events, illustrating the potential influence of ecology and life history on organismal responses to past climatic change.

Experimental ischaemic stroke induces transient cardiac atrophy and dysfunction.

BACKGROUND: Stroke can lead to cardiac dysfunction in patients, but the mechanisms underlying the interaction between the injured brain and the heart are poorly understood. The objective of the study is to investigate the effects of experimental murine stroke on cardiac function and molecular signalling in the heart. METHODS AND RESULTS: Mice were subjected to filament-induced left middle cerebral artery occlusion for 30 or 60 min or sham surgery and underwent repetitive micro-echocardiography. Left ventricular contractility was reduced early (24-72 h) but not late (2 months) after brain ischaemia. Cardiac dysfunction was accompanied by a release of high-sensitive cardiac troponin (hsTNT (ng/ml): d1: 7.0 ± 1.0 vs. 25.0 ± 3.2*; d3: 7.3 ± 1.1 vs. 52.2 ± 16.7*; d14: 5.7 ± 0.8 vs. 5.2 ± 0.3; sham vs. 60 min. MCAO; mean ± SEM; *p < 0.05); reduced heart weight (heart weight/tibia length ratio: d1: 6.9 ± 0.2 vs. 6.4 ± 0.1*; d3: 6.7 ± 0.2 vs. 5.8 ± 0.1*; d14: 6.7 ± 0.2 vs. 6.4 ± 03; sham vs. 60 min. MCAO; mean ± SEM; *p < 0.05); resulting from cardiomyocyte atrophy (cardiomyocyte size: d1: 12.8% ± 0.002**; d3: 13.5% ± 0.002**; 14d: 6.3% ± 0.003*; 60 min. MCAO vs. sham; mean ± SEM; **p < 0.01; *p < 0.05), accompanied by increased atrogin-1 and the E3 ubiquitin ligase murf-1. Net norepinephrine but not synthesis was increased, suggesting a reduced norepinephrine release or an increase of norepinephrine re-uptake, resulting in a functional denervation. Transcriptome analysis in cardiac tissue identified the transcription factor peroxisome proliferator-activated receptor gamma as a potential mediator of stroke-induced transcriptional dysregulation involved in cardiac atrophy. CONCLUSIONS: Stroke induces a complex molecular response in the heart muscle with immediate but transient cardiac atrophy and dysfunction.

The miR-644a/CTBP1/p53 axis suppresses drug resistance by simultaneous inhibition of cell survival and epithelial-mesenchymal transition in breast cancer.

Tumor cells develop drug resistance which leads to recurrence and distant metastasis. MicroRNAs are key regulators of tumor pathogenesis; however, little is known whether they can sensitize cells and block metastasis simultaneously. Here, we report miR-644a as a novel inhibitor of both cell survival and EMT whereby acting as pleiotropic therapy-sensitizer in breast cancer. We showed that both miR-644a expression and its gene signature are associated with tumor progression and distant metastasis-free survival. Mechanistically, miR-644a directly targets the transcriptional co-repressor C-Terminal Binding Protein 1 (CTBP1) whose knock-outs by the CRISPR-Cas9 system inhibit tumor growth, metastasis, and drug resistance, mimicking the phenotypes induced by miR-644a. Furthermore, downregulation of CTBP1 by miR-644a upregulates wild type- or mutant-p53 which acts as a 'molecular switch' between G1-arrest and apoptosis by inducing cyclin-dependent kinase inhibitor 1 (p21, CDKN1A, CIP1) or pro-apoptotic phorbol-12-myristate-13-acetate-induced protein 1 (Noxa, PMAIP1), respectively. Interestingly, an increase in mutant-p53 by either overexpression of miR-644a or downregulation of CTBP1 was enough to shift this balance in favor of apoptosis through upregulation of Noxa. Notably, p53-mutant patients, but not p53-wild type ones, with high CTBP1 have a shorter survival suggesting that CTBP1 could be a potential prognostic factor for breast cancer patients with p53 mutations. Overall, re-activation of the miR-644a/CTBP1/p53 axis may represent a new strategy for overcoming both therapy resistance and metastasis.

A network-based method to assess the statistical significance of mild co-regulation effects.

Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences, or microRNAs (miRNAs) and mRNAs. In terms of network biology, such screening approaches primarily attempt to elucidate relations between biological components of two distinct types, which can be represented as edges between nodes in a bipartite graph. However, it is often desirable not only to determine regulatory relationships between nodes of different types, but also to understand the connection patterns of nodes of the same type. Especially interesting is the co-occurrence of two nodes of the same type, i.e., the number of their common neighbours, which current high-throughput screening analysis fails to address. The co-occurrence gives the number of circumstances under which both of the biological components are influenced in the same way. Here we present SICORE, a novel network-based method to detect pairs of nodes with a statistically significant co-occurrence. We first show the stability of the proposed method on artificial data sets: when randomly adding and deleting observations we obtain reliable results even with noise exceeding the expected level in large-scale experiments. Subsequently, we illustrate the viability of the method based on the analysis of a proteomic screening data set to reveal regulatory patterns of human microRNAs targeting proteins in the EGFR-driven cell cycle signalling system. Since statistically significant co-occurrence may indicate functional synergy and the mechanisms underlying canalization, and thus hold promise in drug target identification and therapeutic development, we provide a platform-independent implementation of SICORE with a graphical user interface as a novel tool in the arsenal of high-throughput screening analysis.

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 ß (TGF-ß)-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.

Utilization of RNAi to validate antibodies for reverse phase protein arrays.

Reverse phase protein arrays (RPPAs) emerged as a very useful tool for high-throughput screening of protein expression in large numbers of small specimen. Similar to other protein chemistry methods, antibody specificity is also a major concern for RPPA. Currently, testing antibodies on Western blot for specificity and applying serial dilution curves to determine signal/concentration linearity of RPPA signals are most commonly employed to validate antibodies for RPPA applications. However, even the detection antibodies fulfilling both requirements do not always give the expected result. Chemically synthesized small interfering RNAs (siRNAs) are one of the most promising and time-efficient tools for loss-of-function studies by specifically targeting the gene of interest resulting in a reduction at the protein expression level, and are therefore used to dissect biological processes. Here, we report the utilization of siRNA-treated sample lysates for the quantification of a protein of interest as a useful and reliable tool to validate antibody specificity for RPPAs. As our results indicate, we recommend the use of antibodies which give the highest dynamic range between the control siRNA-treated samples and the target protein (here: EGFR) siRNA-treated ones on RPPAs, to be able to quantify even small differences of protein abundance with high confidence.