Bioinformatics Data Mining Research Articles

Genome-wide analysis of regulatory proteases sequences identified through bioinformatics data mining in Taenia solium.

BackgroundCysticercosis remains a major neglected tropical disease of humanity in many regions, especially in sub-Saharan Africa, Central America and elsewhere. Owing to the emerging drug resistance and the inability of current drugs to prevent re-infection, identification of novel vaccines and chemotherapeutic agents against Taenia solium and related helminth pathogens is a public health priority. The T. solium genome and the predicted proteome were reported recently, providing a wealth of information from which new interventional targets might be identified. In order to characterize and classify the entire repertoire of protease-encoding genes of T. solium, which act fundamental biological roles in all life processes, we analyzed the predicted proteins of this cestode through a combination of bioinformatics tools. Functional annotation was performed to yield insights into the signaling processes relevant to the complex developmental cycle of this tapeworm and to highlight a suite of the proteases as potential intervention targets.ResultsWithin the genome of this helminth parasite, we identified 200 open reading frames encoding proteases from five clans, which correspond to 1.68% of the 11,902 protein-encoding genes predicted to be present in its genome. These proteases include calpains, cytosolic, mitochondrial signal peptidases, ubiquitylation related proteins, and others. Many not only show significant similarity to proteases in the Conserved Domain Database but have conserved active sites and catalytic domains. KEGG Automatic Annotation Server (KAAS) analysis indicated that ~60% of these proteases share strong sequence identities with proteins of the KEGG database, which are involved in human disease, metabolic pathways, genetic information processes, cellular processes, environmental information processes and organismal systems. Also, we identified signal peptides and transmembrane helices through comparative analysis with classes of important regulatory proteases. Phylogenetic analysis using Bayes approach provided support for inferring functional divergence among regulatory cysteine and serine proteases.ConclusionNumerous putative proteases were identified for the first time in T. solium, and important regulatory proteases have been predicted. This comprehensive analysis not only complements the growing knowledge base of proteolytic enzymes, but also provides a platform from which to expand knowledge of cestode proteases and to explore their biochemistry and potential as intervention targets.Electronic supplementary materialThe online version of this article (doi: 10.1186/1471-2164-15-428) contains supplementary material, which is available to authorized users.

Molecular network analysis suggests a logical hypothesis for the pathological role of c9orf72 in amyotrophic lateral sclerosis/frontotemporal dementia.

BACKGROUNDExpanded GGGGCC hexanucleotide repeats, ranging from hundreds to thousands in number, located in the noncoding region of the chromosome 9 open reading frame 72 (C9orf72) gene represent the most common genetic abnormality for familial and sporadic amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) (abbreviated as C9ALS). Currently, three pathological mechanisms, such as haplo insufficiency of C9orf72, formation of nuclear RNA foci composed of sense and antisense repeats, and accumulation of unconventionally transcribed dipeptide-repeat (DPR) proteins, are proposed for C9ALS. However, at present, the central mechanism underlying neurodegeneration in C9ALS remains largely unknown.METHODSBy using three distinct pathway analysis tools of bioinformatics, we studied molecular networks involved in C9ALS pathology by focusing on C9orf72 omics datasets, such as proteome of C9orf72 repeat RNA-binding proteins, transcriptome of induced pluripotent stem cells (iPSC)-derived motor neurons of patients with C9ALS, and transcriptome of purified motor neurons of patients with C9ALS.RESULTSWe found that C9orf72 repeat RNA-binding proteins play a crucial role in the regulation of post-transcriptional RNA processing. The expression of a wide range of extracellular matrix proteins and matrix metalloproteinases was reduced in iPSC-derived motor neurons of patients with C9ALS. The regulation of RNA processing and cytoskeletal dynamics is disturbed in motor neurons of patients with C9ALS in vivo.CONCLUSIONSBioinformatics data mining approach suggests a logical hypothesis that C9orf72 repeat expansions that deregulate post-transcriptional RNA processing disturb the homeostasis of cytoskeletal dynamics and remodeling of extracellular matrix, leading to degeneration of stress-vulnerable neurons in the brain and spinal cord of patients with C9ALS.

