The integration of gene and miRNA expression using pathway topology: a case study on Epithelial Ovarian Cancer

Pathways are formal descriptions of the biological processes involving finely regulated structures by which a cell converts molecules or processes signals. The study of gene expression in terms of pathways is defined as pathway analysis and aims at identifying groups of functionally related genes that show coordinated expression changes. Recently, pathway analysis moved from algorithms using merely gene list to ones exploiting the topology that define gene connections. A crucial, and unfortunately limiting step for these novel methods are the availability of the pathways as gene networks in which nodes are genes and edges are the relations between two elements. To this aim, we develop a pathway data interpreter, called graphite, able to uniformly store, process and convert pathway information into gene networks. graphite has been made publicly available as R package within the Bioconductor platform. In the field of the topological pathway analysis, graphite fills the existing gap lying between technical and methodological aspects. graphite i) allows performing more informative analysis on omics data and ii) allows developing new methods based on the increased accessibil- ity of biological knowledge. However, the pathways of the four main public resources integrated into graphite (KEGG, Reactome, Biocarta and PID), still lack of crucial interactors: the microRNAs. The microRNAs are small non-coding RNAs that post-transcriptionally regulate gene expression, their function on the messenger target is repressive but their effect on the transcription is dependent of the topology of the pathway in which the miRNA is involved. In the last decade, many targets have been discovered and experimentally validated, dedicated databases are available providing these information. Thus, I worked on an extension of graphite package able to integrate microRNAs in pathway topology, i) linking the non-coding RNAs to their validated target genes, ii) providing integrated networks suitable for the topological pathway analyses. The feasibility of this approach has been validated on a specific biological context, the early stage of Epithelial Ovarian Cancer (EOC). EOC has long been considered as a single disease. The emerging opinion, however, sees ovarian cancer as a general term that encloses a group of histo-pathological subtypes sharing a common anatomic location. In collaboration with the Mario Negri institute, 257 stage I EOC tumour biopsies were collected and stratified into training and validation sets. miRNA microarray data was used to generate the most highly reproducible signatures for each histotype through a dedicated resampling inferential strategy. qRT- PCR was used to validate the results in both the training and validation set. The results indicate that the clear cell histotype is characterized by high expression levels of miR- 30a and miR-30a*, while mucinous patients by high levels of miR-192 and miR-194, interestingly as well as mucinous non-ovarian tissues. Then, the integrative approach that combines mRNA and miRNA profiles using graphite has been applied to identify the mucinous specific regulatory circuits. Taken together our findings demonstrate that EOC histotypes have discriminant regulatory circuits that drive the differentiation of the tumour environment. Our approach successfully guides us towards important biological results with interesting therapeutic implications in EOC

graphite - a Bioconductor package to convert pathway topology to gene network

BACKGROUND: Gene set analysis is moving towards considering pathway topology as a crucial feature. Pathway elements are complex entities such as protein complexes, gene family members and chemical compounds. The conversion of pathway topology to a gene/protein networks (where nodes are a simple element like a gene/protein) is a critical and challenging task that enables topology-based gene set analyses. Unfortunately, currently available R/Bioconductor packages provide pathway networks only from single databases. They do not propagate signals through chemical compounds and do not differentiate between complexes and gene families. RESULTS: Here we present graphite, a Bioconductor package addressing these issues. Pathway information from four different databases is interpreted following specific biologically-driven rules that allow the reconstruction of gene-gene networks taking into account protein complexes, gene families and sensibly removing chemical compounds from the final graphs. The resulting networks represent a uniform resource for pathway analyses. Indeed, graphite provides easy access to three recently proposed topological methods. The graphite package is available as part of the Bioconductor software suite. CONCLUSIONS: graphite is an innovative package able to gather and make easily available the contents of the four major pathway databases. In the field of topological analysis graphite acts as a provider of biological information by reducing the pathway complexity considering the biological meaning of the pathway elements

Editorial : Multi-omic Data Integration in Oncology

Non peer reviewe

Meta-analysis of expression signatures of muscle atrophy: gene interaction networks in early and late stages

