Nathalie Nicot

Interplay of microRNAs, transcription factors and target genes: linking dynamic expression changes to function

MicroRNAs (miRNAs) are ubiquitously expressed small non-coding RNAs that, in most cases, negatively regulate gene expression at the post-transcriptional level. miRNAs are involved in fine-tuning fundamental cellular processes such as proliferation, cell death and cell cycle control and are believed to confer robustness to biological responses. Here, we investigated simultaneously the transcriptional changes of miRNA and mRNA expression levels over time after activation of the Janus kinase/Signal transducer and activator of transcription (Jak/STAT) pathway by interferon-γ stimulation of melanoma cells. To examine global miRNA and mRNA expression patterns, time-series microarray data were analysed. We observed delayed responses of miRNAs (after 24–48 h) with respect to mRNAs (12–24 h) and identified biological functions involved at each step of the cellular response. Inference of the upstream regulators allowed for identification of transcriptional regulators involved in cellular reactions to interferon-γ stimulation. Linking expression profiles of transcriptional regulators and miRNAs with their annotated functions, we demonstrate the dynamic interplay of miRNAs and upstream regulators with biological functions. Finally, our data revealed network motifs in the form of feed-forward loops involving transcriptional regulators, mRNAs and miRNAs. Additional information obtained from integrating time-series mRNA and miRNA data may represent an important step towards understanding the regulatory principles of gene expression.

The acquisition of resistance to TNFα in breast cancer cells is associated with constitutive activation of autophagy as revealed by a transcriptome analysis using a custom microarray

While the autophagic process is mainly regulated at the post-translational level, a growing body of evidence suggests that autophagy might also be regulated at the transcriptional level. The identification of transcription factors involved in the regulation of autophagy genes has provided compelling evidence for such regulation. In this context, a powerful high throughput analysis tool to simultaneously monitor the expression level of autophagy genes is urgently needed. Here we describe setting up the first comprehensive human autophagy database (HADb, available at www.autophagy.lu) and the development of a companion Human Autophagy-dedicated cDNA Microarray which comprises 234 genes involved in or related to autophagy. The autophagy microarray tool used on breast adenocarcinoma MCF-7 cell line allowed the identification of 47 differentially expressed autophagy genes associated with the acquisition of resistance to the cytotoxic effect of TNFα. The autophagy-core machinery genes DRAM (Damage-Regulated Autophagy Modulator), BNIP3L (BCL2/adenovirus E1B 19 kDa interacting protein 3-like), BECN1 (Beclin 1), GABARAP (Gamma-AminoButyric Acid Receptor-Associated Protein) and UVRAG (UV radiation resistance associated gene) were found upregulated in TNF-resistant cells, suggesting a constitutive activation of the autophagy machinery in these cells. More interestingly, we identified NPC1 as the most upregulated genes in TNF-resistant compared to TNF-sensitive MCF-7 cells, suggesting a relation between the intracellular transport of cholesterol, the regulation of autophagy and NPC1 expression in TNF-resistant tumor cells. In conclusion, we describe here new tools that may help investigating autophagy gene regulation in various cellular models and diseases.

An essential role of syntaxin 3 protein for granule exocytosis and secretion of IL‐1α, IL‐1β, IL‐12b, and CCL4 from differentiated HL‐60 cells

