Publications de l’équipe
Année de publication : 2015
NaviCell Web Service for network-based data visualization.
Nucleic acids research : W560-5 : DOI : 10.1093/nar/gkv450 En savoir plusRésumé
Data visualization is an essential element of biological research, required for obtaining insights and formulating new hypotheses on mechanisms of health and disease. NaviCell Web Service is a tool for network-based visualization of ‘omics’ data which implements several data visual representation methods and utilities for combining them together. NaviCell Web Service uses Google Maps and semantic zooming to browse large biological network maps, represented in various formats, together with different types of the molecular data mapped on top of them. For achieving this, the tool provides standard heatmaps, barplots and glyphs as well as the novel map staining technique for grasping large-scale trends in numerical values (such as whole transcriptome) projected onto a pathway map. The web service provides a server mode, which allows automating visualization tasks and retrieving data from maps via RESTful (standard HTTP) calls. Bindings to different programming languages are provided (Python and R). We illustrate the purpose of the tool with several case studies using pathway maps created by different research groups, in which data visualization provides new insights into molecular mechanisms involved in systemic diseases such as cancer and neurodegenerative diseases.
ReplierThe shortest path is not the one you know: application of biological network resources in precision oncology research.
Mutagenesis : 191-204 : DOI : 10.1093/mutage/geu078 En savoir plusRésumé
Several decades of molecular biology research have delivered a wealth of detailed descriptions of molecular interactions in normal and tumour cells. This knowledge has been functionally organised and assembled into dedicated biological pathway resources that serve as an invaluable tool, not only for structuring the information about molecular interactions but also for making it available for biological, clinical and computational studies. With the advent of high-throughput molecular profiling of tumours, close to complete molecular catalogues of mutations, gene expression and epigenetic modifications are available and require adequate interpretation. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular profiles of tumours. Making sense out of these descriptions requires biological pathway resources for functional interpretation of the data. In this review, we describe the available biological pathway resources, their characteristics in terms of construction mode, focus, aims and paradigms of biological knowledge representation. We present a new resource that is focused on cancer-related signalling, the Atlas of Cancer Signalling Networks. We briefly discuss current approaches for data integration, visualisation and analysis, using biological networks, such as pathway scoring, guilt-by-association and network propagation. Finally, we illustrate with several examples the added value of data interpretation in the context of biological networks and demonstrate that it may help in analysis of high-throughput data like mutation, gene expression or small interfering RNA screening and can guide in patients stratification. Finally, we discuss perspectives for improving precision medicine using biological network resources and tools. Taking into account the information about biological signalling machinery in cells may help to better interpret molecular patterns of tumours and enable to put precision oncology into general clinical practice.
ReplierAnnée de publication : 2014
Multi-factor data normalization enables the detection of copy number aberrations in amplicon sequencing data.
Bioinformatics (Oxford, England) : 3443-50 : DOI : 10.1093/bioinformatics/btu436 En savoir plusRésumé
Because of its low cost, amplicon sequencing, also known as ultra-deep targeted sequencing, is now becoming widely used in oncology for detection of actionable mutations, i.e. mutations influencing cell sensitivity to targeted therapies. Amplicon sequencing is based on the polymerase chain reaction amplification of the regions of interest, a process that considerably distorts the information on copy numbers initially present in the tumor DNA. Therefore, additional experiments such as single nucleotide polymorphism (SNP) or comparative genomic hybridization (CGH) arrays often complement amplicon sequencing in clinics to identify copy number status of genes whose amplification or deletion has direct consequences on the efficacy of a particular cancer treatment. So far, there has been no proven method to extract the information on gene copy number aberrations based solely on amplicon sequencing.
Replier[Biological network modelling and precision medicine in oncology].
Bulletin du cancer : S18-21 : DOI : 10.1684/bdc.2014.1973 En savoir plusRésumé
Precision medicine in oncology is becoming reality thanks to the next-generation sequencing of tumours and the development of targeted inhibitors enabling tailored therapies. Many clinical trials base their strategy on the identification of mutations to deliver the targeted inhibitor that counteract supposedly the effect of a mutated gene. Recent results have shown that this gene-centered strategy can be successful, but can also fall short in stopping progression. This is due to the many compensation mechanisms, cross-talks and feedback loops that enable the tumoral cell to escape treatment. Taking into account the regulatory network is necessary to establish which inhibitor or combination of inhibitors would achieve the best therapeutic results. Mathematical modelling of biological networks, together with high-quality pathway databases collecting our knowledge of the molecular circuitry of normal and tumoral cells, hold the hopes of an enhanced future for precision medicine in oncology.
