Long-Term Cigarette Smoke Exposure and Changes in MiRNA Expression and Proteome in Non-Small-Cell Lung Cancer.

Chronic exposure to cigarette smoke markedly increases the risk for lung cancer. Regulation of gene expression at the post-transcriptional level by miRNAs influences a variety of cancer-related interactomes. Yet, relatively little is known on the effects of long-term cigarette smoke exposure on miRNA expression and gene regulation. NCI-H292 (H292) is a cell line sensitive to cigarette smoke with mucoepidermoid characteristics in culture. We report, in this study, original observations on long-term (12 months) cigarette smoke effects in the H292 cell line, using microarray-based miRNA expression profiling, and stable isotopic labeling with amino acids in cell culture-based quantitative proteomic analysis. We identified 112 upregulated and 147 downregulated miRNAs (by twofold) in cigarette smoke-treated H292 cells. The liquid chromatography-tandem mass spectrometry analysis identified 3,959 proteins, of which, 303 proteins were overexpressed and 112 proteins downregulated (by twofold). We observed 39 miRNA target pairs (proven targets) that were differentially expressed in response to chronic cigarette smoke exposure. Gene ontology analysis of the target proteins revealed enrichment of proteins in biological processes driving metabolism, cell communication, and nucleic acid metabolism. Pathway analysis revealed the enrichment of phagosome maturation, antigen presentation pathway, nuclear factor erythroid 2-related factor 2-mediated oxidative stress response, and cholesterol biosynthesis pathways in cigarette smoke-exposed cells. In conclusion, this report makes an important contribution to knowledge on molecular changes in a lung cell line in response to long term cigarette smoke exposure. The findings might inform future strategies for drug target, biomarker and diagnostics innovation in lung cancer, and clinical oncology. These observations also call for further research on the extent to which continuing or stopping cigarette smoking in patients diagnosed with lung cancer translates into molecular and clinical outcomes.

A pathway map of glutamate metabolism.

Glutamate metabolism plays a vital role in biosynthesis of nucleic acids and proteins. It is also associated with a number of different stress responses. Deficiency of enzymes involved in glutamate metabolism is associated with various disorders including gyrate atrophy, hyperammonemia, hemolytic anemia, γ-hydoxybutyric aciduria and 5-oxoprolinuria. Here, we present a pathway map of glutamate metabolism representing metabolic intermediates in the pathway, 107 regulator molecules, 9 interactors and 3 types of post-translational modifications. This pathway map provides detailed information about enzyme regulation, protein-enzyme interactions, post-translational modifications of enzymes and disorders due to enzyme deficiency. The information included in the map was based on published experimental evidence reported from mammalian systems.

A draft map of the human proteome.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Pancreatic Cancer Database: an integrative resource for pancreatic cancer.

Pancreatic cancer is the fourth leading cause of cancer-related death in the world. The etiology of pancreatic cancer is heterogeneous with a wide range of alterations that have already been reported at the level of the genome, transcriptome, and proteome. The past decade has witnessed a large number of experimental studies using high-throughput technology platforms to identify genes whose expression at the transcript or protein levels is altered in pancreatic cancer. Based on expression studies, a number of molecules have also been proposed as potential biomarkers for diagnosis and prognosis of this deadly cancer. Currently, there are no repositories which provide an integrative view of multiple Omics data sets from published research on pancreatic cancer. Here, we describe the development of a web-based resource, Pancreatic Cancer Database (http://www.pancreaticcancerdatabase.org), as a unified platform for pancreatic cancer research. PCD contains manually curated information pertaining to quantitative alterations in miRNA, mRNA, and proteins obtained from small-scale as well as high-throughput studies of pancreatic cancer tissues and cell lines. We believe that PCD will serve as an integrative platform for scientific community involved in pancreatic cancer research.

Proteomic analysis of human osteoarthritis synovial fluid.

BACKGROUND: Osteoarthritis is a chronic musculoskeletal disorder characterized mainly by progressive degradation of the hyaline cartilage. Patients with osteoarthritis often postpone seeking medical help, which results in the diagnosis being made at an advanced stage of cartilage destruction. Sustained efforts are needed to identify specific markers that might help in early diagnosis, monitoring disease progression and in improving therapeutic outcomes. We employed a multipronged proteomic approach, which included multiple fractionation strategies followed by high resolution mass spectrometry analysis to explore the proteome of synovial fluid obtained from osteoarthritis patients. In addition to the total proteome, we also enriched glycoproteins from synovial fluid using lectin affinity chromatography. RESULTS: We identified 677 proteins from synovial fluid of patients with osteoarthritis of which 545 proteins have not been previously reported. These novel proteins included ADAM-like decysin 1 (ADAMDEC1), alanyl (membrane) aminopeptidase (ANPEP), CD84, fibulin 1 (FBLN1), matrix remodelling associated 5 (MXRA5), secreted phosphoprotein 2 (SPP2) and spondin 2 (SPON2). We identified 300 proteins using lectin affinity chromatography, including the glycoproteins afamin (AFM), attractin (ATRN), fibrillin 1 (FBN1), transferrin (TF), tissue inhibitor of metalloproteinase 1 (TIMP1) and vasorin (VSN). Gene ontology analysis confirmed that a majority of the identified proteins were extracellular and are mostly involved in cell communication and signaling. We also confirmed the expression of ANPEP, dickkopf WNT signaling pathway inhibitor 3 (DKK3) and osteoglycin (OGN) by multiple reaction monitoring (MRM) analysis of osteoarthritis synovial fluid samples. CONCLUSIONS: We present an in-depth analysis of the synovial fluid proteome from patients with osteoarthritis. We believe that the catalog of proteins generated in this study will further enhance our knowledge regarding the pathophysiology of osteoarthritis and should assist in identifying better biomarkers for early diagnosis.

