The nitrone spin trap 5,5-dimethyl-1-pyrroline N-oxide dampens lipopolysaccharide-induced transcriptomic changes in macrophages.

OBJECTIVE: M1-like inflammatory phenotype of macrophages plays a critical role in tissue damage in chronic inflammatory diseases. Previously, we found that the nitrone spin trap 5,5-dimethyl-1-pyrroline N-oxide (DMPO) dampens lipopolysaccharide (LPS)-triggered inflammatory priming of RAW 264.7 cells. Herein, we tested whether DMPO by itself can induce changes in macrophage transcriptome, and that these effects may prevent LPS-induced activation of macrophages. MATERIALS AND METHODS: To test our hypothesis, we performed a transcriptomic and bioinformatics analysis in RAW 264.7 cells incubated with or without LPS, in the presence or in the absence of DMPO. RESULTS: Functional data analysis showed 79 differentially expressed genes (DEGs) when comparing DMPO vs Control. We used DAVID databases for identifying enriched gene ontology terms and Ingenuity Pathway Analysis for functional analysis. Our data showed that DMPO vs Control comparison of DEGs is related to downregulation immune-system processes among others. Functional analysis indicated that interferon-response factor 7 and toll-like receptor were related (predicted inhibitions) to the observed transcriptomic effects of DMPO. Functional data analyses of the DMPO + LPS vs LPS DEGs were consistent with DMPO-dampening LPS-induced inflammatory transcriptomic profile in RAW 264.7. These changes were confirmed using Nanostring technology. CONCLUSIONS: Taking together our data, surprisingly, indicate that DMPO by itself affects gene expression related to regulation of immune system and that DMPO dampens LPS-triggered MyD88- and TRIF-dependent signaling pathways. Our research provides critical data for further studies on the possible use of DMPO as a structural platform for the design of novel mechanism-based anti-inflammatory drugs.

Blood gene expression profiling of an early acetaminophen response.

Acetaminophen can adversely affect the liver especially when overdosed. We used whole blood as a surrogate to identify genes as potential early indicators of an acetaminophen-induced response. In a clinical study, healthy human subjects were dosed daily with 4 g of either acetaminophen or placebo pills for 7 days and evaluated over the course of 14 days. Alanine aminotransferase (ALT) levels for responders to acetaminophen increased between days 4 and 9 after dosing, and 12 genes were detected with expression profiles significantly altered within 24 h. The early responsive genes separated the subjects by class and dose period. In addition, the genes clustered patients who overdosed on acetaminophen apart from controls and also predicted the exposure classifications with 100% accuracy. The responsive genes serve as early indicators of an acetaminophen exposure, and their gene expression profiles can potentially be evaluated as molecular indicators for further consideration.

Blood transcript immune signatures distinguish a subset of people with elevated serum ALT from others given acetaminophen.

The diagnosis of drug-induced liver injury is hindered by the limited utility of clinical chemistries. We have shown that hepatotoxicants can produce peripheral blood transcriptome "signatures" (PBTS) in rodents and humans. In this study, 42 adults were treated with acetaminophen (APAP; 1 g every 6 hours) for seven days, followed by three days of placebo. Eleven subjects received only placebo. After five days, 12 subjects (30%) had increases in serum alanine aminotransferase (ALT) levels ("responders"). PBTS of 707 and 760 genes, respectively, could distinguish responders and nonresponders from placebos. Functional analysis of the responder PBTS revealed increased expression of genes involved in TH2-mediated and innate immune responses, whereas the nonresponders demonstrated increased gene expression consistent with a tolerogenic immune response. Taken together, these observations suggest that the clinical subjects with transient increases in serum ALT failed to maintain or intensify a hepatic tolerogenic immune response.

Consistency of predictive signature genes and classifiers generated using different microarray platforms.

Microarray-based classifiers and associated signature genes generated from various platforms are abundantly reported in the literature; however, the utility of the classifiers and signature genes in cross-platform prediction applications remains largely uncertain. As part of the MicroArray Quality Control Phase II (MAQC-II) project, we show in this study 80-90% cross-platform prediction consistency using a large toxicogenomics data set by illustrating that: (1) the signature genes of a classifier generated from one platform can be directly applied to another platform to develop a predictive classifier; (2) a classifier developed using data generated from one platform can accurately predict samples that were profiled using a different platform. The results suggest the potential utility of using published signature genes in cross-platform applications and the possible adoption of the published classifiers for a variety of applications. The study reveals an opportunity for possible translation of biomarkers identified using microarrays to clinically validated non-array gene expression assays.

Genomic indicators in the blood predict drug-induced liver injury.

Genomic biomarkers for the detection of drug-induced liver injury (DILI) from blood are urgently needed for monitoring drug safety. We used a unique data set as part of the Food and Drug Administration led MicroArray Quality Control Phase-II (MAQC-II) project consisting of gene expression data from the two tissues (blood and liver) to test cross-tissue predictability of genomic indicators to a form of chemically induced liver injury. We then use the genomic indicators from the blood as biomarkers for prediction of acetaminophen-induced liver injury and show that the cross-tissue predictability of a response to the pharmaceutical agent (accuracy as high as 92.1%) is better than, or at least comparable to, that of non-therapeutic compounds. We provide a database of gene expression for the highly informative predictors, which brings biological context to the possible mechanisms involved in DILI. Pathway-based predictors were associated with inflammation, angiogenesis, Toll-like receptor signaling, apoptosis, and mitochondrial damage. The results show for the first time and support the hypothesis that genomic indicators in the blood can serve as potential diagnostic biomarkers predictive of DILI.

Blood gene expression signatures predict exposure levels.