<p>Abstract</p> <p>Background</p> <p>Skeletal muscle mass can be markedly reduced through a process called atrophy, as a consequence of many diseases or critical physiological and environmental situations. Atrophy is characterised by loss of contractile proteins and reduction of fiber volume. Although in the last decade the molecular aspects underlying muscle atrophy have received increased attention, the fine mechanisms controlling muscle degeneration are still incomplete. In this study we applied meta-analysis on gene expression signatures pertaining to different types of muscle atrophy for the identification of novel key regulatory signals implicated in these degenerative processes.</p> <p>Results</p> <p>We found a general down-regulation of genes involved in energy production and carbohydrate metabolism and up-regulation of genes for protein degradation and catabolism. Six functional pathways occupy central positions in the molecular network obtained by the integration of atrophy transcriptome and molecular interaction data. They are TGF-β pathway, apoptosis, membrane trafficking/cytoskeleton organization, NFKB pathways, inflammation and reorganization of the extracellular matrix. Protein degradation pathway is evident only in the network specific for muscle short-term response to atrophy. TGF-β pathway plays a central role with proteins SMAD3/4, MYC, MAX and CDKN1A in the general network, and JUN, MYC, GNB2L1/RACK1 in the short-term muscle response network.</p> <p>Conclusion</p> <p>Our study offers a general overview of the molecular pathways and cellular processes regulating the establishment and maintenance of atrophic state in skeletal muscle, showing also how the different pathways are interconnected. This analysis identifies novel key factors that could be further investigated as potential targets for the development of therapeutic treatments. We suggest that the transcription factors SMAD3/4, GNB2L1/RACK1, MYC, MAX and JUN, whose functions have been extensively studied in tumours but only marginally in muscle, appear instead to play important roles in regulating muscle response to atrophy.</p

Filling gaps in PPAR-alpha signaling through comparative nutrigenomics analysis

<p>Abstract</p> <p>Background</p> <p>The application of high-throughput genomic tools in nutrition research is a widespread practice. However, it is becoming increasingly clear that the outcome of individual expression studies is insufficient for the comprehensive understanding of such a complex field. Currently, the availability of the large amounts of expression data in public repositories has opened up new challenges on microarray data analyses. We have focused on PPARα, a ligand-activated transcription factor functioning as fatty acid sensor controlling the gene expression regulation of a large set of genes in various metabolic organs such as liver, small intestine or heart. The function of PPARα is strictly connected to the function of its target genes and, although many of these have already been identified, major elements of its physiological function remain to be uncovered. To further investigate the function of PPARα, we have applied a cross-species meta-analysis approach to integrate sixteen microarray datasets studying high fat diet and PPARα signal perturbations in different organisms.</p> <p>Results</p> <p>We identified 164 genes (MDEGs) that were differentially expressed in a constant way in response to a high fat diet or to perturbations in PPARs signalling. In particular, we found five genes in yeast which were highly conserved and homologous of PPARα targets in mammals, potential candidates to be used as models for the equivalent mammalian genes. Moreover, a screening of the MDEGs for all known transcription factor binding sites and the comparison with a human genome-wide screening of Peroxisome Proliferating Response Elements (PPRE), enabled us to identify, 20 new potential candidate genes that show, both binding site, both change in expression in the condition studied. Lastly, we found a non random localization of the differentially expressed genes in the genome.</p> <p>Conclusion</p> <p>The results presented are potentially of great interest to resume the currently available expression data, exploiting the power of <it>in silico </it>analysis filtered by evolutionary conservation. The analysis enabled us to indicate potential gene candidates that could fill in the gaps with regards to the signalling of PPARα and, moreover, the non-random localization of the differentially expressed genes in the genome, suggest that epigenetic mechanisms are of importance in the regulation of the transcription operated by PPARα.</p

Transcriptome Profiles of Human Visceral Adipocytes in Obesity and Colorectal Cancer Unravel the Effects of Body Mass Index and Polyunsaturated Fatty Acids on Genes and Biological Processes Related to Tumorigenesis

