Proteostasis networks in aging: novel insights from text-mining approaches.

Aging is a topic of paramount importance in an increasingly elderly society and has been the focus of extensive research. Protein homeostasis (proteostasis) decline is a hallmark in aging and several age-related diseases, but which specific proteins and mechanisms are involved in proteostasis (de)regulation during the aging process remain largely unknown. Here, we used different text-mining tools complemented with protein-protein interaction data to address this complex topic. Analysis of the integrated protein interaction networks identified novel proteins and pathways associated to proteostasis mechanisms and aging or age-related disorders, indicating that this approach is useful to identify previously unknown links and for retrieving information of potential novel biomarkers or therapeutic targets.

Study of NAD-interacting proteins highlights the extent of NAD regulatory roles in the cell and its potential as a therapeutic target.

Nicotinamide adenine dinucleotide (NAD) levels are essential for the normal physiology of the cell and are strictly regulated to prevent pathological conditions. NAD functions as a coenzyme in redox reactions, as a substrate of regulatory proteins, and as a mediator of protein-protein interactions. The main objectives of this study were to identify the NAD-binding and NAD-interacting proteins, and to uncover novel proteins and functions that could be regulated by this metabolite. It was considered if cancer-associated proteins were potential therapeutic targets. Using multiple experimental databases, we defined datasets of proteins that directly interact with NAD - the NAD-binding proteins (NADBPs) dataset - and of proteins that interact with NADBPs - the NAD-protein-protein interactions (NAD-PPIs) dataset. Pathway enrichment analysis revealed that NADBPs participate in several metabolic pathways, while NAD-PPIs are mostly involved in signalling pathways. These include disease-related pathways, namely, three major neurodegenerative disorders: Alzheimer's disease, Huntington's disease, and Parkinson's disease. Then, the complete human proteome was further analysed to select potential NADBPs. TRPC3 and isoforms of diacylglycerol (DAG) kinases, which are involved in calcium signalling, were identified as new NADBPs. Potential therapeutic targets that interact with NAD were identified, that have regulatory and signalling functions in cancer and neurodegenerative diseases.

Methodology to identify a gene expression signature by merging microarray datasets.

A vast number of microarray datasets have been produced as a way to identify differentially expressed genes and gene expression signatures. A better understanding of these biological processes can help in the diagnosis and prognosis of diseases, as well as in the therapeutic response to drugs. However, most of the available datasets are composed of a reduced number of samples, leading to low statistical, predictive and generalization power. One way to overcome this problem is by merging several microarray datasets into a single dataset, which is typically a challenging task. Statistical methods or supervised machine learning algorithms are usually used to determine gene expression signatures. Nevertheless, statistical methods require an arbitrary threshold to be defined, and supervised machine learning methods can be ineffective when applied to high-dimensional datasets like microarrays. We propose a methodology to identify gene expression signatures by merging microarray datasets. This methodology uses statistical methods to obtain several sets of differentially expressed genes and uses supervised machine learning algorithms to select the gene expression signature. This methodology was validated using two distinct research applications: one using heart failure and the other using autism spectrum disorder microarray datasets. For the first, we obtained a gene expression signature composed of 117 genes, with a classification accuracy of approximately 98%. For the second use case, we obtained a gene expression signature composed of 79 genes, with a classification accuracy of approximately 82%. This methodology was implemented in R language and is available, under the MIT licence, at https://github.com/bioinformatics-ua/MicroGES.

NAPRT Expression Regulation Mechanisms: Novel Functions Predicted by a Bioinformatics Approach.