To respond to potential adverse exposures properly, health care providers need accurate indicators of exposure levels. The indicators are particularly important in the case of acetaminophen (APAP) intoxication, the leading cause of liver failure in the U.S. We hypothesized that gene expression patterns derived from blood cells would provide useful indicators of acute exposure levels. To test this hypothesis, we used a blood gene expression data set from rats exposed to APAP to train classifiers in two prediction algorithms and to extract patterns for prediction using a profiling algorithm. Prediction accuracy was tested on a blinded, independent rat blood test data set and ranged from 88.9% to 95.8%. Genomic markers outperformed predictions based on traditional clinical parameters. The expression profiles of the predictor genes from the patterns extracted from the blood exhibited remarkable (97% accuracy) transtissue APAP exposure prediction when liver gene expression data were used as a test set. Analysis of human samples revealed separation of APAP-intoxicated patients from control individuals based on blood expression levels of human orthologs of the rat discriminatory genes. The major biological signal in the discriminating genes was activation of an inflammatory response after exposure to toxic doses of APAP. These results support the hypothesis that gene expression data from peripheral blood cells can provide valuable information about exposure levels, well before liver damage is detected by classical parameters. It also supports the potential use of genomic markers in the blood as surrogates for clinical markers of potential acute liver damage.

Insulin-like growth factor-1 inscribes a gene expression profile for angiogenic factors and cancer progression in breast epithelial cells.

Activation of the insulin-like growth factor-1 receptor (IGF-1R) by IGF-1 is associated with the risk and progression of many types of cancer, although despite this it remains unclear how activated IGF-1R contributes to cancer progression. In this study, gene expression changes elicited by IGF-1 were profiled in breast epithelial cells. We noted that many genes are functionally linked to cancer progression and angiogenesis. To validate some of the changes observed, the RNA and/or protein was confirmed for c-fos, cytochrome P450 1A1, cytochrome P450 1B1, interleukin-1 beta, fas ligand, vascular endothelial growth factor, and urokinase plasminogen activator. Nuclear proteins were also temporally monitored to address how gene expression changes were regulated. We found that IGF-1 stimulated the nuclear translocation of phosphorylated AKT, hypoxic-inducible factor-1 alpha, and phosphorylated cAMP-responsive element-binding protein, which correlated with temporal changes in gene expression. Next, the promoter regions of IGF-1-regulated genes were searched in silico. The promoters of genes that clustered together had similar regulatory regions. In summary, IGF-1 inscribes a gene expression profile relevant to cancer progression, and this study provides insight into the mechanism(s) whereby some of these changes occur.

Progress in the application of DNA microarrays.

Microarray technology has been applied to a variety of different fields to address fundamental research questions. The use of microarrays, or DNA chips, to study the gene expression profiles of biologic samples began in 1995. Since that time, the fundamental concepts behind the chip, the technology required for making and using these chips, and the multitude of statistical tools for analyzing the data have been extensively reviewed. For this reason, the focus of this review will be not on the technology itself but on the application of microarrays as a research tool and the future challenges of the field.

MAPS: a microarray project system for gene expression experiment information and data validation.

SUMMARY: MAPS is a MicroArray Project System for management and interpretation of microarray gene expression experiment information and data. Microarray project information is organized to track experiments and results that are: (1) validated by performing analysis on stored replicate gene expression data; and (2) queried according to the biological classifications of genes deposited on microarray chips.

Inactivation of DNA mismatch repair by increased expression of yeast MLH1.

Inactivation of DNA mismatch repair by mutation or by transcriptional silencing of the MLH1 gene results in genome instability and cancer predisposition. We recently found (P. V. Shcherbakova and T. A. Kunkel, Mol. Cell. Biol. 19:3177-3183, 1999) that an elevated spontaneous mutation rate can also result from increased expression of yeast MLH1. Here we investigate the mechanism of this mutator effect. Hybridization of poly(A)(+) mRNA to DNA microarrays containing 96.4% of yeast open reading frames revealed that MLH1 overexpression did not induce changes in expression of other genes involved in DNA replication or repair. MLH1 overexpression strongly enhanced spontaneous mutagenesis in yeast strains with defects in the 3'-->5' exonuclease activity of replicative DNA polymerases delta and epsilon but did not enhance the mutation rate in strains with deletions of MSH2, MLH1, or PMS1. This suggests that overexpression of MLH1 inactivates mismatch repair of replication errors. Overexpression of the PMS1 gene alone caused a moderate increase in the mutation rate and strongly suppressed the mutator effect caused by MLH1 overexpression. The mutator effect was also reduced by a missense mutation in the MLH1 gene that disrupted Mlh1p-Pms1p interaction. Analytical ultracentrifugation experiments showed that purified Mlh1p forms a homodimer in solution, albeit with a K(d) of 3.14 microM, 36-fold higher than that for Mlh1p-Pms1p heterodimerization. These observations suggest that the mismatch repair defect in cells overexpressing MLH1 results from an imbalance in the levels of Mlh1p and Pms1p and that this imbalance might lead to formation of nonfunctional mismatch repair complexes containing Mlh1p homodimers.

Smooth muscle alpha-actin promoter activity is induced by serum stimulation of fibroblast cells.

Transient transfection analysis of a plasmid containing human alpha-actin promoter linked to bacterial chloramphenicol acetyl transferase (CAT) reporter gene, in Rat-2 fibroblast cells, indicates that smooth muscle (sm) alpha-actin promoter activity is induced by serum. The CArG [CC (A/T) 6GG] box sequences within the alpha-actin promoter mediate the serum induction. This induction can be blocked by overexpression of Fos, suggesting that it follows the same regulatory pathway as c-fos.