Bioinformatic data mining on UDP-glucose:flavonoid 7- O-glucosyltransferase (UBGAT) genes and their encoding proteins in two plants of genus Scutellaria

The GenBank sequences of UBGAT (UDP-glucose:flavonoid 7-O-glucosyltransferase) genes and their encoding proteins from Scutellaria baicalensisand Scutellaria laeteviolacea, were predicted and analyzed by some bioinformatics methods and tools such as expasy, vector NTI, National Center for Biotechnology Information (NCBI) etc. The results obtained are as follows: both Sbubgat andSlubgat genes contained complete open reading frame (ORF); the formula of SbUBGAT and SbUBGAT were C2193H3462N590O638S11 and C2263H3562N596O664S13, respectively and both proteins were found in the cytoplasm, without transmembrane topological structure, and were hydrophic proteins related to intermediary metabolism and amino acid synthesis; the secondary structure of UBGATs constitute mainly α-helix and random coil and the tertiary structure were modeling. In brief, this study lay theoretical foundation for metabolic mechanism and genetic regulation researches of flavonoids biosynthesis. Key words: Scutellaria baicalensis, Scutellaria laeteviolacea, flavonoids, bioinformatics, UDP-glucose:flavonoid 7-O-glucosyltransferase.

Quantitative clinical proteomic study of autopsied human infarcted brain specimens to elucidate the deregulated pathways in ischemic stroke pathology

Ischemic stroke, still lacking an effective neuroprotective therapy is the third leading cause of global mortality and morbidity. Here, we have applied an 8-plex iTRAQ-based 2D-LC-MS/MS strategy to study the commonly regulated infarct proteome from three different brain regions (putamen, thalamus and the parietal lobe) of female Japanese patients. Infarcts were compared with age-, post-mortem interval- and location-matched control specimens. The iTRAQ experiment confidently identified 1520 proteins with 0.1% false discovery rate. Bioinformatics data mining and immunochemical validation of pivotal perturbed proteins revealed a global failure of the cellular energy metabolism in the infarcted tissues as seen by the parallel down-regulation of proteins related to glycolysis, pyruvate dehydrogenase complex, TCA cycle and oxidative phosphorylation. The concomitant down-regulation of all participating proteins (SLC25A11, SLC25A12, GOT2 and MDH2) of malate-aspartate shuttle might be responsible for the metabolic in-coordination between the cytosol and mitochondria resulting in the failure of energy metabolism. The levels of proteins related to reactive gliosis (VIM, GFAP) and anti-inflammatory response (ANXA1, ANXA2) showed an increasing trend. The elevation of ferritin (FTL, FTH1) may indicate an iron-mediated oxidative imbalance aggravating the mitochondrial failure and neurotoxicity. The deregulated proteins could be useful as potential therapeutic targets or biomarkers for ischemic stroke. Clinical proteomics of stroke has been lagging behind other areas of clinical proteomics like Alzheimer's disease or schizophrenia. Our study is the first quantitative clinical proteomics study where iTRAQ-2D-LC-MS/MS has been utilized in the area of ischemic stroke to obtain a comparative profile of human ischemic infarcts and age-, sex-, location- and post-mortem interval-matched control brain specimens. Different pathological attributes of ischemic stroke well-known through basic and pre-clinical research such as failure of cellular energy metabolism, reactive gliosis, activation of anti-inflammatory response and aberrant iron metabolism have been observed at the bedside. Our dataset could act as a reference for similar studies done in the future using ischemic brain samples from various brain banks across the world. A meta-analysis of these studies could help to map the pathological proteome specific to ischemic stroke that will guide the scientific community to better evaluate the pros and cons of the pre-clinical models for efficacy and mechanistic studies. Infarct being the core of injury should have the most intense regulation for several key proteins involved in the pathophysiology of ischemic stroke. Hence, a part of the up-regulated proteome could leak into the general circulation that may offer candidates of interest as potential biomarkers. In support of our proposed hypothesis, we report ferritin in the current study as one of the most elevated proteins in the infarct, which has been documented as a biomarker in the context of ischemic stroke by an independent study. Overall, our approach has the potential to identify probable therapeutic targets and biomarkers in the area of ischemic stroke.

Abstract 4466: Integrative study of dysregulated genes in translocated ALK-positive non-small cell lung cancer and personalized targeted therapy resistance.