ReplierBioinformatics for precision medicine in oncology: principles and application to the SHIVA clinical trial.
Frontiers in genetics : 152 : DOI : 10.3389/fgene.2014.00152 En savoir plusRésumé
Precision medicine (PM) requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of (i) warranting the integration and the traceability of data, (ii) ensuring the correct processing and analyses of genomic data, and (iii) applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application.
ReplierConcomitant Notch activation and p53 deletion trigger epithelial-to-mesenchymal transition and metastasis in mouse gut.
Nature communications : 5005 : DOI : 10.1038/ncomms6005 En savoir plusRésumé
Epithelial-to-mesenchymal transition-like (EMT-like) is a critical process allowing initiation of metastases during tumour progression. Here, to investigate its role in intestinal cancer, we combine computational network-based and experimental approaches to create a mouse model with high metastatic potential. Construction and analysis of this network map depicting molecular mechanisms of EMT regulation based on the literature suggests that Notch activation and p53 deletion have a synergistic effect in activating EMT-like processes. To confirm this prediction, we generate transgenic mice by conditionally activating the Notch1 receptor and deleting p53 in the digestive epithelium (NICD/p53(-/-)). These mice develop metastatic tumours with high penetrance. Using GFP lineage tracing, we identify single malignant cells with mesenchymal features in primary and metastatic tumours in vivo. The development of such a model that recapitulates the cellular features observed in invasive human colorectal tumours is appealing for innovative drug discovery.
ReplierSequence profiling of the Saccharomyces cerevisiae genome permits deconvolution of unique and multialigned reads for variant detection.
G3 (Bethesda, Md.) : 707-15 : DOI : 10.1534/g3.113.009464 En savoir plusRésumé
Advances in high-throughput sequencing (HTS) technologies have accelerated our knowledge of genomes in hundreds of organisms, but the presence of repetitions found in every genome raises challenges to unambiguously map short reads. In particular, short polymorphic reads that are multialigned hinder our capacity to detect mutations. Here, we present two complementary bioinformatics strategies to perform more robust analyses of genome content and sequencing data, validated by use of the Saccharomyces cerevisiae fully sequenced genome. First, we created an annotated HTS profile for the reference genome, based on the production of virtual HTS reads. Using variable read lengths and different numbers of mismatches, we found that 35 nt-reads, with a maximum of 6 mismatches, targets 89.5% of the genome to unique (U) regions. Longer reads consisting of 50-100 nt provided little additional benefits on the U regions extent. Second, to analyze the remaining multialigned (M) regions, we identified the intragenomic single-nucleotide variants and thus defined the unique (MU) and multialigned (MM) subregions, as exemplified for the polymorphic copies of the six flocculation genes and the 50 Ty retrotransposons. As a resource, the coordinates of the U and M regions of the yeast genome have been added to the Saccharomyces Genome Database (www.yeastgenome.org). The benefit of this advanced method of genome annotation was confirmed by our ability to identify acquired single nucleotide polymorphisms in the U and M regions of an experimentally sequenced variant wild-type yeast strain.
ReplierAnnée de publication : 2013
Stability-based comparison of class discovery methods for DNA copy number profiles.
PloS one : e81458 : DOI : 10.1371/journal.pone.0081458 En savoir plusRésumé
Array-CGH can be used to determine DNA copy number, imbalances in which are a fundamental factor in the genesis and progression of tumors. The discovery of classes with similar patterns of array-CGH profiles therefore adds to our understanding of cancer and the treatment of patients. Various input data representations for array-CGH, dissimilarity measures between tumor samples and clustering algorithms may be used for this purpose. The choice between procedures is often difficult. An evaluation procedure is therefore required to select the best class discovery method (combination of one input data representation, one dissimilarity measure and one clustering algorithm) for array-CGH. Robustness of the resulting classes is a common requirement, but no stability-based comparison of class discovery methods for array-CGH profiles has ever been reported.
ReplierSynthetic lethality between gene defects affecting a single non-essential molecular pathway with reversible steps.