Besides their roles in the killing of pathogens, neutrophils have the capacity to package a variety of cytokines into cytoplasmic granules for subsequent release upon inflammatory conditions. Because the rapid secretion of cytokines orchestrates the action of other immune cells at the infection site and thus, can contribute to the development and chronicity of inflammatory diseases, we aimed to determine the intracellular SNARE machinery responsible for the regulation of cytokine secretion and degranulation. From a constructed gene‐expression network, we first selected relevant cytokines for functional validation by the CBA approach. We established a cytokine‐secretion profile for human neutrophils and dHL‐60 cells, underlining their similar ability to secrete a broad variety of cytokines within proinflammatory conditions mimicked by LPS stimulation. Secondly, after screening of SNARE genes by microarray experiments, we selected STX3 for further functional studies. With the use of a siRNA strategy, we show that STX3 is clearly required for the maximal release of IL‐1α, IL‐1β, IL‐12b, and CCL4 without alteration of other cytokine secretion in dHL‐60 cells. In addition, we demonstrate that STX3 is involved in MMP‐9 exocytosis from gelatinase granules, where STX3 is partly localized. Our results suggest that the secretion of IL‐1α, IL‐1β, IL‐12b, and CCL4 occurs during gelatinase degranulation, a process controlled by STX3. In summary, these findings provide first evidence that STX3 has an essential role in trafficking pathways of cytokines in neutrophil granulocytes.

RNA sequencing and transcriptome arrays analyses show opposing results for alternative splicing in patient derived samples

BackgroundRNA sequencing (RNA-seq) and microarrays are two transcriptomics techniques aimed at the quantification of transcribed genes and their isoforms. Here we compare the latest Affymetrix HTA 2.0 microarray with Illumina 2000 RNA-seq for the analysis of patient samples - normal lung epithelium tissue and squamous cell carcinoma lung tumours. Protein coding mRNAs and long non-coding RNAs (lncRNAs) were included in the study.ResultsBoth platforms performed equally well for protein-coding RNAs, however the stochastic variability was higher for the sequencing data than for microarrays. This reduced the number of differentially expressed genes and genes with predictive potential for RNA-seq compared to microarray data. Analysis of this variability revealed a lack of reads for short and low abundant genes; lncRNAs, being shorter and less abundant RNAs, were found especially susceptible to this issue. A major difference between the two platforms was uncovered by analysis of alternatively spliced genes. Investigation of differential exon abundance showed insufficient reads for many exons and exon junctions in RNA-seq while the detection on the array platform was more stable. Nevertheless, we identified 207 genes which undergo alternative splicing and were consistently detected by both techniques.ConclusionsDespite the fact that the results of gene expression analysis were highly consistent between Human Transcriptome Arrays and RNA-seq platforms, the analysis of alternative splicing produced discordant results. We concluded that modern microarrays can still outperform sequencing for standard analysis of gene expression in terms of reproducibility and cost.

Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network

BackgroundThe reconstruction of context-specific metabolic models from easily and reliably measurable features such as transcriptomics data will be increasingly important in research and medicine. Current reconstruction methods suffer from high computational effort and arbitrary threshold setting. Moreover, understanding the underlying epigenetic regulation might allow the identification of putative intervention points within metabolic networks. Genes under high regulatory load from multiple enhancers or super-enhancers are known key genes for disease and cell identity. However, their role in regulation of metabolism and their placement within the metabolic networks has not been studied.MethodsHere we present FASTCORMICS, a fast and robust workflow for the creation of high-quality metabolic models from transcriptomics data. FASTCORMICS is devoid of arbitrary parameter settings and due to its low computational demand allows cross-validation assays. Applying FASTCORMICS, we have generated models for 63 primary human cell types from microarray data, revealing significant differences in their metabolic networks.ResultsTo understand the cell type-specific regulation of the alternative metabolic pathways we built multiple models during differentiation of primary human monocytes to macrophages and performed ChIP-Seq experiments for histone H3 K27 acetylation (H3K27ac) to map the active enhancers in macrophages. Focusing on the metabolic genes under high regulatory load from multiple enhancers or super-enhancers, we found these genes to show the most cell type-restricted and abundant expression profiles within their respective pathways. Importantly, the high regulatory load genes are associated to reactions enriched for transport reactions and other pathway entry points, suggesting that they are critical regulatory control points for cell type-specific metabolism.ConclusionsBy integrating metabolic modelling and epigenomic analysis we have identified high regulatory load as a common feature of metabolic genes at pathway entry points such as transporters within the macrophage metabolic network. Analysis of these control points through further integration of metabolic and gene regulatory networks in various contexts could be beneficial in multiple fields from identification of disease intervention strategies to cellular reprogramming.

