Predictive integration of gene functional similarity and co-expression defines treatment response of endothelial progenitor cells

<p>Abstract</p> <p>Background</p> <p>Endothelial progenitor cells (EPCs) have been implicated in different processes crucial to vasculature repair, which may offer the basis for new therapeutic strategies in cardiovascular disease. Despite advances facilitated by functional genomics, there is a lack of systems-level understanding of treatment response mechanisms of EPCs. In this research we aimed to characterize the EPCs response to adenosine (Ado), a cardioprotective factor, based on the systems-level integration of gene expression data and prior functional knowledge. Specifically, we set out to identify novel biosignatures of Ado-treatment response in EPCs.</p> <p>Results</p> <p>The predictive integration of gene expression data and standardized functional similarity information enabled us to identify new treatment response biosignatures. Gene expression data originated from Ado-treated and -untreated EPCs samples, and functional similarity was estimated with Gene Ontology (GO)-based similarity information. These information sources enabled us to implement and evaluate an integrated prediction approach based on the concept of <it>k</it>-nearest neighbours learning (<it>k</it>NN). The method can be executed by expert- and data-driven input queries to guide the search for biologically meaningful biosignatures. The resulting <it>integrated kNN </it>system identified new candidate EPC biosignatures that can offer high classification performance (areas under the operating characteristic curve > 0.8). We also showed that the proposed models can outperform those discovered by standard gene expression analysis. Furthermore, we report an initial independent <it>in vitro </it>experimental follow-up, which provides additional evidence of the potential validity of the top biosignature.</p> <p>Conclusion</p> <p>Response to Ado treatment in EPCs can be accurately characterized with a new method based on the combination of gene co-expression data and GO-based similarity information. It also exploits the incorporation of human expert-driven queries as a strategy to guide the automated search for candidate biosignatures. The proposed biosignature improves the systems-level characterization of EPCs. The new integrative predictive modeling approach can also be applied to other phenotype characterization or biomarker discovery problems.</p

Prediction of LDL cholesterol response to statin using transcriptomic and genetic variation

BACKGROUND: Statins are widely prescribed for lowering LDL-cholesterol (LDLC) levels and risk of cardiovascular disease. There is, however, substantial inter-individual variation in the magnitude of statin-induced LDLC reduction. To date, analysis of individual DNA sequence variants has explained only a small proportion of this variability. The present study was aimed at assessing whether transcriptomic analyses could be used to identify additional genetic contributions to inter-individual differences in statin efficacy. RESULTS: Using expression array data from immortalized lymphoblastoid cell lines derived from 372 participants of the Cholesterol and Pharmacogenetics clinical trial, we identify 100 signature genes differentiating high versus low statin responders. A radial-basis support vector machine prediction model of these signature genes explains 12.3% of the variance in statin-mediated LDLC change. Addition of SNPs either associated with expression levels of the signature genes (eQTLs) or previously reported to be associated with statin response in genome-wide association studies results in a combined model that predicts 15.0% of the variance. Notably, a model of the signature gene associated eQTLs alone explains up to 17.2% of the variance in the tails of a separate subset of the Cholesterol and Pharmacogenetics population. Furthermore, using a support vector machine classification model, we classify the most extreme 15% of high and low responders with high accuracy. CONCLUSIONS: These results demonstrate that transcriptomic information can explain a substantial proportion of the variance in LDLC response to statin treatment, and suggest that this may provide a framework for identifying novel pathways that influence cholesterol metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0460-9) contains supplementary material, which is available to authorized users

Biological processes, properties and molecular wiring diagrams of candidate low-penetrance breast cancer susceptibility genes