Abstract Background: Recent studies revealed that ALK (anaplastic lymphoma kinase) 2p23 translocation, most commonly fused with echinoderm microtubule-associated protein-like 4 (EML4), is a novel driver oncogene in about 5% of non-small cell lung cancer (NSCLC). ALK 2p23 fusion (ALK+) can be diagnosed by dual color break-part ALK FISH assay to inform personalized targeted therapy using the ALK inhibitor crizotinib. However, the underlying mechanisms of ALK oncogenic signaling and more importantly ALK inhibitor crizotinib resistance are not well understood. Materials and Methods: To understand the mechanism of oncogenic ALK signaling, an ALK+ NSCLC microarray dataset was retrieved from NCBI-GEO data repository (GSE31210) and analyzed using data-mining bioinformatics approaches. This dataset includes the gene expression profiles of 11 ALK+ NSCLC and 20 normal lung tissue samples. Statistical analysis was carried out to identify altered genes in ALK+ NSCLC and Ingenuity Pathway Analysis (IPA) software was deployed to uncover their network interactions. To study the resistance mechanism of the ALK+ H3122 human NSCLC cell line against the specific ALK inhibitor TAE684, real-time polymerase chain reaction (qRT-PCR), cell viability assay and immunoblotting were performed using standard techniques. Results: We identified a set of 1,656 genes that were significantly altered in ALK+ NSCLC, consisting of 662 upregulated and 994 downregulated. The principal component analysis (PCA) based on the top 51 of these dysregulated genes evidently separated ALK+ and normal lung tissue samples, implicating that these genes could represent potential genomic signature of ALK+ NSCLC. The IPA analysis revealed 35 canonical pathways linked to ALK signaling, including beta-adrenergic and angiopoietin signaling pathways. The results of qRT-PCR, cell viability assay and immunoblotting showed that in translocated ALK+ H3122 human NSCLC cell line, HGF (hepatocyte growth factor) overexpression could activate ALK downstream signaling via activation of MET receptor kinase pathway, thus potentially bypassing the oncogenic ALK signaling under ALK inhibitor TAE684 treatment. Hence, alternative direct activation of ALK downstream signaling molecules via MET/HGF axis activation may potentially contribute to ALK inhibitor drug resistance. Conclusion: Using bioinformatics data-mining, we have identified dysregulated genes and pathways in ALK+ NSCLC, many of which are novel biomarkers not previously reported. We also verified the relevance and potential key role of MET/HGF signaling axis in ALK inhibitor resistance. Taken together, our results highlighted the cross-talk between ALK and MET signaling in NSCLC and shed new insights into possible pitfalls of potential specific ALK targeting inhibitor drugs. Citation Format: Ivy Shi, Lihong Yin, Patrick C. Ma. Integrative study of dysregulated genes in translocated ALK-positive non-small cell lung cancer and personalized targeted therapy resistance. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4466. doi:10.1158/1538-7445.AM2013-4466

Looking for Arabidopsis thaliana peroxidases involved in lignin biosynthesis

Monolignol polymerization into lignin is catalyzed by peroxidases or laccases. Recently, a Zinnia elegans peroxidase (ZePrx) that is considered responsible for monolignol polymerization in this plant has been molecularly and functionally characterized. Nevertheless, Arabidopsis thaliana has become an alternative model plant for studies of lignification, filling the gaps that may occur with Z.elegans. The arabidopsis genome offers the possibility of performing bioinformatic analyses and data mining that are not yet feasible with other plant species, in order to obtain preliminary evidence on the role of genes and proteins. In our search for arabidopsis homologs to the ZePrx, we performed an exhaustive in silico characterization of everything from the protein to the transcript of Arabidopsis thaliana peroxidases (AtPrxs) homologous to ZePrx, with the aim of identifying one or more peroxidases that may be involved in monolignol polymerization. Nine peroxidases (AtPrx 4, 5, 52, 68, 67, 36, 14, 49 and 72) with an E-value greater than 1e-80 with ZePrx were selected for this study. The results demonstrate that a high level of 1D, 2D and 3D homology between these AtPrxs and ZePrx are not always accompanied by the presence of the same electrostatic and mRNA properties that indicate a peroxidase is involved in lignin biosynthesis. In summary, we can confirm that the peroxidases involved in lignification are among AtPrx 4, 52, 49 and 72. Their structural and mRNA features indicate that exert their action in the cell wall similar to ZePrx.