Crosstalk between different family members: IL27 recapitulates IFNγ responses in HCC cells, but is inhibited by IL6-type cytokines

Interleukin-27 (IL27) is a type-I-cytokine of the IL6/IL12 family predominantly secreted by activated macrophages and dendritic cells. In the liver, IL27 expression was observed to be upregulated in patients with hepatitis B, and sera of hepatocellular carcinoma (HCC) patients contain significantly elevated levels of IL27 compared to healthy controls or patients with hepatitis and/or liver cirrhosis. In this study, we show that IL27 induces STAT1 and STAT3 phosphorylation in 5 HCC lines and 3 different types of non-transformed liver cells. We were especially interested in the relevance of the IL27-induced STAT3 activation in liver cells. Thus, we compared the IL27 responses with those induced by IFNγ (STAT1-dominated response) or IL6-type cytokines (IL6, hyper-IL6 (hy-IL6) or OSM) (STAT3-dominated response) by microarray analysis and find that in HCC cells, IL27 induces an IFNγ-like, STAT1-dependent transcriptional response, but we do not find an effective STAT3-dependent response. Validation experiments corroborate the finding from the microarray evaluation. Interestingly, the availability of STAT1 seems critical in the shaping of the IL27 response, as the siRNA knock-down of STAT1 revealed the ability of IL27 to induce the acute-phase protein γ-fibrinogen, a typical IL6 family characteristic. Moreover, we describe a crosstalk between the signaling of IL6-type cytokines and IL27: responses to the gp130-engaging cytokine IL27 (but not those to IFNs) can be inhibited by IL6-type cytokine pre-stimulation, likely by a SOCS3-mediated mechanism. Thus, IL27 recapitulates IFNγ responses in liver cells, but differs from IFNγ by its sensitivity to SOCS3 inhibition.

Whole transcriptome microarrays identify long non-coding RNAs associated with cardiac hypertrophy.

Long non-coding RNAs (lncRNAs) have recently emerged as a novel group of non-coding RNAs able to regulate gene expression. While their role in cardiac disease is only starting to be understood, their involvement in cardiac hypertrophy is poorly known. We studied the association between lncRNAs and left ventricular hypertrophy using whole transcriptome microarrays. Wild-type mice and mice overexpressing the adenosine A2A receptor were subjected to transverse aortic constriction (TAC) to induce left ventricular hypertrophy. Expression profiles of lncRNAs in the heart were characterized using genome-wide microarrays. An analytical pipeline was specifically developed to extract lncRNA data from microarrays. We identified 2 lncRNAs up-regulated and 3 lncRNAs down-regulated in the hearts of A2A-receptor overexpressing-mice subjected to TAC compared to wild-type mice. Differential expression of these 2 lncRNAs was validated by quantitative PCR. Complete microarray dataset is available at Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/) under the accession number GSE45423. Here, we describe in details the experimental design, microarray performance and analysis.

Bronchial airway gene expression in smokers with lung or head and neck cancer

Cigarette smoking is the major cause of cancers of the respiratory tract, including non‐small cell lung cancer (NSCLC) and head and neck cancer (HNC). In order to better understand carcinogenesis of the lung and upper airways, we have compared the gene expression profiles of tumor‐distant, histologically normal bronchial biopsy specimens obtained from current smokers with NSCLC or HNC (SC, considered as a single group), as well as nonsmokers (NS) and smokers without cancer (SNC). RNA from a total of 97 biopsies was used for gene expression profiling (Affymetrix HG‐U133 Plus 2.0 array). Differentially expressed genes were used to compare NS, SNC, and SC, and functional analysis was carried out using Ingenuity Pathway Analysis (IPA). Smoking‐related cancer of the respiratory tract was found to affect the expression of genes encoding xenobiotic biotransformation proteins, as well as proteins associated with crucial inflammation/immunity pathways and other processes that protect the airway from the chemicals in cigarette smoke or contribute to carcinogenesis. Finally, we used the prediction analysis for microarray (PAM) method to identify gene signatures of cigarette smoking and cancer, and uncovered a 15‐gene signature that distinguished between SNC and SC with an accuracy of 83%. Thus, gene profiling of histologically normal bronchial biopsy specimens provided insight into cigarette‐induced carcinogenesis of the respiratory tract and gene signatures of cancer in smokers.