Background: Recent advances in whole-genome association studies (WGASs) for human cancer risk are beginning to provide the part lists of low-penetrance susceptibility genes. However, statistical analysis in these studies is complicated by the vast number of genetic variants examined and the weak effects observed, as a result of which constraints must be incorporated into the study design and analytical approach. In this scenario, biological attributes beyond the adjusted statistics generally receive little attention and, more importantly, the fundamental biological characteristics of low-penetrance susceptibility genes have yet to be determined. Methods: We applied an integrative approach for identifying candidate low-penetrance breast cancer susceptibility genes, their characteristics and molecular networks through the analysis of diverse sources of biological evidence. Results: First, examination of the distribution of Gene Ontology terms in ordered WGAS results identified asymmetrical distribution of Cell Communication and Cell Death processes linked to risk. Second, analysis of 11 different types of molecular or functional relationships in genomic and proteomic data sets defined the 'omic' properties of candidate genes: i/ differential expression in tumors relative to normal tissue; ii/ somatic genomic copy number changes correlating with gene expression levels; iii/ differentially expressed across age at diagnosis; and iv/ expression changes after BRCA1 perturbation. Finally, network modeling of the effects of variants on germline gene expression showed higher connectivity than expected by chance between novel candidates and with known susceptibility genes, which supports functional relationships and provides mechanistic hypotheses of risk. Conclusion: This study proposes that cell communication and cell death are major biological processes perturbed in risk of breast cancer conferred by low-penetrance variants, and defines the common omic properties, molecular interactions and possible functional effects of candidate genes and proteins

Association of adipocyte genes with ASP expression: a microarray analysis of subcutaneous and omental adipose tissue in morbidly obese subjects

<p>Abstract</p> <p>Background</p> <p>Prevalence of obesity is increasing to pandemic proportions. However, obese subjects differ in insulin resistance, adipokine production and co-morbidities. Based on fasting plasma analysis, obese subjects were grouped as Low Acylation Stimulating protein (ASP) and Triglyceride (TG) (LAT) vs High ASP and TG (HAT). Subcutaneous (SC) and omental (OM) adipose tissues (n = 21) were analysed by microarray, and biologic pathways in lipid metabolism and inflammation were specifically examined.</p> <p>Methods</p> <p>LAT and HAT groups were matched in age, obesity, insulin, and glucose, and had similar expression of insulin-related genes (InsR, IRS-1). ASP related genes tended to be increased in the HAT group and were correlated (factor B, adipsin, complement C3, p < 0.01 each). Differences between LAT and HAT group were almost exclusively in SC tissue, with little difference in OM tissue. Increased C5L2 (p < 0.01), an ASP receptor, in HAT suggests a compensatory ASP pathway, associated with increased TG storage.</p> <p>Results</p> <p>HAT adipose tissue demonstrated increased lipid related genes for storage (CD36, DGAT1, DGAT2, SCD1, FASN, and LPL), lipolysis (HSL, CES1, perilipin), fatty acid binding proteins (FABP1, FABP3) and adipocyte differentiation markers (CEBPα, CEBPβ, PPARγ). By contrast, oxidation related genes were decreased (AMPK, UCP1, CPT1, FABP7). HAT subjects had increased anti-inflammatory genes TGFB1, TIMP1, TIMP3, and TIMP4 while proinflammatory PIG7 and MMP2 were also significantly increased; all genes, p < 0.025.</p> <p>Conclusion</p> <p>Taken together, the profile of C5L2 receptor, ASP gene expression and metabolic factors in adipose tissue from morbidly obese HAT subjects suggests a compensatory response associated with the increased plasma ASP and TG.</p

Anti-proliferative effect of Rosmarinus officinalis L. extract on human melanoma A375 cells

Rosemary (Rosmarinus officinalis L.) has been used since ancient times in traditional medicine, while nowadays various rosemary formulations are increasingly exploited by alternative medicine to cure or prevent a wide range of health disorders. Rosemary's bioproperties have prompted scientific investigation, which allowed us to ascertain antioxidant, anti-inflammatory, cytostatic, and cytotoxic activities of crude extracts or of pure components. Although there is a growing body of experimental work, information about rosemary's anticancer properties, such as chemoprotective or anti-proliferative effects on cancer cells, is very poor, especially concerning the mechanism of action. Melanoma is a skin tumor whose diffusion is rapidly increasing in the world and whose malignancy is reinforced by its high resistance to cytotoxic agents; hence the availability of new cytotoxic drugs would be very helpful to improve melanoma prognosis. Here we report on the effect of a rosemary hydroalcoholic extract on the viability of the human melanoma A375 cell line. Main components of rosemary extract were identified by liquid chromatography coupled to tandem mass spectrometry (LC/ESI-MS/MS) and the effect of the crude extract or of pure components on the proliferation of cancer cells was tested by MTT and Trypan blue assays. The effect on cell cycle was investigated by using flow cytometry, and the alteration of the cellular redox state was evaluated by intracellular ROS levels and protein carbonylation analysis. Furthermore, in order to get information about the molecular mechanisms of cytotoxicity, a comparative proteomic investigation was performed

