Identification of a Common Gene Expression Response in Different Lung Inflammatory Diseases in Rodents and Macaques

To identify gene expression responses common to multiple pulmonary diseases we collected microarray data for acute lung inflammation models from 12 studies and used these in a meta-analysis. The data used include exposures to air pollutants; bacterial, viral, and parasitic infections; and allergic asthma models. Hierarchical clustering revealed a cluster of 383 up-regulated genes with a common response. This cluster contained five subsets, each characterized by more specific functions such as inflammatory response, interferon-induced genes, immune signaling, or cell proliferation. Of these subsets, the inflammatory response was common to all models, interferon-induced responses were more pronounced in bacterial and viral models, and a cell division response was more prominent in parasitic and allergic models. A common cluster containing 157 moderately down-regulated genes was associated with the effects of tissue damage. Responses to influenza in macaques were weaker than in mice, reflecting differences in the degree of lung inflammation and/or virus replication. The existence of a common cluster shows that in vivo lung inflammation in response to various pathogens or exposures proceeds through shared molecular mechanisms

A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

hTERT promoter activity and CpG methylation in HPV-induced carcinogenesis

<p>Abstract</p> <p>Background</p> <p>Activation of telomerase resulting from deregulated hTERT expression is a key event during high-risk human papillomavirus (hrHPV)-induced cervical carcinogenesis. In the present study we examined hTERT promoter activity and its relation to DNA methylation as one of the potential mechanisms underlying deregulated hTERT transcription in hrHPV-transformed cells.</p> <p>Methods</p> <p>Using luciferase reporter assays we analyzed hTERT promoter activity in primary keratinocytes, HPV16- and HPV18-immortalized keratinocyte cell lines and cervical cancer cell lines. In the same cells as well as cervical specimens we determined hTERT methylation by bisulfite sequencing analysis of the region spanning -442 to +566 (relative to the ATG) and quantitative methylation specific PCR (qMSP) analysis of two regions flanking the hTERT core promoter.</p> <p>Results</p> <p>We found that in most telomerase positive cells increased hTERT core promoter activity coincided with increased hTERT mRNA expression. On the other hand basal hTERT promoter activity was also detected in telomerase negative cells with no or strongly reduced hTERT mRNA expression levels. In both telomerase positive and negative cells regulatory sequences flanking both ends of the core promoter markedly repressed exogenous promoter activity.</p> <p>By extensive bisulfite sequencing a strong increase in CpG methylation was detected in hTERT positive cells compared to cells with no or strongly reduced hTERT expression. Subsequent qMSP analysis of a larger set of cervical tissue specimens revealed methylation of both regions analyzed in 100% of cervical carcinomas and 38% of the high-grade precursor lesions, compared to 9% of low grade precursor lesions and 5% of normal controls.</p> <p>Conclusions</p> <p>Methylation of transcriptionally repressive sequences in the hTERT promoter and proximal exonic sequences is correlated to deregulated hTERT transcription in HPV-immortalized cells and cervical cancer cells. The detection of DNA methylation at these repressive regions may provide an attractive biomarker for early detection of cervical cancer.</p

Transgene Silencing and Transgene-Derived siRNA Production in Tobacco Plants Homozygous for an Introduced AtMYB90 Construct

Transgenic tobacco (Nicotiana tabacum) lines were engineered to ectopically over-express AtMYB90 (PAP2), an R2–R3 Myb gene associated with regulation of anthocyanin production in Arabidopsis thaliana. Independently transformed transgenic lines, Myb27 and Myb237, accumulated large quantities of anthocyanin, generating a dark purple phenotype in nearly all tissues. After self-fertilization, some progeny of the Myb27 line displayed an unexpected pigmentation pattern, with most leaves displaying large sectors of dramatically reduced anthocyanin production. The green-sectored 27Hmo plants were all found to be homozygous for the transgene and, despite a doubled transgene dosage, to have reduced levels of AtMYB90 mRNA. The observed reduction in anthocyanin pigmentation and AtMYB90 mRNA was phenotypically identical to the patterns seen in leaves systemically silenced for the AtMYB90 transgene, and was associated with the presence of AtMYB90-derived siRNA homologous to both strands of a portion of the AtMYB90 transcribed region. Activation of transgene silencing in the Myb27 line was triggered when the 35S::AtMYB90 transgene dosage was doubled, in both Myb27 homozygotes, and in plants containing one copy of each of the independently segregating Myb27 and Myb237 transgene loci. Mapping of sequenced siRNA molecules to the Myb27 TDNA (including flanking tobacco sequences) indicated that the 3′ half of the AtMYB90 transcript is the primary target for siRNA associated silencing in both homozygous Myb27 plants and in systemically silenced tissues. The transgene within the Myb27 line was found to consist of a single, fully intact, copy of the AtMYB90 construct. Silencing appears to initiate in response to elevated levels of transgene mRNA (or an aberrant product thereof) present within a subset of leaf cells, followed by spread of the resulting small RNA to adjacent leaf tissues and subsequent amplification of siRNA production

Особливості державного регулювання інвестиційно-інноваційної діяльності, в сфері екології

BACKGROUND: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. METHODS: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. RESULTS: The 245,782 cohort members contributed 3,229,220 person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m(3)), PM10 S (1.58; 1.03-2.44 per 200 ng/m(3)), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m(3)) and PM10 K (1.17; 1.02-1.33 per 100 ng/m(3)). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. CONCLUSIONS: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important