共查询到20条相似文献,搜索用时 31 毫秒
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Sean P. Pitroda Tong Zhou Randy F. Sweis Matthew Filippo Edwardine Labay Michael A. Beckett Helena J. Mauceri Hua Liang Thomas E. Darga Samantha Perakis Sajid A. Khan Harold G. Sutton Wei Zhang Nikolai N. Khodarev Joe G. N. Garcia Ralph R. Weichselbaum 《PloS one》2012,7(10)
Background
Vascular endothelial cells contribute to the pathogenesis of numerous human diseases by actively regulating the stromal inflammatory response; however, little is known regarding the role of endothelial inflammation in the growth of human tumors and its influence on the prognosis of human cancers.Methods
Using an experimental model of tumor necrosis factor-alpha (TNF-α)-mediated inflammation, we characterized inflammatory gene expression in immunopurified tumor-associated endothelial cells. These genes formed the basis of a multivariate molecular predictor of overall survival that was trained and validated in four types of human cancer.Results
We report that expression of experimentally derived tumor endothelial genes distinguished pathologic tissue specimens from normal controls in several human diseases associated with chronic inflammation. We trained these genes in human cancer datasets and defined a six-gene inflammatory signature that predicted significantly reduced overall survival in breast cancer, colon cancer, lung cancer, and glioma. This endothelial-derived signature predicted outcome independently of, but cooperatively with, standard clinical and pathological prognostic factors. Consistent with these findings, conditioned culture media from human endothelial cells stimulated by pro-inflammatory cytokines accelerated the growth of human colon and breast tumors in immunodeficient mice as compared with conditioned media from untreated endothelial cells.Conclusions
This study provides the first prognostic cancer gene signature derived from an experimental model of tumor-associated endothelial inflammation. These findings support the notion that activation of inflammatory pathways in non-malignant tumor-infiltrating endothelial cells contributes to tumor growth and progression in multiple human cancers. Importantly, these results identify endothelial-derived factors that could serve as potential targets for therapy in diverse human cancers. 相似文献8.
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Background
Gene expression profiling using microarrays is a powerful technology widely used to study regulatory networks. Profiling of mRNA levels in mutant organisms has the potential to identify genes regulated by the mutated protein.Methodology/Principle Findings
Using tissues from multiple lines of knockout mice we have examined genome-wide changes in gene expression. We report that a significant proportion of changed genes were found near the targeted gene.Conclusions/Significance
The apparent clustering of these genes was explained by the presence of flanking DNA from the parental ES cell. We provide recommendations for the analysis and reporting of microarray data from knockout mice 相似文献14.
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Anatoly L. Mayburd 《PloS one》2009,4(6)
Background
Stochastic fluctuations in the protein turnover underlie the random emergence of neural precursor cells from initially homogenous cell population. If stochastic alteration of the levels in signal transduction networks is sufficient to spontaneously alter a phenotype, can it cause a sporadic chronic disease as well – including cancer?Methods
Expression in >80 disease-free tissue environments was measured using Affymetrix microarray platform comprising 54675 probe-sets. Steps were taken to suppress the technical noise inherent to microarray experiment. Next, the integrated expression and expression variability data were aligned with the mechanistic data covering major human chronic diseases.Results
Measured as class average, variability of expression of disease associated genes measured in health was higher than variability of random genes for all chronic pathologies. Anti-cancer FDA approved targets were displaying much higher variability as a class compared to random genes. Same held for magnitude of gene expression. The genes known to participate in multiple chronic disorders demonstrated the highest variability. Disease-related gene categories displayed on average more intricate regulation of biological function vs random reference, were enriched in adaptive and transient functions as well as positive feedback relationships.Conclusions
A possible causative link can be suggested between normal (healthy) state gene expression variation and inception of major human pathologies, including cancer. Study of variability profiles may lead to novel diagnostic methods, therapies and better drug target prioritization. The results of the study suggest the need to advance personalized therapy development. 相似文献16.
Thorrez L Van Deun K Tranchevent LC Van Lommel L Engelen K Marchal K Moreau Y Van Mechelen I Schuit F 《PloS one》2008,3(3):e1854
Background
Housekeeping genes are needed in every tissue as their expression is required for survival, integrity or duplication of every cell. Housekeeping genes commonly have been used as reference genes to normalize gene expression data, the underlying assumption being that they are expressed in every cell type at approximately the same level. Often, the terms “reference genes” and “housekeeping genes” are used interchangeably. In this paper, we would like to distinguish between these terms. Consensus is growing that housekeeping genes which have traditionally been used to normalize gene expression data are not good reference genes. Recently, ribosomal protein genes have been suggested as reference genes based on a meta-analysis of publicly available microarray data.Methodology/Principal Findings
We have applied several statistical tools on a dataset of 70 microarrays representing 22 different tissues, to assess and visualize expression stability of ribosomal protein genes. We confirmed the housekeeping status of these genes, but further estimated expression stability across tissues in order to assess their potential as reference genes. One- and two-way ANOVA revealed that all ribosomal protein genes have significant expression variation across tissues and exhibit tissue-dependent expression behavior as a group. Via multidimensional unfolding analysis, we visualized this tissue-dependency. In addition, we explored mechanisms that may cause tissue dependent effects of individual ribosomal protein genes.Conclusions/Significance
Here we provide statistical and biological evidence that ribosomal protein genes exhibit important tissue-dependent variation in mRNA expression. Though these genes are most stably expressed of all investigated genes in a meta-analysis they cannot be considered true reference genes. 相似文献17.
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Xiaopei Shen Shan Li Lin Zhang Hongdong Li Guini Hong XianXiao Zhou Tingting Zheng Wenjing Zhang Chunxiang Hao Tongwei Shi Chunyang Liu Zheng Guo 《PloS one》2013,8(4)
Background
Cancer cells typically exhibit large-scale aberrant methylation of gene promoters. Some of the genes with promoter methylation alterations play “driver” roles in tumorigenesis, whereas others are only “passengers”.Results
Based on the assumption that promoter methylation alteration of a driver gene may lead to expression alternation of a set of genes associated with cancer pathways, we developed a computational framework for integrating promoter methylation and gene expression data to identify driver methylation aberrations of cancer. Applying this approach to breast cancer data, we identified many novel cancer driver genes and found that some of the identified driver genes were subtype-specific for basal-like, luminal-A and HER2+ subtypes of breast cancer.Conclusion
The proposed framework proved effective in identifying cancer driver genes from genome-wide gene methylation and expression data of cancer. These results may provide new molecular targets for potential targeted and selective epigenetic therapy. 相似文献20.
Rajicic N Cuschieri J Finkelstein DM Miller-Graziano CL Hayden D Moldawer LL Moore E O'Keefe G Pelik K Warren HS Schoenfeld DA;Inflammation the Host Response to Injury Large Scale Collaborative Research Program 《PloS one》2010,5(12):e14380