Too much data, but little inter-changeability: a lesson learned from mining public data on tissue specificity of gene expression

BACKGROUND: The tissue expression pattern of a gene often provides an important clue to its potential role in a biological process. A vast amount of gene expression data have been and are being accumulated in public repository through different technology platforms. However, exploitations of these rich data sources remain limited in part due to issues of technology standardization. Our objective is to test the data comparability between SAGE and microarray technologies, through examining the expression pattern of genes under normal physiological states across variety of tissues. RESULTS: There are 42–54% of genes showing significant correlations in tissue expression patterns between SAGE and GeneChip, with 30–40% of genes whose expression patterns are positively correlated and 10–15% of genes whose expression patterns are negatively correlated at a statistically significant level (p = 0.05). Our analysis suggests that the discrepancy on the expression patterns derived from technology platforms is not likely from the heterogeneity of tissues used in these technologies, or other spurious correlations resulting from microarray probe design, abundance of genes, or gene function. The discrepancy can be partially explained by errors in the original assignment of SAGE tags to genes due to the evolution of sequence databases. In addition, sequence analysis has indicated that many SAGE tags and Affymetrix array probe sets are mapped to different splice variants or different sequence regions although they represent the same gene, which also contributes to the observed discrepancies between SAGE and array expression data. CONCLUSION: To our knowledge, this is the first report attempting to mine gene expression patterns across tissues using public data from different technology platforms. Unlike previous similar studies that only demonstrated the discrepancies between the two gene expression platforms, we carried out in-depth analysis to further investigate the cause for such discrepancies. Our study shows that the exploitation of rich public expression resource requires extensive knowledge about the technologies, and experiment. Informatic methodologies for better interoperability among platforms still remain a gap. One of the areas that can be improved practically is the accurate sequence mapping of SAGE tags and array probes to full-length genes. REVIEWERS: This article was reviewed by Dr. I. King Jordan, Dr. Joel Bader, and Dr. Arcady Mushegian

Comparative analysis and integrative classification of NCI60 cell lines and primary tumors using gene expression profiling data

BACKGROUND: NCI60 cell lines are derived from cancers of 9 tissue origins and have been invaluable in vitro models for cancer research and anti-cancer drug screen. Although extensive studies have been carried out to assess the molecular features of NCI60 cell lines related to cancer and their sensitivities to more than 100,000 chemical compounds, it remains unclear if and how well these cell lines represent or model their tumor tissues of origin. Identification and confirmation of correct origins of NCI60 cell lines are critical to their usage as model systems and to translate in vitro studies into clinical potentials. Here we report a direct comparison between NCI60 cell lines and primary tumors by analyzing global gene expression profiles. RESULTS: Comparative analysis suggested that 51 of 59 cell lines we analyzed represent their presumed tumors of origin. Taking advantage of available clinical information of primary tumor samples used to generate gene expression profiling data, we further classified those cell lines with the correct origins into different subtypes of cancer or different stages in cancer development. For example, 6 of 7 non-small cell lung cancer cell lines were classified as lung adenocarcinomas and all of them were classified into late stages in tumor progression. CONCLUSION: Taken together, we developed and applied a novel approach for systematic comparative analysis and integrative classification of NCI60 cell lines and primary tumors. Our results could provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screenings. Moreover, this gene expression profile based approach can be generally applied to evaluate experimental model systems such as cell lines and animal models for human diseases

Retrospective analysis of protein kinase C-beta (PKC-β) expression in lymphoid malignancies and its association with survival in diffuse large B-cell lymphomas

BACKGROUND: Both mechanistic features and recent correlative findings suggest a potential role for protein kinase C-beta (PKC-β) in tumor pathogenesis, particularly in B-cell malignancies. To evaluate the role of this gene in lymphoid malignancies, we analyzed global gene expression data to quantify PKC-β expression across diagnostic groups and, when possible, determined correlations between PKC-β expression and survival. RESULTS: Our analysis showed that the level of PKC-β expression was highest in chronic lymphocytic leukemia and follicular lymphoma. Within diffuse large-B cell lymphoma (DLBCL), PKC-β expression was significantly higher in activated B-cell- like subtype than germinal center B-cell- like subtype (P < 0.0001). Elevated PKC-β appeared to be associated with worse survival in both of these subtypes. When analyzed within clinically defined risk groups established by the International Prognostic Index (IPI), PKC-β expression was lowest in patients with low IPI scores (0–1). Within intermediate- and high-risk IPI groups, elevated PKC-β expression was associated with worse survival, suggesting that PKC-β may expand the prognostic value of the IPI. Results of global gene expression analyses of DLBCL samples corroborate previous observations that anti-apoptosis, cell proliferation, and B-cell proliferation signaling pathways are functionally related to PKC-β. CONCLUSION: We present a first detailed pharmacogenomics report comparing PKC-β mRNA expression across different lymphoid malignancies and evaluating it as an outcome predictor. Our findings suggest that DLBCL patients with elevated PKC-β have a worse prognosis, indicating that further evaluation of PKC-β as a chemotherapeutic target for lymphoid malignancies is warranted. REVIEWERS: This article was reviewed by Dr. Pierre Pontarotti, Dr. Kateryna Makova, and Dr. Matthew Coleman (nominated by Dr. Sandrine Dudoit)