Obesity, a low-grade inflammatory condition, represents a major risk factor for the development of several pathologies including colorectal cancer (CRC). Although the adipose tissue inflammatory state is now recognized as a key player in obesity-associated morbidities, the underlying biological processes are complex and not yet precisely defined. To this end, we analyzed transcriptome profiles of human visceral adipocytes from lean and obese subjects affected or not by CRC by RNA sequencing (n = 6 subjects/category), and validated selected modulated genes by real-time qPCR. We report that obesity and CRC, conditions characterized by the common denominator of inflammation, promote changes in the transcriptional program of adipocytes mostly involving pathways and biological processes linked to extracellular matrix remodeling, and metabolism of pyruvate, lipids and glucose. Interestingly, although the transcriptome of adipocytes shows several alterations that are common to both disorders, some modifications are unique under obesity (e.g., pathways associated with inflammation) and CRC (e.g., TGFβ signaling and extracellular matrix remodeling) and are influenced by the body mass index (e.g., processes related to cell adhesion, angiogenesis, as well as metabolism). Indeed, cancer-induced transcriptional program is deeply affected by obesity, with adipocytes from obese individuals exhibiting a more complex response to the tumor. We also report that in vitro exposure of adipocytes to ω3 and ω6 polyunsaturated fatty acids (PUFA) endowed with either anti- or pro-inflammatory properties, respectively, modulates the expression of genes involved in processes potentially relevant to carcinogenesis, as assessed by real-time qPCR. All together our results suggest that genes involved in pyruvate, glucose and lipid metabolism, fibrosis and inflammation are central in the transcriptional reprogramming of adipocytes occurring in obese and CRC-affected individuals, as well as in their response to PUFA exposure. Moreover, our results indicate that the transcriptional program of adipocytes is strongly influenced by the BMI status in CRC subjects. The dysregulation of these interrelated processes relevant for adipocyte functions may contribute to create more favorable conditions to tumor establishment or favor tumor progression, thus linking obesity and colorectal cancer

The Biological Connection Markup Language: a SBGN-compliant format for visualization, filtering and analysis of biological pathways

Motivation: Many models and analysis of signaling pathways have been proposed. However, neither of them takes into account that a biological pathway is not a fixed system, but instead it depends on the organism, tissue and cell type as well as on physiological, pathological and experimental conditions

KrillDB: A de novo transcriptome database for the Antarctic krill (Euphausia superba)

© 2017 Sales et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Antarctic krill (Euphausia superba) is a key species in the Southern Ocean with an estimated biomass between 100 and 500 million tonnes. Changes in krill population viability would have catastrophic effect on the Antarctic ecosystem. One looming threat due to elevated levels of anthropogenic atmospheric carbon dioxide (CO2) is ocean acidification (lowering of sea water pH by CO2 dissolving into the oceans). The genetics of Antarctic krill has long been of scientific interest for both for the analysis of population structure and analysis of functional genetics. However, the genetic resources available for the species are relatively modest. We have developed the most advanced genetic database on Euphausia superba, KrillDB, which includes comprehensive data sets of former and present transcriptome projects. In particular, we have built a de novo transcriptome assembly using more than 360 million Illumina sequence reads generated from larval krill including individuals subjected to different CO2levels. The database gives access to: 1) the full list of assembled genes and transcripts; 2) their level of similarity to transcripts and proteins from other species; 3) the predicted protein domains contained within each transcript; 4) their predicted GO terms; 5) the level of expression of each transcript in the different larval stages and CO2treatments. All references to external entities (sequences, domains, GO terms) are equipped with a link to the appropriate source database. Moreover, the software implements a full-text search engine that makes it possible to submit free-form queries. KrillDB represents the first largescale attempt at classifying and annotating the full krill transcriptome. For this reason, we believe it will constitute a cornerstone of future approaches devoted to physiological and molecular study of this key species in the Southern Ocean food web

DC-ATLAS: a systems biology resource to dissect receptor specific signal transduction in dendritic cells

BACKGROUND: The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance when using pathway-based analyses to decipher complex immunological datasets. Here, we present DC-ATLAS, a novel and versatile resource for the interpretation of high-throughput data generated perturbing the signaling network of dendritic cells (DCs). RESULTS: Pathways are annotated using a novel data model, the Biological Connection Markup Language (BCML), a SBGN-compliant data format developed to store the large amount of information collected. The application of DC-ATLAS to pathway-based analysis of the transcriptional program of DCs stimulated with agonists of the toll-like receptor family allows an integrated description of the flow of information from the cellular sensors to the functional outcome, capturing the temporal series of activation events by grouping sets of reactions that occur at different time points in well-defined functional modules. CONCLUSIONS: The initiative significantly improves our understanding of DC biology and regulatory networks. Developing a systems biology approach for immune system holds the promise of translating knowledge on the immune system into more successful immunotherapy strategies