Microarray-based expression profiling of normal and malignant immune cells

Classification of Widely and Rarely Expressed Genes with Recurrent Neural Network

A tissue-specific gene expression shapes the formation of tissues, while gene expression changes reflect the immune response of the human body to environmental stimulations or pressure, particularly in disease conditions, such as cancers. A few genes are commonly expressed across tissues or various cancers, while others are not. To investigate the functional differences between widely and rarely expressed genes, we defined the genes that were expressed in 32 normal tissues/cancers (i.e., called widely expressed genes; FPKM >1 in all samples) and those that were not detected (i.e., called rarely expressed genes; FPKM <1 in all samples) based on the large gene expression data set provided by Uhlen et al. Each gene was encoded using the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment scores. Minimum redundancy maximum relevance (mRMR) was used to measure and rank these features on the mRMR feature list. Thereafter, we applied the incremental feature selection method with a supervised classifier recurrent neural network (RNN) to select the discriminate features for classifying widely expressed genes from rarely expressed genes and construct an optimum RNN classifier. The Youden's indexes generated by the optimum RNN classifier and evaluated using a 10-fold cross validation were 0.739 for normal tissues and 0.639 for cancers. Furthermore, the underlying mechanisms of the key discriminate GO and KEGG features were analyzed. Results can facilitate the identification of the expression landscape of genes and elucidation of how gene expression shapes tissues and the microenvironment of cancers.

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Some genes are widely expressed across tissues or various cancers.

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A number of genes are rarely expressed across tissues or various cancers.

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The functional differences between widely and rarely expressed genes were studied.

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Several GO terms and KEGG pathways were extracted and analyzed.

Functional Genomic Investigation of the Molecular Biological Impact of Electron Beam Radiation in Lymphoma Cells

PURPOSE

The biological response of electron beam radiation (EBR) in tumors remains underexplored. This study describes the molecular biological and genomic impact of EBR on tumor cells.

METHODS

A mouse model bearing Dalton's lymphoma ascites cells was exposed to an 8-MeV pulsed electron beam, at a dose rate of 2 Gy/min using a microtron, a linear accelerator. The radiation-induced changes were assessed by histopathology, fluorescence-activated cell sorting, signaling pathway-focused reporter assays, and gene expression by microarray analysis.

RESULTS

EBR was found to increase apoptosis and G2-M cell cycle arrest with concomitant tumor regression in vivo. The microarray data revealed that EBR induced tumor regression, apoptosis, and cell cycle arrest mediated by p53, PPAR, and SMAD2/3/4 signaling pathways. Activation of interferon regulatory factor and NFkB signaling were also found upon EBR. Chemo-genomics exploration revealed the possibility of drugs that can be effectively used in combination with EBR.

CONCLUSION

For the first time, an 8-MeV pulse EBR induced genomic changes, and their consequence in molecular and biological processes were identified in lymphoma cells. The comprehensive investigation of radiation-mediated responses in cancer cells also revealed the potential therapeutic features of EBR.

Gene expression analysis using single molecule detection

Recent developments of single molecule detection techniques and in particular the introduction of fluorescence correlation spectroscopy (FCS) led to a number of important applications in biological research. We present a unique approach for the gene expression analysis using dual-color cross-correlation. The expression assay is based on gene-specific hybridization of two dye-labeled DNA probes to a selected target gene. The counting of the dual-labeled molecules within the solution allows the quantification of the expressed gene copies in absolute numbers. As detection and analysis by FCS can be performed at the level of single molecules, there is no need for any type of amplification. We describe the gene expression assay and present data demonstrating the capacity of this novel technology. In order to prove the gene specificity, we performed experiments with gene-depleted total cDNA. The biological application was demonstrated by quantifying selected high, medium and low abundant genes in cDNA prepared from HL-60 cells.

Endogenous versus exogenous glucocorticoid responses to experimental bacterial sepsis

Although lack of adrenals dramatically reduces resistance against sepsis generally, the value of glucocorticoid levels above those normally produced by stress remains controversial. An early and long-held concept is that glucocorticoid protection against lipopolysaccharides in animal models is important. Supporting this concept, C3H/HeJ mice, lacking Toll-like receptor-4 (TLR-4), and consequently, endotoxin hyporesponsive, have recently been shown to be resistant to glucocorticoid protection against live Escherichia coli. Effective antibiotic intervention, as an additional parameter and with concomitant administration of glucocorticoid, not only allows for expected antibiotic protection but also for glucocorticoid protection against E. coli or Staphylococcus aureus of mice sensitized to tumor necrosis factor alpha, regardless of the status of the TLR-4 receptor. TLRs, including but not limited to TLR-2, may be involved in glucocorticoid protective efficacy against Gram-positive and Gram-negative sepsis. Overlapping and possibly endotoxin-independent signaling may become important considerations.