The nicotinate phosphoribosyltransferase (NAPRT) gene has gained relevance in the research of cancer therapeutic strategies due to its main role as a NAD biosynthetic enzyme. NAD metabolism is an attractive target for the development of anti-cancer therapies, given the high energy requirements of proliferating cancer cells and NAD-dependent signaling. A few studies have shown that NAPRT expression varies in different cancer types, making it imperative to assess NAPRT expression and functionality status prior to the application of therapeutic strategies targeting NAD. In addition, the recent finding of NAPRT extracellular form (eNAPRT) suggested the involvement of NAPRT in inflammation and signaling. However, the mechanisms regulating NAPRT gene expression have never been thoroughly addressed. In this study, we searched for NAPRT gene expression regulatory mechanisms in transcription factors (TFs), RNA binding proteins (RBPs) and microRNA (miRNAs) databases. We identified several potential regulators of NAPRT transcription activation, downregulation and alternative splicing and performed GO and expression analyses. The results of the functional analysis of TFs, RBPs and miRNAs suggest new, unexpected functions for the NAPRT gene in cell differentiation, development and neuronal biology.

Merging microarray studies to identify a common gene expression signature to several structural heart diseases.

BACKGROUND: Heart disease is the leading cause of death worldwide. Knowing a gene expression signature in heart disease can lead to the development of more efficient diagnosis and treatments that may prevent premature deaths. A large amount of microarray data is available in public repositories and can be used to identify differentially expressed genes. However, most of the microarray datasets are composed of a reduced number of samples and to obtain more reliable results, several datasets have to be merged, which is a challenging task. The identification of differentially expressed genes is commonly done using statistical methods. Nonetheless, these methods are based on the definition of an arbitrary threshold to select the differentially expressed genes and there is no consensus on the values that should be used. RESULTS: Nine publicly available microarray datasets from studies of different heart diseases were merged to form a dataset composed of 689 samples and 8354 features. Subsequently, the adjusted p-value and fold change were determined and by combining a set of adjusted p-values cutoffs with a list of different fold change thresholds, 12 sets of differentially expressed genes were obtained. To select the set of differentially expressed genes that has the best accuracy in classifying samples from patients with heart diseases and samples from patients with no heart condition, the random forest algorithm was used. A set of 62 differentially expressed genes having a classification accuracy of approximately 95% was identified. CONCLUSIONS: We identified a gene expression signature common to different cardiac diseases and supported our findings by showing their involvement in the pathophysiology of the heart. The approach used in this study is suitable for the identification of gene expression signatures, and can be extended to different diseases.

Evolution of the NET (NocA, Nlz, Elbow, TLP-1) protein family in metazoans: insights from expression data and phylogenetic analysis.

The NET (for NocA, Nlz, Elbow, TLP-1) protein family is a group of conserved zinc finger proteins linked to embryonic development and recently associated with breast cancer. The members of this family act as transcriptional repressors interacting with both class I histone deacetylases and Groucho/TLE co-repressors. In Drosophila, the NET family members Elbow and NocA are vital for the development of tracheae, eyes, wings and legs, whereas in vertebrates ZNF703 and ZNF503 are important for the development of the nervous system, eyes and limbs. Despite the relevance of this protein family in embryogenesis and cancer, many aspects of its origin and evolution remain unknown. Here, we show that NET family members are present and expressed in multiple metazoan lineages, from cnidarians to vertebrates. We identified several protein domains conserved in all metazoan species or in specific taxonomic groups. Our phylogenetic analysis suggests that the NET family emerged in the last common ancestor of cnidarians and bilaterians and that several rounds of independent events of gene duplication occurred throughout evolution. Overall, we provide novel data on the expression and evolutionary history of the NET family that can be relevant to understanding its biological role in both normal conditions and disease.

Extensive regulation of nicotinate phosphoribosyltransferase (NAPRT) expression in human tissues and tumors.