An emerging role of microRNA miR-223 in cardiovascular pathophysiology

MicroRNAs (miRNAs) comprise a class of small, noncoding, untranslated RNAs that control expression of complementary target mRNAs. Though termed 'micro-RNAs', these small entities can easily create a 'macro' impact at cellular or even at organismal level, under physiological or pathological conditions. A minor change in their expression or regulation can cause (or prevent / protect against) a disease condition. miR-223 is known to be a platelet-enriched myeloid specific miRNA. However, our recent finding and many other studies have demonstrated a possible role for miR-223 in vascular smooth muscle cells and in cardiomyocytes. miR- 223 is proposed to play a cardioprotective and anti-inflammatory role and its expression is dysregulated in cardiovascular diseases (CVD) such as vascular calcification, acute myocardial infarction, diabetic and non-diabetic heart failure. Here, we provide an overview of the recent advancements in the field of miR-223 research and its involvement in cardiovascular pathophysiology. Additionally, with the help of bioinformatics analyses, web resources and data mining, we identified putative transcriptional regulators of miR-223 expression in cardiac and vascular cells. Finally, we attempted to correlate the altered expression of miR-223 in CVD with some of its known or predicted targets, which might have a possible role in miR-223 disease linkage.

The periodontal pathogen Porphyromonas gingivalis changes the gene expression in vascular smooth muscle cells involving the TGFbeta/Notch signalling pathway and increased cell proliferation

BackgroundPorphyromonas gingivalis is a gram-negative bacterium that causes destructive chronic periodontitis. In addition, this bacterium is also involved in the development of cardiovascular disease. The aim of this study was to investigate the effects of P. gingivalis infection on gene and protein expression in human aortic smooth muscle cells (AoSMCs) and its relation to cellular function.ResultsAoSMCs were exposed to viable P. gingivalis for 24 h, whereafter confocal fluorescence microscopy was used to study P. gingivalis invasion of AoSMCs. AoSMCs proliferation was evaluated by neutral red assay. Human genome microarray, western blot and ELISA were used to investigate how P. gingivalis changes the gene and protein expression of AoSMCs. We found that viable P. gingivalis invades AoSMCs, disrupts stress fiber structures and significantly increases cell proliferation. Microarray results showed that, a total of 982 genes were identified as differentially expressed with the threshold log2 fold change > |1| (adjust p-value <0.05). Using bioinformatic data mining, we demonstrated that up-regulated genes are enriched in gene ontology function of positive control of cell proliferation and down-regulated genes are enriched in the function of negative control of cell proliferation. The results from pathway analysis revealed that all the genes belonging to these two categories induced by P. gingivalis were enriched in 25 pathways, including genes of Notch and TGF-beta pathways.ConclusionsThis study demonstrates that P. gingivalis is able to invade AoSMCs and stimulate their proliferation. The activation of TGF-beta and Notch signaling pathways may be involved in the bacteria-mediated proliferation of AoSMCs. These findings further support the association between periodontitis and cardiovascular diseases.

Comparative genomic analysis of NAC transcriptional factors to dissect the regulatory mechanisms for cell wall biosynthesis

BackgroundNAC domain transcription factors are important transcriptional regulators involved in plant growth, development and stress responses. Recent studies have revealed several classes of NAC transcriptional factors crucial for controlling secondary cell wall biosynthesis. These transcriptional factors mainly include three classes, SND, NST and VND. Despite progress, most current analysis is carried out in the model plant Arabidopsis. Moreover, many downstream genes regulated by these transcriptional factors are still not clear.MethodsIn order to identify the key homologue genes across species and discover the network controlling cell wall biosynthesis, we carried out comparative genome analysis of NST, VND and SND genes across 19 higher plant species along with computational modelling of genes regulated or co-regulated with these transcriptional factors.ResultsThe comparative genome analysis revealed that evolutionarily the secondary-wall-associated NAC domain transcription factors first appeared in Selaginella moellendorffii. In fact, among the three groups, only VND genes appeared in S. moellendorffii, which is evolutionarily earlier than the other two groups. The Arabidopsis and rice gene expression analysis showed specific patterns of the secondary cell wall-associated NAC genes (SND, NST and VND). Most of them were preferentially expressed in the stem, especially the second internodes. Furthermore, comprehensive co-regulatory network analysis revealed that the SND and MYB genes were co-regulated, which indicated the coordinative function of these transcriptional factors in modulating cell wall biosynthesis. In addition, the co-regulatory network analysis revealed many novel genes and pathways that could be involved in cell wall biosynthesis and its regulation. The gene ontology analysis also indicated that processes like carbohydrate synthesis, transport and stress response, are coordinately regulated toward cell wall biosynthesis.ConclusionsOverall, we provided a new insight into the evolution and the gene regulatory network of a subgroup of the NAC gene family controlling cell wall composition through bioinformatics data mining and bench validation. Our work might benefit to elucidate the possible molecular mechanism underlying the regulation network of secondary cell wall biosynthesis.