Microbial degradation of furanic compounds: biochemistry, genetics, and impact

Microbial metabolism of furanic compounds, especially furfural and 5-hydroxymethylfurfural (HMF), is rapidly gaining interest in the scientific community. This interest can largely be attributed to the occurrence of toxic furanic aldehydes in lignocellulosic hydrolysates. However, these compounds are also widespread in nature and in human processed foods, and are produced in industry. Although several microorganisms are known to degrade furanic compounds, the variety of species is limited mostly to Gram-negative aerobic bacteria, with a few notable exceptions. Furanic aldehydes are highly toxic to microorganisms, which have evolved a wide variety of defense mechanisms, such as the oxidation and/or reduction to the furanic alcohol and acid forms. These oxidation/reduction reactions constitute the initial steps of the biological pathways for furfural and HMF degradation. Furfural degradation proceeds via 2-furoic acid, which is metabolized to the primary intermediate 2-oxoglutarate. HMF is converted, via 2,5-furandicarboxylic acid, into 2-furoic acid. The enzymes in these HMF/furfural degradation pathways are encoded by eight hmf genes, organized in two distinct clusters in Cupriavidus basilensis HMF14. The organization of the five genes of the furfural degradation cluster is highly conserved among microorganisms capable of degrading furfural, while the three genes constituting the initial HMF degradation route are organized in a highly diverse manner. The genetic and biochemical characterization of the microbial metabolism of furanic compounds holds great promises for industrial applications such as the biodetoxifcation of lignocellulosic hydrolysates and the production of value-added compounds such as 2,5-furandicarboxylic acid

Deregulation of Rab and Rab Effector Genes in Bladder Cancer

Growing evidence indicates that Rab GTPases, key regulators of intracellular transport in eukaryotic cells, play an important role in cancer. We analysed the deregulation at the transcriptional level of the genes encoding Rab proteins and Rab-interacting proteins in bladder cancer pathogenesis, distinguishing between the two main progression pathways so far identified in bladder cancer: the Ta pathway characterized by a high frequency of FGFR3 mutation and the carcinoma in situ pathway where no or infrequent FGFR3 mutations have been identified. A systematic literature search identified 61 genes encoding Rab proteins and 223 genes encoding Rab-interacting proteins. Transcriptomic data were obtained for normal urothelium samples and for two independent bladder cancer data sets corresponding to 152 and 75 tumors. Gene deregulation was analysed with the SAM (significant analysis of microarray) test or the binomial test. Overall, 30 genes were down-regulated, and 13 were up-regulated in the tumor samples. Five of these deregulated genes (LEPRE1, MICAL2, RAB23, STXBP1, SYTL1) were specifically deregulated in FGFR3-non-mutated muscle-invasive tumors. No gene encoding a Rab or Rab-interacting protein was found to be specifically deregulated in FGFR3-mutated tumors. Cluster analysis showed that the RAB27 gene cluster (comprising the genes encoding RAB27 and its interacting partners) was deregulated and that this deregulation was associated with both pathways of bladder cancer pathogenesis. Finally, we found that the expression of KIF20A and ZWINT was associated with that of proliferation markers and that the expression of MLPH, MYO5B, RAB11A, RAB11FIP1, RAB20 and SYTL2 was associated with that of urothelial cell differentiation markers. This systematic analysis of Rab and Rab effector gene deregulation in bladder cancer, taking relevant tumor subgroups into account, provides insight into the possible roles of Rab proteins and their effectors in bladder cancer pathogenesis. This approach is applicable to other group of genes and types of cancer