Nicotinamide adenine dinucleotide (NAD) is a cofactor in redox reactions and a substrate for NAD-consuming enzymes, such as PARPs and sirtuins. As cancer cells have increased NAD requirements, the main NAD salvage enzymes in humans, nicotinamide phosphoribosyltransferase (NAMPT) and nicotinate phosphoribosyltransferase (NAPRT), are involved in the development of novel anti-cancer therapies. Knowledge of the expression patterns of both genes in tissues and tumors is critical for the use of nicotinic acid (NA) as cytoprotective in therapies using NAMPT inhibitors. Herein, we provide a comprehensive study of NAPRT and NAMPT expression across human tissues and tumor cell lines. We show that both genes are widely expressed under normal conditions and describe the occurrence of novel NAPRT transcripts. Also, we explore some of the NAPRT gene expression mechanisms. Our findings underline that the efficiency of NA in treatments with NAMPT inhibitors is dependent on the knowledge of the expression profiles and regulation of both NAMPT and NAPRT.

NAMPT and NAPRT1: novel polymorphisms and distribution of variants between normal tissues and tumor samples.

Nicotinamide phosphoribosyltransferase (NAMPT) and nicotinate phosphoribosyltransferase domain containing 1 (NAPRT1) are the main human NAD salvage enzymes. NAD regulates energy metabolism and cell signaling, and the enzymes that control NAD availability are linked to pathologies such as cancer and neurodegeneration. Here, we have screened normal and tumor samples from different tissues and populations of origin for mutations in human NAMPT and NAPRT1, and evaluated their potential pathogenicity. We have identified several novel polymorphisms and showed that NAPRT1 has a greater genetic diversity than NAMPT, where any alteration can have a greater functional impact. Some variants presented different frequencies between normal and tumor samples that were most likely related to their population of origin. The novel mutations described that affect protein structure or expression levels can be functionally relevant and should be considered in a disease context. Particularly, mutations that decrease NAPRT1 expression can predict the usefulness of Nicotinic Acid in tumor treatments with NAMPT inhibitors.

The evolutionary portrait of metazoan NAD salvage.

Nicotinamide Adenine Dinucleotide (NAD) levels are essential for cellular homeostasis and survival. Main sources of intracellular NAD are the salvage pathways from nicotinamide, where Nicotinamide phosphoribosyltransferases (NAMPTs) and Nicotinamidases (PNCs) have a key role. NAMPTs and PNCs are important in aging, infection and disease conditions such as diabetes and cancer. These enzymes have been considered redundant since either one or the other exists in each individual genome. The co-occurrence of NAMPT and PNC was only recently detected in invertebrates though no structural or functional characterization exists for them. Here, using expression and evolutionary analysis combined with homology modeling and protein-ligand docking, we show that both genes are expressed simultaneously in key species of major invertebrate branches and emphasize sequence and structural conservation patterns in metazoan NAMPT and PNC homologues. The results anticipate that NAMPTs and PNCs are simultaneously active, raising the possibility that NAD salvage pathways are not redundant as both are maintained to fulfill the requirement for NAD production in some species.

Functional and epigenetic characterization of the KRT19 gene in renal cell neoplasms.

The KRT19 gene encodes cytokeratin 19, an element of the cytoskeleton whose expression is frequently altered in renal cell carcinoma (RCC). Epigenetic phenomena, such as promoter methylation, may be a regulatory mechanism of expression of this gene. The aim of this study was to assess the epigenetic regulation of the KRT19 gene using epigenetic-modulating drugs, through the evaluation of methylation and expression status of the promoter region of KRT19 in 6 renal carcinoma cell lines and 112 primary renal tumors (52 clear cell RCC, 22 papillary RCC, 22 chromophobe cell RCC, and 16 oncocytomas). The diagnostic and prognostic value of KRT19 methylation levels in RCC was also evaluated. In cell lines 769-P, A498, and Caki-1, KRT19 re-expression was observed after treatment with 5-aza-2'deoxycytidine and trichostatin A. Conversely, a decrease in promoter methylation levels was apparent for the same cell lines. In primary renal tumors, KRT19 promoter methylation frequency was low (20.5% of cases). Although chromophobe cell RCC showed the lowest frequency compared with the remaining subtypes, this difference did not reach statistical significance. Moreover, no correlation between KRT19 methylation and expression was apparent in tumor samples and no significant correlations with clinicopathological parameters were observed. KRT19 methylation is not a frequent feature of primary RCC and oncocytomas, nor is it associated with clinicopathological parameters. Although we found evidence that KRT19 gene expression is epigenetically regulated in cell lines, this finding was not translated to primary tumors, suggesting the intervention of other genetic mechanisms for in vivo regulation of the KRT19 gene.