Wnt/β-catenin signaling is downregulated but restored by nutrition interventions in the aged heart in mice

Aging hallmarks include decreased progenitor cell functions. The Wnt/β-catenin signaling pathway has emerged as a key player in cellular aging in recent years. Wnt activity changes in aged tissues including skin, serum, muscle and artery. In heart, it is hypothesized that Wnt signaling increases with aging and this signaling drives cardiac progenitor cells into fibrogenic lineage. However, experimental evidence supporting this hypothesis has not been established. Here we take a bioinformatics data mining approach, utilizing pre-existing data, to study cardiac aging gene expression data in mice. Contrary to the hypothesis, our study shows that the Wnt/β-catenin signaling is down-regulated in aged heart in mice. Nutrition treatment, with calorie restriction and Resveratrol supplementation, known to retard aging, opposes heart aging by restoring Wnt/β-catenin signaling level in the old heart. In addition, the expression of β-catenin gene, a key regulator of the Wnt/β-catenin signaling pathway, decreases up to 3-fold in aged heart, but is restored to levels found in young heart with methods of nutrition intervention. Combined with database search, our study suggests that some of bioflavonoids may have potential therapeutic benefits to heart aging.

Plants versus fungi and oomycetes: pathogenesis, defense and counter-defense in the proteomics era.

Plant-fungi and plant-oomycete interactions have been studied at the proteomic level for many decades. However, it is only in the last few years, with the development of new approaches, combined with bioinformatics data mining tools, gel staining, and analytical instruments, such as 2D-PAGE/nanoflow-LC-MS/MS, that proteomic approaches thrived. They allow screening and analysis, at the sub-cellular level, of peptides and proteins resulting from plants, pathogens, and their interactions. They also highlight post-translational modifications to proteins, e.g., glycosylation, phosphorylation or cleavage. However, many challenges are encountered during in planta studies aimed at stressing details of host defenses and fungal and oomycete pathogenicity determinants during interactions. Dissecting the mechanisms of such host-pathogen systems, including pathogen counter-defenses, will ensure a step ahead towards understanding current outcomes of interactions from a co-evolutionary point of view, and eventually move a step forward in building more durable strategies for management of diseases caused by fungi and oomycetes. Unraveling intricacies of more complex proteomic interactions that involve additional microbes, i.e., PGPRs and symbiotic fungi, which strengthen plant defenses will generate valuable information on how pathosystems actually function in nature, and thereby provide clues to solving disease problems that engender major losses in crops every year.

Novel gene expression profile in blood cells from cattle experimentally exposed to Mycobacterium avium subsp. paratuberculosis (164.24)

Abstract Mycobacterium avium subspecies paratuberculosis (Mptb) is the causative agent of the chronic debilitating condition called Johne’s (JD) disease that affects ruminants and is a suspected causative agent in Crohn’s disease in humans. Identifying and characterising the different strategies employed by Mptb to alter the host immune system in its favour and thereby persist intracellularly could hold the key to fighting this disease. Affymetrix Genechip Bovine Gene microarrays were performed using the RNA prepared from blood samples collected from exposed and non-exposed control cattle from the controlled experimental model of bovine JD. Bio-informatics tools and data mining were applied to identify relationships between genes and physiological functions. Genes related to lipid pathways and anti-bacterial defence mechanisms were identified and validated in a larger cohort at different time-points post-infection by quantitative polymerase chain reaction. Several novel gene pathways were shown to be differentially regulated in bovine JD linking lipid pathways and anti-bacterial defence mechanisms. Downregulation of the cellular cholesterol homeostasis mechanism could act as a countermeasure to infection. A novel model was developed that explores how these could impact the host immune response in a double edged sword manner that leads to the progression of pathogenesis.