Amplified Genes May Be Overexpressed, Unchanged, or Downregulated in Cervical Cancer Cell Lines

Several copy number-altered regions (CNAs) have been identified in the genome of cervical cancer, notably, amplifications of 3q and 5p. However, the contribution of copy-number alterations to cervical carcinogenesis is unresolved because genome-wide there exists a lack of correlation between copy-number alterations and gene expression. In this study, we investigated whether CNAs in the cell lines CaLo, CaSki, HeLa, and SiHa were associated with changes in gene expression. On average, 19.2% of the cell-line genomes had CNAs. However, only 2.4% comprised minimal recurrent regions (MRRs) common to all the cell lines. Whereas 3q had limited common gains (13%), 5p was entirely duplicated recurrently. Genome-wide, only 15.6% of genes located in CNAs changed gene expression; in contrast, the rate in MRRs was up to 3 times this. Chr 5p was confirmed entirely amplified by FISH; however, maximum 33.5% of the explored genes in 5p were deregulated. In 3q, this rate was 13.4%. Even in 3q26, which had 5 MRRs and 38.7% recurrently gained SNPs, the rate was only 15.1%. Interestingly, up to 19% of deregulated genes in 5p and 73% in 3q26 were downregulated, suggesting additional factors were involved in gene repression. The deregulated genes in 3q and 5p occurred in clusters, suggesting local chromatin factors may also influence gene expression. In regions amplified discontinuously, downregulated genes increased steadily as the number of amplified SNPs increased (p<0.01, Spearman's correlation). Therefore, partial gene amplification may function in silencing gene expression. Additional genes in 1q, 3q and 5p could be involved in cervical carcinogenesis, specifically in apoptosis. These include PARP1 in 1q, TNFSF10 and ECT2 in 3q and CLPTM1L, AHRR, PDCD6, and DAP in 5p. Overall, gene expression and copy-number profiles reveal factors other than gene dosage, like epigenetic or chromatin domains, may influence gene expression within the entirely amplified genome segments

Analysis of the Basidiomycete Coprinopsis cinerea Reveals Conservation of the Core Meiotic Expression Program over Half a Billion Years of Evolution

Coprinopsis cinerea (also known as Coprinus cinereus) is a multicellular basidiomycete mushroom particularly suited to the study of meiosis due to its synchronous meiotic development and prolonged prophase. We examined the 15-hour meiotic transcriptional program of C. cinerea, encompassing time points prior to haploid nuclear fusion though tetrad formation, using a 70-mer oligonucleotide microarray. As with other organisms, a large proportion (∼20%) of genes are differentially regulated during this developmental process, with successive waves of transcription apparent in nine transcriptional clusters, including one enriched for meiotic functions. C. cinerea and the fungi Saccharomyces cerevisiae and Schizosaccharomyces pombe diverged ∼500–900 million years ago, permitting a comparison of transcriptional programs across a broad evolutionary time scale. Previous studies of S. cerevisiae and S. pombe compared genes that were induced upon entry into meiosis; inclusion of C. cinerea data indicates that meiotic genes are more conserved in their patterns of induction across species than genes not known to be meiotic. In addition, we found that meiotic genes are significantly more conserved in their transcript profiles than genes not known to be meiotic, which indicates a remarkable conservation of the meiotic process across evolutionarily distant organisms. Overall, meiotic function genes are more conserved in both induction and transcript profile than genes not known to be meiotic. However, of 50 meiotic function genes that were co-induced in all three species, 41 transcript profiles were well-correlated in at least two of the three species, but only a single gene (rad50) exhibited coordinated induction and well-correlated transcript profiles in all three species, indicating that co-induction does not necessarily predict correlated expression or vice versa. Differences may reflect differences in meiotic mechanisms or new roles for paralogs. Similarities in induction, transcript profiles, or both, should contribute to gene discovery for orthologs without currently characterized meiotic roles