Prognostic value of opioid binding protein/cell adhesion molecule-like promoter methylation in bladder carcinoma.

The OPCML gene (opioid binding protein/cell adhesion molecule-like), a putative tumour suppressor gene, is frequently inactivated in carcinomas, namely through aberrant promoter methylation. Herein, we aimed to determine whether OPCML altered expression mediated by epigenetic mechanisms was implicated in bladder carcinogenesis and to assess its potential as a bladder cancer epi-marker. OPCML promoter methylation levels from 91 samples of bladder urothelial carcinoma, 25 normal bladder tissues and bladder cancer cell lines were assessed by quantitative methylation-specific polymerase chain reaction, and correlated with OPCML mRNA expression, determined by quantitative reverse-transcription polymerase chain reaction. To prove the epigenetic regulation of OPCML, five bladder cancer cell lines were exposed to 5-aza-2'deoxycytidine (5-aza-dC), a specific DNA methyltransferase inhibitor and trichostatin A (TSA), a histone deacetylase inhibitor. In bladder tumours, the overall frequency of methylation was 60% and methylation levels were significantly higher when compared with normal mucosa (P=0.0001). No correlation was found between methylation levels and clinicopathological parameters. Interestingly, OPCML promoter methylation was associated with worse disease-specific survival (P=0.022) in univariate analysis. Furthermore, a significant inverse correlation between OPCML promoter methylation and mRNA expression levels was found, although a significant re-expression was only achieved when 5-aza-dC and TSA were used simultaneously. The high frequency of OPCML promoter methylation in urothelial carcinomas suggests an important role for this epigenetic alteration in bladder carcinogenesis, highlighting its potential as an epigenetic biomarker for bladder urothelial carcinoma with prognostic significance.

Three epigenetic biomarkers, GDF15, TMEFF2, and VIM, accurately predict bladder cancer from DNA-based analyses of urine samples.

PURPOSE: To identify a panel of epigenetic biomarkers for accurate bladder cancer (BlCa) detection in urine sediments. EXPERIMENTAL DESIGN: Gene expression microarray analysis of BlCa cell lines treated with 5-aza-2'-deoxycytidine and trichostatin A as well as 26 tissue samples was used to identify a list of novel methylation candidates for BlCa. Methylation levels of candidate genes were quantified in 4 BlCa cell lines, 50 BlCa tissues, 20 normal bladder mucosas (NBM), and urine sediments from 51 BlCa patients and 20 healthy donors, 19 renal cancer patients, and 20 prostate cancer patients. Receiver operator characteristic curve analysis was used to assess the diagnostic performance of the gene panel. RESULTS: GDF15, HSPA2, TMEFF2, and VIM were identified as epigenetic biomarkers for BlCa. The methylation levels were significantly higher in BlCa tissues than in NBM (P < 0.001) and the cancer specificity was retained in urine sediments (P < 0.001). A methylation panel comprising GDF15, TMEFF2, and VIM correctly identified BlCa tissues with 100% sensitivity and specificity. In urine samples, the panel achieved a sensitivity of 94% and specificity of 100% and an area under the curve of 0.975. The gene panel could discriminate BlCa from both healthy individuals and renal or prostate cancer patients (sensitivity, 94%; specificity, 90%). CONCLUSIONS: By using a genome-wide approach, we have identified a biomarker panel that allows for early and accurate noninvasive detection of BlCa using urine samples.