Plasma Proteome Database as a resource for proteomics research: 2014 update.

Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization's (HUPO's) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10,546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.

IL-11/IL11RA receptor mediated signaling: a web accessible knowledgebase.

Abstract Interleukin-11 (IL-11) is a pleiotropic cytokine that belongs to gp130 family. It plays a significant role in the synthesis and maturation of hematopoietic cells, inhibition of adipogenesis, regulation of embryo implantation, and trophoblasts invasion. Although IL-11 signaling has been described in several biological processes, a centralized resource documenting these molecular reactions induced by IL-11 is not publicly available. In the current study, we have manually annotated the molecular reactions and interactions induced by IL-11 from literature available. We have documented 40 unique molecules involved in 18 protein-protein interactions, 26 enzyme-substrate reactions, 7 translocation events, and 4 activation/ inhibition reactions. We have also annotated 23 genes reported to be differentially regulated under IL-11 stimulation. We have enabled the data availability in standard exchange formats from 'NetPath', a repository for signaling pathways. We believe that this will help in the identification of potential therapeutic targets in IL-11-associated disorders.

Access guide to human proteinpedia.

Human Proteinpedia (http://www.humanproteinpedia.org) is a publicly available proteome repository for sharing human protein data derived from multiple experimental platforms. It incorporates diverse features of the human proteome including protein-protein interactions, enzyme-substrate relationships, PTMs, subcellular localization, and expression of proteins in various human tissues and cell lines in diverse biological conditions including diseases. Through a publicly distributed annotation system developed especially for proteomic data, investigators across the globe can upload, view, and edit proteomic data even before they are published. Inclusion of information on investigators and laboratories that generated the data, as well as visualization of tandem mass spectra, stained tissue sections, protein/peptide microarrays, fluorescent micrographs, and western blots, ensures quality of proteomic data assimilated in Human Proteinpedia. Many of the protein annotations submitted to Human Proteinpedia have also been made available to the scientific community through Human Protein Reference Database (http://www.hprd.org), another resource developed by our group. In this protocol, we describe how to submit, edit, and retrieve proteomic data in Human Proteinpedia.

NetSlim: high-confidence curated signaling maps.

We previously developed NetPath as a resource for comprehensive manually curated signal transduction pathways. The pathways in NetPath contain a large number of molecules and reactions which can sometimes be difficult to visualize or interpret given their complexity. To overcome this potential limitation, we have developed a set of more stringent curation and inclusion criteria for pathway reactions to generate high-confidence signaling maps. NetSlim is a new resource that contains this 'core' subset of reactions for each pathway for easy visualization and manipulation. The pathways in NetSlim are freely available at http://www.netpath.org/netslim.

A comprehensive manually curated reaction map of RANKL/RANK-signaling pathway.

Receptor activator of nuclear factor-kappa B ligand (RANKL) is a member of tumor necrosis factor (TNF) superfamily that plays a key role in the regulation of differentiation, activation and survival of osteoclasts and also in tumor cell migration and bone metastasis. Osteoclast activation induced by RANKL regulates hematopoietic stem cell mobilization as part of homeostasis and host defense mechanisms thereby linking regulation of hematopoiesis with bone remodeling. Binding of RANKL to its receptor, Receptor activator of nuclear factor-kappa B (RANK) activates molecules such as NF-kappa B, mitogen activated protein kinase (MAPK), nuclear factor of activated T cells (NFAT) and phosphatidyl 3-kinase (PI3K). Although the molecular and cellular roles of these molecules have been reported previously, a systematic cataloging of the molecular events induced by RANKL/RANK interaction has not been attempted. Here, we present a comprehensive reaction map of the RANKL/RANK-signaling pathway based on an extensive manual curation of the published literature. We hope that the curated RANKL/RANK-signaling pathway model would enable new biomedical discoveries, which can provide novel insights into disease processes and development of novel therapeutic interventions.

Characterization of dental caries by LIF spectroscopy with 404-nm excitation.

The potential of laser-induced fluorescence (LIF) spectroscopy for the characterization of different stages of dental caries using 404-nm diode laser excitation was investigated. In vitro spectra from 16 sound, 10 noncavitated carious and 10 cavitated carious molar teeth were recorded on a miniature fibre-optic spectrometer. The areas under the receiver operating characteristics (ROC-AUC) were calculated and one-way analysis of variance (ANOVA) was performed. The LIF spectra of the carious teeth showed two peaks at 635 and 680 nm in addition to a broad band seen at 500 nm in sound teeth. The fluorescence intensity ratios, F500/F635 and F500/F680, in carious teeth were always lower than those in sound teeth. The ROC-AUC for discriminating between carious and sound teeth was 0.94, and for discriminating between noncavitated and cavitated carious teeth was 0.87. Statistically significant differences (p<0.001) were seen between sound, noncavitated carious and cavitated carious teeth. The results showed that LIF spectroscopy has the potential to be useful for characterizing different stages of caries in a clinical setting.