PLoS computational biology : e1003016 : DOI : 10.1371/journal.pcbi.1003016 En savoir plusRésumé
Systematic analysis of synthetic lethality (SL) constitutes a critical tool for systems biology to decipher molecular pathways. The most accepted mechanistic explanation of SL is that the two genes function in parallel, mutually compensatory pathways, known as between-pathway SL. However, recent genome-wide analyses in yeast identified a significant number of within-pathway negative genetic interactions. The molecular mechanisms leading to within-pathway SL are not fully understood. Here, we propose a novel mechanism leading to within-pathway SL involving two genes functioning in a single non-essential pathway. This type of SL termed within-reversible-pathway SL involves reversible pathway steps, catalyzed by different enzymes in the forward and backward directions, and kinetic trapping of a potentially toxic intermediate. Experimental data with recombinational DNA repair genes validate the concept. Mathematical modeling recapitulates the possibility of kinetic trapping and revealed the potential contributions of synthetic, dosage-lethal interactions in such a genetic system as well as the possibility of within-pathway positive masking interactions. Analysis of yeast gene interaction and pathway data suggests broad applicability of this novel concept. These observations extend the canonical interpretation of synthetic-lethal or synthetic-sick interactions with direct implications to reconstruct molecular pathways and improve therapeutic approaches to diseases such as cancer.
ReplierRNAi-dependent and independent control of LINE1 accumulation and mobility in mouse embryonic stem cells.
PLoS genetics : e1003791 : DOI : 10.1371/journal.pgen.1003791 En savoir plusRésumé
In most mouse tissues, long-interspersed elements-1 (L1s) are silenced via methylation of their 5′-untranslated regions (5′-UTR). A gradual loss-of-methylation in pre-implantation embryos coincides with L1 retrotransposition in blastocysts, generating potentially harmful mutations. Here, we show that Dicer- and Ago2-dependent RNAi restricts L1 accumulation and retrotransposition in undifferentiated mouse embryonic stem cells (mESCs), derived from blastocysts. RNAi correlates with production of Dicer-dependent 22-nt small RNAs mapping to overlapping sense/antisense transcripts produced from the L1 5′-UTR. However, RNA-surveillance pathways simultaneously degrade these transcripts and, consequently, confound the anti-L1 RNAi response. In Dicer(-/-) mESC complementation experiments involving ectopic Dicer expression, L1 silencing was rescued in cells in which microRNAs remained strongly depleted. Furthermore, these cells proliferated and differentiated normally, unlike their non-complemented counterparts. These results shed new light on L1 biology, uncover defensive, in addition to regulatory roles for RNAi, and raise questions on the differentiation defects of Dicer(-/-) mESCs.
ReplierNaviCell: a web-based environment for navigation, curation and maintenance of large molecular interaction maps.
BMC systems biology : 100 : DOI : 10.1186/1752-0509-7-100 En savoir plusRésumé
Molecular biology knowledge can be formalized and systematically represented in a computer-readable form as a comprehensive map of molecular interactions. There exist an increasing number of maps of molecular interactions containing detailed and step-wise description of various cell mechanisms. It is difficult to explore these large maps, to organize discussion of their content and to maintain them. Several efforts were recently made to combine these capabilities together in one environment, and NaviCell is one of them.
ReplierHMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data.
Bioinformatics (Oxford, England) : 2979-86 : DOI : 10.1093/bioinformatics/btt524 En savoir plusRésumé
Cancer cells are often characterized by epigenetic changes, which include aberrant histone modifications. In particular, local or regional epigenetic silencing is a common mechanism in cancer for silencing expression of tumor suppressor genes. Though several tools have been created to enable detection of histone marks in ChIP-seq data from normal samples, it is unclear whether these tools can be efficiently applied to ChIP-seq data generated from cancer samples. Indeed, cancer genomes are often characterized by frequent copy number alterations: gains and losses of large regions of chromosomal material. Copy number alterations may create a substantial statistical bias in the evaluation of histone mark signal enrichment and result in underdetection of the signal in the regions of loss and overdetection of the signal in the regions of gain.
ReplierBreakpoint features of genomic rearrangements in neuroblastoma with unbalanced translocations and chromothripsis.