In silico identification and characterization of 1-aminocyclopropane-1-carboxylate deaminase from Phytophthora sojae

As part of an effort to obtain a fungal 1-aminocyclopropane-1-carboxylate deaminase encoding gene from Phytophthora sojae expressed sequence Tag database, we identify and characterize the ACCD from P. sojae using bioinformatics data mining tools and techniques. Computed structural model of P. sojae ACCD was found to consist of mixed α/β motifs and probable loops. The predicted model resembles the structure of Pseudomonas ACCD (RMSD-0.44Å). The main differences observed between them are the presence of partial length of domain one, and longer helix α4. Ramachandran plot analysis revealed that portion of all residues falling into the most favorable regions was 95.0%. The substrate - and geometrical- docking of developed structure postulated functional capability of ACCD to carry out ACC cleavage reaction. The catalytic site in homo-tetrameric structure open to opposite directions separated by ∼37.97Å distance arranged around central axis. This study provides a comprehensive identification and characterization of the ACCD in P. sojae and it may be helpful in the transcriptional and expression based study of P. sojae pathogenesis.

Abstract 3003: Development of a computational framework for disease knowledge modeling and clinical treatment decision support and its application to a rare cancer, malignant peripheral nerve sheath tumor (MPNST)

Abstract The integration of increasingly diverse and disparate data about cancers into routine, clinical decision making is a major challenge for evidence-based medicine. Clearly, a comprehensive knowledge model for an indication is the mandatory basis for any evidence-based treatment prioritization. But the concepts and technologies required to collate pre-existing disease and treatment data into useful models of molecular etiology are unclear. Rare cancers represent a particularly pressing need in this context: finding, combining and enriching the few existing disease information and using it for treatment prioritization, -especially in the off-label setting-, beyond the often poorly defined standard of care. To address this, we have developed a novel framework for computational disease knowledge modeling and tested its applicability for clinical treatment decision support in the concrete case of a patient with a recurrent rare cancer, -malignant peripheral nerve sheath tumor (MPNST). Our primary goal was to construct for the first time an integrated disease knowledge model for MPNST by combining bioinformatics and text data mining methods. Text data mining on scientific literature (Pubmed) defined a basic corpus of 317 publications with a total of 145 proteins/ genes and sequence variants, associated with indication terms for MPNST. This set was enriched in factors involved in the MPNST-related tissue and cell biology, and candidate drivers of familial and sporadic MPNST forms. From this core we identified 47 factors, for which MPNST-associated genomic or transcriptomic aberrations had been reported. Utilizing information on molecular pathway association, physical protein interactions and cellular process association of these factors from an integrated oncology data warehouse, we then built a network representation of the molecular disease knowledge for MPNST. Our model highlights and links several molecular modules potentially involved in MPNST, such as deregulated receptor tyrosine kinases involved in cell proliferation, adhesion and invasion, the downstream signaling pathways PI3K/ AKT/ MTOR and RAS/ RAF/ MAPK, and their interactions with the familial MPNST candidate genes NF1 and NF2. Using drug database and clinical trial information we matched treatment options and associated open protocols to our model and mapped the target promiscuity profiles of drugs to network topography. This validated the clinical relevance of molecular entities in our model and allowed treatment prioritization for the patient based on the modeled disease knowledge. Our study demonstrates the feasibility of computational disease knowledge modeling in oncology and the utility of it in providing mechanistic evidence for treatment prioritization in poorly understood rare cancers such as MPNST. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3003. doi:1538-7445.AM2012-3003

Abstract 3267: Inhibition of angiogenic potential of neuroblastoma cells through regulation of microRNA expression profiles by tumor suppressor gene dipeptidyl peptidase IV