Circulating Markers Reflect Both Anti- and Pro-Atherogenic Drug Effects in ApoE-Deficient Mice

Background: Current drug therapy of atherosclerosis is focused on treatment of major risk factors, e.g. hypercholesterolemia while in the future direct disease modification might provide additional benefits. However, development of medicines targeting vascular wall disease is complicated by the lack of reliable biomarkers. In this study, we took a novel approach to identify circulating biomarkers indicative of drug efficacy by reducing the complexity of the in vivo system to the level where neither disease progression nor drug treatment was associated with the changes in plasma cholesterol.Results: ApoE-/- mice were treated with an ACE inhibitor ramipril and HMG-CoA reductase inhibitor simvastatin. Ramipril significantly reduced the size of atherosclerotic plaques in brachiocephalic arteries, however simvastatin paradoxically stimulated atherogenesis. Both effects occurred without changes in plasma cholesterol. Blood and vascular samples were obtained from the same animals. In the whole blood RNA samples, expression of MMP9, CD14 and IL-1RN reflected pro and anti-atherogenic drug effects. In the plasma, several proteins, e.g. IL-1β, IL-18 and MMP9 followed similar trends while protein readout was less sensitive than RNA analysis.Conclusion: In this study, we have identified inflammation-related whole blood RNA and plasma protein markers reflecting anti-atherogenic effects of ramipril and pro-atherogenic effects of simwastatin in a mouse model of atherosclerosis. This opens an opportunity for early, non-invasive detection of direct drug effects on atherosclerotic plaques in complex in vivo systems

Biochemical characterization of calmodulin isoforms and identification of calmodulin-binding proteins in Arabidopsis

A central question in plant biology is how plant cells discriminate among diverse stimuli to generate precise physiological responses when many stimuli and their responses are coupled by the same signal of changes in intracellular Ca\sp{2+} concentration. The identification of four calmodulin (CaM) isoforms in Arabidopsis provides a good opportunity to address this fundamental question. The goal of this research was to address whether CaM isoforms confer specificity to Ca\sp{2+}-mediated signal transduction pathways. A combination of in vitro biochemical enzyme activation and molecular biological approaches were employed to tackle this question. First, CaM isoforms produced from E. coli expression systems were used to test their abilities to activate pea NAD kinase. There was a small, but significant difference among the CaM isoforms' ability to activate pea NAD kinase in vitro. Minor differences in K\sb{0.5}, but not V\sb{\rm max}, were observed between CaM isoforms and chimeric proteins tagged at their N-termini with a 12-residue c-myc epitope. Nonsense mutations of the C-terminal 7 residues of CaM-6 (CaM-6M), however, drastically impaired the ability of the protein to activate NAD kinase. The requirement for free Ca\sp{2+} to activate NAD kinase by wt and mutant CaM-6 proteins was identical. In contrast, CaM-6M bound synthetic peptide substrates with lower apparent affinity than CaM-6. Because of the importance of NAD kinase as a model system for studying CaM structure and function relationships, a systematic series of experiments were performed to purify NAD kinase with the goal of obtaining direct amino acid sequence information. The method reported here yielded higher purity of the enzyme ($\sim$5000 fold) with enhanced enzyme stability than any previously published methods. Methods of detecting CaM-binding proteins (CaM-BPs) were optimized by conjugating several reporter molecules CaM. The feasibilities of conjugates as ligand probes for detecting CaM-BPs in protein fractions after separation in SDS-PAGE and in screening cDNA expression library were evaluated. Thirty-two clones encoding putative CaM-BPs were isolated from an Arabidopsis flower library. Eighteen clones were partially sequenced. Data base comparisons revealed that some of the sequences shared significant homology with enzymes involved in cell division, phospholipid signaling and other cellular process.U of I OnlyETDs are only available to UIUC Users without author permissio

Editorial message: special track on bioinformatics

Palakal MJ, Rahmann S, Liao B. Editorial message: special track on bioinformatics. In: Liebrock LM, ed. Proceedings of the 2005 ACM symposium on Applied computing (SAC '05). New York, NY: ACM; 2005: 99

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Too much data, but little inter-changeability: a lesson learned from mining public data on tissue specificity of gene expressio