Insights into ligand stimulation effects on gastro-intestinal stromal tumors signalling

Mutations in KIT or PDGFRA are responsible for >85% of gastrointestinal stromal tumors. The introduction of imatinib in the GIST therapy scheme revolutionized the patient outcome. Unfortunately, the therapy allows the disease stabilization instead of curation. Furthermore the resistance to the inhibitor arises in most cases within two first years of therapy. A thorough investigation of the signalling pathways activated by the major PDGFRA and KIT mutants encountered in the GIST landscape allowed to identify striking differences between the two receptor tyrosine kinases. PDGFRA mutants were not responsive to their ligand, PDGFAA, and displayed a high constitutive kinase activity. In contrast, all KIT mutants retained, in addition to their constitutive activation, the ability to be stimulated by their ligand. Kit mutants displayed a lower intrinsic kinase activity relative to PDGFRA mutants, while the KIT Exon 11 deletion mutant exhibited the highest intrinsic kinase activity among KIT mutants. At the transcriptomic level, the MAPK pathway was established as the most prominent activated pathway, which is commonly up-regulated by all PDGFRA and KIT mutants. Inhibition of this pathway, using the MEK inhibitor PD0325901, reduced the proliferation of GIST primary cells at nanomolar concentrations. Altogether, our data demonstrate the high value of MEK inhibitors for combination therapy in GIST treatment and more importantly the interest of evaluating the SCF expression profile in GIST patients presenting KIT mutations.

The PD‐L1‐ and IL6‐mediated dampening of the IL27/STAT1 anticancer responses are prevented by α‐PD‐L1 or α‐IL6 antibodies

Interleukin‐27 (IL27) is a type‐I cytokine of the IL6/IL12 family and is predominantly secreted by activated macrophages and dendritic cells. We show that IL27 induces STAT factor phosphorylation in cancerous cell lines of different tissue origin. IL27 leads to STAT1 phosphorylation and recapitulates an IFN‐γ‐like response in the microarray analyses, with up‐regulation of genes involved in antiviral defense, antigen presentation, and immune suppression. Like IFN‐γ, IL27 leads to an up‐regulation of TAP2 and MHC‐I proteins, which mediate increased tumor immune clearance. However, both cytokines also upregulate proteins such as PD‐L1 (CD274) and IDO‐1, which are associated with immune escape of cancer. Interestingly, differential expression of these genes was observed within the different cell lines and when comparing IL27 to IFN‐γ. In coculture experiments of hepatocellular carcinoma (HCC) cells with peripheral blood mononuclear cells, pre‐treatment of the HCC cells with IL27 resulted in lowered IL2 production by anti‐CD3/‐CD28 activated T‐lymphocytes. Addition of anti‐PD‐L1 antibody, however, restored IL2 secretion. The levels of other TH1 cytokines were also enhanced or restored upon administration of anti‐PD‐L1. In addition, we show that the suppression of IL27 signaling by IL6‐type cytokine pre‐stimulation—mimicking a situation occurring, for example, in IL6‐secreting tumors or in tumor inflammation–induced cachexia—can be antagonized by antibodies against IL6‐type cytokines or their receptors. Therapeutically, the antitumor effects of IL27 (mediated, e.g., by increased antigen presentation) might thus be increased by combining IL27 with blocking antibodies against PD‐L1 or/and IL6‐type cytokines.