Abstract Neuroblastoma (NB), a childhood cancer of peripheral nervous system generally progress to highly angiogenic and therapy resistant fatal metastatic tumor. We have recently shown that a cell surface protease called dipeptidyl peptidase (DPPIV) is expressed in normal neural crest derived differentiated cells and its expression is lost in proliferating NB, the malignant counterpart. We also demonstrated that re-expression of DPPIV in NB cells leads to their differentiation, apoptosis, and suppression of their migratory and angiogenic potential. Importantly, DPPIV inhibits the tumorigenic potential of NB cells in a xenograft mouse model. To further identify DPPIV-responsive genes and mechanisms, we used Affymetrix microarray analysis. This study showed an association of DPPIV expression with up-regulation of thrombospondin-1 (THBS1), an angiogenesis inhibitor. Interestingly, some of the genes regulated by DPPIV are also altered by microRNA (miRNAs), indicating that at least some of the miRNAs might act as intermediate effectors in mediating DPPIV function. PCR array screening of cancer specific miRNAs, showed that DPPIV indeed alters miRNA profile in NB cells. In particular, DPPIV down-regulated miR-19a which is a part of the miR-17-92 cluster that is known to decrease THBS1 levels. Furthermore, bioinformatics data mining of Sangers MicroCosm Targets v5 predicted THBS1 as a potential target of miR-19a suggesting that down-regulation of miR19a leading to up-regulation of THBS1 was a possible mechanism involved in DPPIV tumor suppressor function. In support of this idea, silencing of DPPIV expression by RNA interference resulted in increased miR-19a and decreased THBS1 expression. Furthermore, transfection of NB cells with anti-miR-19a decreased miR19a and increased THBS1 levels as shown by real time quantitative RT-PCR, immunofluorescence and western blot analysis. Furthermore, DPPIV expression decreased the levels of cMYC, a transcription factor that up-regulates miR-19a expression. These effects were associated with decreased levels of basic fibroblast growth factor (bFGF) and vascular endothelial growth factor (VEGF), two strong downstream pro-angiogenic factors. Taken together, our work identifies a novel and an important mechanism wherein DPPIV inhibits angiogenesis and growth of NB tumor cells through down regulation of miR-19a mediated c-MYC expression and increased expression of THBS1, an angiogenesis inhibitor. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3267. doi:10.1158/1538-7445.AM2011-3267

Abstract 5073: Proteomic profiling of head and neck squamous cell carcinoma cell lines

Abstract INTRODUCTION: Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth most common cancer worldwide with approximately 500,000 new cases diagnosed each year. Squamous cell carcinomas of the larynx (LSCC) and the hypopharynx (HSCC) are subtypes of HNSCC. The current diagnostic methods are not sensitive enough since pre-cancerous fields are often not visible to the naked eye during endoscopic examination and are difficult to detect even on histology. Discovery of novel biomarkers for HNSCC should lead to improved detection of HNSCC. Mass spectrometry-based proteomics methods have emerged as promising approaches for biomarker discovery. As one approach, mass-spectrometric identification of proteins shed or secreted from cancer cells can contribute to our understanding of tumour behaviour and to the identification of potential diagnostic biomarkers for HSCC and LSCC. EXPERIMENTAL DESIGN: In order to identify putative biomarkers for HNSCC detection, mass spectrometry-based proteomic profiling was performed on the conditioned media (i.e. secretome) of cancer cell lines of laryngeal and hypopharyngeal origin (UTSCC42a, UTSCC8, and FaDu). In addition, a human gene expression microarray was used to identify over-expressed genes in HNSCC cell lines in comparison to a control cell line. The protein expression data was integrated with gene expression microarray profiles and systematic bioinformatics data mining using publicly available resources (Human Protein Atlas and published proteomic/transcriptomic data) was used to prioritize the markers for validation. Subsequently, real-time quantitative PCR, Western Blotting, and immunohistochemistry (IHC), were performed to validate the over-expression of selected markers. RESULTS: Proteomic profiling of HNSCC cell lines resulted in 1850 protein identifications. By integrating the protein expression data with gene expression microarray profiles, we identified 90 putative protein biomarkers that were secreted or shed to the extracellular space and over-expressed in HNSCC cell lines, relative to controls. Subsequently, the over-expression of 5 markers was successfully validated at the transcriptional and translational levels using quantitative real-time PCR, Western Blotting, and IHC on the HNSCC cell lines, and xenograft tumour models. CONCLUSION: Secretome and transcriptome profiling of HNSCC cell lines enabled the identification of 90 putative HNSCC biomarkers for further validation, 5 of which were successfully validated in vitro. Several of these markers have been implicated in HNSCC, illustrating the robustness of our approach to biomarker discovery. Future validation steps will include examination of these proteins in primary HNSCC biopsies, and matching patient sera. Ultimately, identification of a panel of protein biomarkers in a biological fluid (e.g. serum) of HNSCC patients will allow the development of an effective diagnostic test for early diagnosis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5073. doi:10.1158/1538-7445.AM2011-5073

