http://www.sage-hindawi.comThe latest articles from SAGE-Hindawi Access to Research© 2010, SAGE-Hindawi Access to Research. All rights reserved.http://www.sage-hindawi.com/journals/hgp/2009/239204.htmlProteomics is the large-scale study of the structure and function of proteins in complex biological sample. Such an approach has the potential value to understand the complex nature of the organism. Current proteomic tools allow large-scale, high-throughput analyses for the detection, identification, and functional investigation of proteome. Advances in protein fractionation and labeling techniques have improved protein identification to include the least abundant proteins. In addition, proteomics has been complemented by the analysis of posttranslational modifications and techniques for the quantitative comparison of different proteomes. However, the major limitation of proteomic investigations remains the complexity of biological structures and physiological processes, rendering the path of exploration paved with various difficulties and pitfalls. The quantity of data that is acquired with new techniques places new challenges on data processing and analysis. This article provides a brief overview of currently available proteomic techniques and their applications, followed by detailed description of advantages and technical challenges. Some solutions to circumvent technical difficulties are proposed.Kondethimmanahalli Chandramouli and Pei-Yuan Qian© 2010, SAGE-Hindawi Access to Research. All rights reserved.http://www.sage-hindawi.com/journals/hgp/2009/453634.htmlGene expression profiling (GEP) of 8 stage 0/I untreated Chronic Lymphocytic Leukemia (CLL) patients showed over-expression of Frizzled 3 (FZD3)/ROR-1 receptor tyrosine kinase (RTK), FLT-3 RTK and CXCR3 G-protein coupled receptor (GPCR). RT-PCR of 24 genes in 21 patients of the WNT pathway corroborated the GEP. Transforming growth factorβ, fibromodulin, TGFβRIII and SMAD2 are also over-expressed by GEP. Serum cytokine profiling of 26 low stage patients showed elevation of IFNγ, CSF3, Flt-3L and insulin-like growth factor binding protein 4. In order to ascertain why CLL cells grow poorly in culture, a GEP of 4 CLL patients cells at 0 hr and 24 hr in culture demonstrated over expression of CXCL5, CCL2 and CXCL3, that may recruit immune cells for survival. Treatment with thalidomide, an immunomodulatory agent, showed elevation of CCL5 by GEP but was not cytotoxic to CLL cells. Our data suggest an interplay of several oncogenic pathways, cytokines and immune cells that promote a survival program in CLL.Daruka Mahadevan, James Choi, Laurence Cooke, Bram Simons, Christopher Riley, Thomas Klinkhammer, Rohit Sud, Sirisha Maddipoti, Sean Hehn, Harinder Garewal, and Catherine Spier© 2010, SAGE-Hindawi Access to Research. All rights reserved.http://www.sage-hindawi.com/journals/hgp/2009/484351.htmlIn order to test the ability of peripheral blood gene expression profiles to predict future disease severity in patients with early rheumatoid arthritis (RA), a group of 17 patients (1±0.2 years disease duration) was evaluated at baseline for gene expression profiles. Disease status was evaluated after a mean of 5 years using an index combining pain, global and recoded MHAQ scores. Unsupervised and supervised algorithms identified “predictor genes” whose combined expression levels correlated with follow-up disease severity scores. Unsupervised clustering algorithms separated patients into two branches. The only significant difference between these two groups was the disease severity score; demographic variables and medication usage were not different. Supervised T-Test analysis identified 19 “predictor genes” of future disease severity. Results were validated in an independent cohort of subjects of established RA with using Support Vector Machines and K-Nearest-Neighbor Classification. Our study demonstrates that peripheral blood gene expression profiles may be a useful tool to predict future disease severity in patients with early and established RA.Zheng Liu, Tuulikki Sokka, Kevin Maas, Nancy J. Olsen, and Thomas M. Aune© 2010, SAGE-Hindawi Access to Research. All rights reserved.http://www.sage-hindawi.com/journals/hgp/2009/869093.htmlDue to rapid technological advances, various types of genomic and proteomic data with different sizes, formats, and structures have become available. Among them are gene expression, single nucleotide polymorphism, copy number variation, and protein-protein/gene-gene interactions. Each of these distinct data types provides a different, partly independent and complementary, view of the whole genome. However, understanding functions of genes, proteins, and other aspects of the genome requires more information than provided by each of the datasets. Integrating data from different sources is, therefore, an important part of current research in genomics and proteomics. Data integration also plays important roles in combining clinical, environmental, and demographic data with high-throughput genomic data. Nevertheless, the concept of data integration is not well defined in the literature and it may mean different things to different researchers. In this paper, we first propose a conceptual framework for integrating genetic, genomic, and proteomic data. The framework captures fundamental aspects of data integration and is developed taking the key steps in genetic, genomic, and proteomic data fusion. Secondly, we provide a review of some of the most commonly used current methods and approaches for combining genomic data with focus on the statistical aspects.Jemila S. Hamid, Pingzhao Hu, Nicole M. Roslin, Vicki Ling, Celia M. T. Greenwood, and Joseph Beyene© 2010, SAGE-Hindawi Access to Research. All rights reserved.http://www.sage-hindawi.com/journals/hgp/2009/597478.htmlGeorge P. Patrinos and Emanuel F. Petricoin© 2010, SAGE-Hindawi Access to Research. All rights reserved.http://www.sage-hindawi.com/journals/hgp/2009/374312.htmlTo identify potential pharmacodynamic biomarkers to guide dose selection in clinical trials using anti-interferon-alpha (IFN-α) monoclonal antibody (mAb) therapy for systemic lupus erythematosus (SLE), we used an Affymetrix human genome array platform and identified 110 IFN-α/β-inducible transcripts significantly upregulated in whole blood (WB) of 41 SLE patients. The overexpression of these genes was confirmed prospectively in 54 additional SLE patients and allowed for the categorization of the SLE patients into groups of high, moderate, and weak overexpressers of IFN-α/β-inducible genes. This approach could potentially allow for an accurate assessment of drug target neutralization in early trials of anti-IFN-α mAb therapy for SLE. Furthermore, ex vivo stimulation of healthy donor peripheral blood mononuclear cells with SLE patient serum and subsequent neutralization with anti-IFN-α mAb or anti-IFN-α receptor mAb showed that anti-IFN-α mAb has comparable effects of neutralizing the overexpression of type I IFN-inducible genes as that of anti-IFNAR mAb. These results suggest that IFN-α, and not other members of type I IFN family in SLE patients, is mainly responsible for the induction of type I IFN-inducible genes in WB of SLE patients. Taken together, these data strengthen the view of IFN-α as a therapeutic target for SLE.Yihong Yao, Brandon W. Higgs, Chris Morehouse, Melissa de los Reyes, Wendy Trigona, Philip Brohawn, Wendy White, Jianliang Zhang, Barbara White, Anthony J. Coyle, Peter A. Kiener, and Bahija Jallal© 2010, SAGE-Hindawi Access to Research. 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