PloS one : e72182 : DOI : 10.1371/journal.pone.0072182 En savoir plusRésumé
Neuroblastoma is a pediatric cancer of the peripheral nervous system in which structural chromosome aberrations are emblematic of aggressive tumors. In this study, we performed an in-depth analysis of somatic rearrangements in two neuroblastoma cell lines and two primary tumors using paired-end sequencing of mate-pair libraries and RNA-seq. The cell lines presented with typical genetic alterations of neuroblastoma and the two tumors belong to the group of neuroblastoma exhibiting a profile of chromothripsis. Inter and intra-chromosomal rearrangements were identified in the four samples, allowing in particular characterization of unbalanced translocations at high resolution. Using complementary experiments, we further characterized 51 rearrangements at the base pair resolution that revealed 59 DNA junctions. In a subset of cases, complex rearrangements were observed with templated insertion of fragments of nearby sequences. Although we did not identify known particular motifs in the local environment of the breakpoints, we documented frequent microhomologies at the junctions in both chromothripsis and non-chromothripsis associated breakpoints. RNA-seq experiments confirmed expression of several predicted chimeric genes and genes with disrupted exon structure including ALK, NBAS, FHIT, PTPRD and ODZ4. Our study therefore indicates that both non-homologous end joining-mediated repair and replicative processes may account for genomic rearrangements in neuroblastoma. RNA-seq analysis allows the identification of the subset of abnormal transcripts expressed from genomic rearrangements that may be involved in neuroblastoma oncogenesis.
ReplierStreamlined ion torrent PGM-based diagnostics: BRCA1 and BRCA2 genes as a model.
European journal of human genetics : EJHG : 535-41 : DOI : 10.1038/ejhg.2013.181 En savoir plusRésumé
To meet challenges in terms of throughput and turnaround time, many diagnostic laboratories are shifting from Sanger sequencing to higher throughput next-generation sequencing (NGS) platforms. Bearing in mind that the performance and quality criteria expected from NGS in diagnostic or research settings are strikingly different, we have developed an Ion Torrent’s PGM-based routine diagnostic procedure for BRCA1/2 sequencing. The procedure was first tested on a training set of 62 control samples, and then blindly validated on 77 samples in parallel with our routine technique. The training set was composed of difficult cases, for example, insertions and/or deletions of various sizes, large-scale rearrangements and, obviously, mutations occurring in homopolymer regions. We also compared two bioinformatic solutions in this diagnostic context, an in-house academic pipeline and the commercially available NextGene software (Softgenetics). NextGene analysis provided higher sensitivity, as four previously undetected single-nucleotide variations were found. Regarding specificity, an average of 1.5 confirmatory Sanger sequencings per patient was needed for complete BRCA1/2 screening. Large-scale rearrangements were identified by two distinct analyses, that is, bioinformatics and fragment analysis with electrophoresis profile comparison. Turnaround time was enhanced, as a series of 30 patients were sequenced by one technician, making the results available for the clinician in 10 working days following blood sampling. BRCA1/2 genes are a good model, representative of the difficulties commonly encountered in diagnostic settings, which is why we believe our findings are of interest for the whole community, and the pipeline described can be adapted by any user of PGM for diagnostic purposes.
ReplierSystems biology of Ewing sarcoma: a network model of EWS-FLI1 effect on proliferation and apoptosis.
Nucleic acids research : 8853-71 : DOI : 10.1093/nar/gkt678 En savoir plusRésumé
Ewing sarcoma is the second most frequent pediatric bone tumor. In most of the patients, a chromosomal translocation leads to the expression of the EWS-FLI1 chimeric transcription factor that is the major oncogene in this pathology. Relative genetic simplicity of Ewing sarcoma makes it particularly attractive for studying cancer in a systemic manner. Silencing EWS-FLI1 induces cell cycle alteration and ultimately leads to apoptosis, but the exact molecular mechanisms underlying this phenotype are unclear. In this study, a network linking EWS-FLI1 to cell cycle and apoptosis phenotypes was constructed through an original method of network reconstruction. Transcriptome time-series after EWS-FLI1 silencing were used to identify core modulated genes by an original scoring method based on fitting expression profile dynamics curves. Literature data mining was then used to connect these modulated genes into a network. The validity of a subpart of this network was assessed by siRNA/RT-QPCR experiments on four additional Ewing cell lines and confirmed most of the links. Based on the network and the transcriptome data, CUL1 was identified as a new potential target of EWS-FLI1. Altogether, using an original methodology of data integration, we provide the first version of EWS-FLI1 network model of cell cycle and apoptosis regulation.
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