Differential aminoacylase expression in neuroblastoma

Neuroblastoma, a cancer of the sympathetic nervous system, is the most common extracranial solid tumor in children. MYCN amplification and increased BDNF/TrkB signaling are features of high-risk tumors; yet, only ˜25% of malignant tumors display these features. Thus, the identification of additional biomarkers and therapeutic targets is essential. As aminoacylase 1 (ACY1), an amino acid deacetylase, is a putative tumor suppressor in small cell lung and renal cell carcinomas, we investigated whether it or the other family members aspartoacylase (ASPA, aminoacylase 2) or aminoacylase 3 (ACY3) could serve a similar function in neuroblastoma. Aminoacylase expression was examined in TrkB-positive, MYCN-amplified (SMS-KCNR and SK-N-BE) and TrkB-negative, non-MYCN-amplified (SK-N-AS, SK-N-SH, SH-SY5Y and SH-EP) neuroblastoma cell lines. Each aminoacylase exhibited distinct spatial localization (i.e., cytosolic ACY1, membrane-associated ASPA and nuclear ACY3). When SK-N-SH cells were treated with neural differentiation agents (e.g., retinoic acid and cAMP) in media containing 10% serum, ACY1 was the only aminoacylase whose expression was upregulated. ASPA was primarily expressed in SH-EP cells of a glial sublineage. ACY3 was more highly expressed in the TrkB-positive, MYCN-amplified lines. All three aminoacylases were expressed in normal human adrenal gland, a common site of neuroblastoma origin, but only ACY1 and ACY3 displayed detectable expression in primary neuroblastoma tumor. Bioinformatics data mining of Kaplan-Meier survival revealed that high ACY3 expression is correlated with poor prognosis, whereas low expression of ACY1 or ASPA is correlated with poor prognosis. These data suggest that aminoacylase expression is dysregulated in neuroblastoma.

Candidate biomarkers in renal cell carcinoma.

405 Background: Renal cell carcinoma (RCC) represents a heterogeneous disease with widely varying prognosis. Therefore, the screening for biomarkers, which allow the diagnosis as well as the assessment of the individual risk of disease progression and mortality are a prerequisite for the selection of patients for different modes of therapies and the implementation of individually tailored surveillance protocols. Methods: Various proteome-based technologies such as 2DE-based proteomics, PROTEOMEX or ligandomics in combination with mass spectrometry have been applied. Bioinformatic data mining led to the categorization and priorization of the respective target lists. Selected candidate targets were further independently verified by qRT-PCR, Western blot and/or immunohistochemistry. Results: A large series of differentially expressed/immunoreactive proteins have been identified in clear cell RCC when compared to normal kidney epithelium. With the different approaches distinct sets of potential candidate targets were defined and categorized into different protein families and functions and according to their cellular localization. Moreover, the limited sharing rates between the respective target lists demonstrate their complementarity. Some selected markers were further validated by qRT-PCR, Western blot analysis and/or immunohistochemical stainings of tissue micro arrays comprised of RCC lesions of different TNM classification and histology revealing distinct expression pattern in regard to the RCC subtype, tumor grading,staging or additional molecular features. Using the ligandomics approach proteins have been identified, which were able to mount an immune response in vitro. Conclusions: Some candidate markers might have the potential to be used as diagnostic and prognostic factors if not as novel targets for therapy and thus could be employed for the expression profiling of a larger series of RCC patients. No significant financial relationships to disclose.

Genome-wide high-throughput integrome analyses by nrLAM-PCR and next-generation sequencing

High-throughput integration site profiling has become a feasible tool to assess vector biosafety and to monitor the cell fate of the gene-corrected cell population in clinical gene therapy studies. Here we report a step-by-step protocol for universal genome-wide and comprehensive integrome analysis that can be performed on >10(2)-10(3) samples of interest in parallel. This assay is composed of fast and cost-efficient non-restrictive linear amplification-mediated PCR; optimized sample preparation for pyrosequencing; and automated bioinformatic data mining, including sequence trimming, alignment to the cellular genome and further annotation. Moreover, the workflow of this large-scale assay can be adapted to any PCR-based method aiming to characterize unknown flanking DNA adjacent to a known DNA region. Thus, in combination with next-generation sequencing technologies, large-scale integrome analysis of > 4 x 10(5)-1 x 10(6) integration site sequences can be accomplished within a single week.

Data Mining in Bioinformatics: Selected Papers from BIOKDD

The two papers in this special section are extended papers chosen from nine peer-reviewed papers originally presented at the 2008 International Workshops on Data Mining in Bioinformatics (BIOKDD), held 24-27 August in Las Vegas, NV.