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We evaluated gene expression in the peripheral blood of Mayak workers in relationship to occupational chronic exposure to identify permanent post-exposure signatures. The Mayak workers had experienced either a combined exposure to incorporated (239)Pu and external gamma rays (n = 82) or exposure to external gamma rays (n = 18). Fifty unexposed individuals served as controls. Peripheral blood was collected and then the RNA was isolated, converting it into cDNA and stored at -20°C. In a previous study at stage I, we screened the mRNA and microRNA transcriptome using 40 of the 150 samples and identified 95 mRNAs and 45 microRNAs. In stage II of this study, we now validated our 140 candidate genes using the qRT-PCR technique for the remaining 92 blood samples (18 samples were lost due to methodological reasons). We analyzed associations of normalized gene expression values in linear models separately for both exposure types (continuous and categorical scales) and adjusted for exposure age as well as stratified by gender. After further adjustment for confounders such as chronic non-cancer diseases or age at biosampling, mostly binary (on/off) dose-to-gene relationships were found for 15 mRNAs and 15 microRNAs, of which 8 mRNAs and 6 microRNAs remained significant after Bonferroni correction. Almost all of them were associated with plutonium incorporation and gender. Our study provides mRNA and microRNA gene expression changes dependent on the exposure type and gender, which occur and seem to persist after chronic radiation exposures supporting the concept of permanent post-exposure signatures.

Introduction: Mesenchymal stem cells (MSCs) are considered to be the most promising stem cell type for cell-based therapies in regenerative medicine. Based on their potential to home to diseased body sites following a therapeutically application, these cells could (i) differentiate then into organspecific cell types to locally restore injured cells or, most prominently, (ii) foster tissue regeneration including immune modulations more indirectly by secretion of protective growth factors and cytokines. As tissue-resident stem cells of mesenchymal origin, these cells are morphologically and even molecularly-at least concerning the classical marker genes-indistinguishable from similar lineage cells, particularly fibroblasts. Methods: Here we used microarray-based gene expression and global DNA methylation analyses as well as accompanying computational tools in order to specify differences between MSCs and fibroblasts, to further unravel potential identity genes and to highlight MSC signaling pathways with regard to their trophic and immunosuppressive action. Results: We identified 1352 differentially expressed genes, of which in the MSCs there is a strong signature for e.g., KRAS signaling, known to play essential role in stemness maintenance, regulation of coagulation and complement being decisive for resolving inflammatory processes, as well as of wound healing particularly important for their regenerative capacity. Genes upregulated in fibroblasts addressed predominately transcription and biosynthetic processes and mapped morphological features of the tissue. Concerning the cellular identity, we specified the already known HOX code for MSCs, established a potential HOX code for fibroblasts, and linked certain HOX genes to functional cell-type-specific properties. Accompanied methylation profiles revealed numerous regions, especially in HOX genes, being differentially methylated, which might provide additional biomarker potential. Discussion: Conclusively, transcriptomic together with epigenetic signatures can be successfully be used for the definition (cellular identity) of MSCs versus fibroblasts as well as for the determination of the superior functional properties of MSCs, such as their immunomodulatory potential. [ABSTRACT FROM AUTHOR]

We herein report on changes in gene expression after radiation exposure to iodine-131 from the Chernobyl accident in the Ukrainian-American thyroid cohort and to external gamma ray or internal plutonium exposure in the Mayak Production Association radiation workers. Taking advantage of access to tissue samples from the thyroid cancer cases in the Ukrainian-American cohort, our group tried to identify candidate genes to discriminate spontaneously occurring thyroid cancers from thyroid cancers caused by radiation exposure. We also examined gene expression changes in normal and cancerous thyroid tissue in relation to iodine-131 dose separately. Gene expression changes in the peripheral blood of radiation exposed Mayak workers were examined to elucidate the dose-to-gene and gene-to-health (e.g. cardiovascular disease) relationships. Results of both projects are discussed under the aspect of dose-response relationships (dose-to-gene) and clinical outcome relationships (gene-to-effect) in light of how mechanistic data can be translated into actionable knowledge for radiation protection or clinical purposes. [ABSTRACT FROM AUTHOR]

Gene expression time-course experiments allow to study the dynamics of transcriptomic changes in cells exposed to different stimuli. However, most approaches for the reconstruction of gene association networks (GANs) do not propose prior-selection approaches tailored to time-course transcriptome data. Here, we present a workflow for the identification of GANs from time-course data using prior selection of genes differentially expressed over time identified by natural cubic spline regression modeling (NCSRM). The workflow comprises three major steps: 1) the identification of differentially expressed genes from time-course expression data by employing NCSRM, 2) the use of regularized dynamic partial correlation as implemented in GeneNet to infer GANs from differentially expressed genes and 3) the identification and functional characterization of the key nodes in the reconstructed networks. The approach was applied on a time-resolved transcriptome data set of radiation-perturbed cell culture models of non-tumor cells with normal and increased radiation sensitivity. NCSRM detected significantly more genes than another commonly used method for time-course transcriptome analysis (BETR). While most genes detected with BETR were also detected with NCSRM the false-detection rate of NCSRM was low (3%). The GANs reconstructed from genes detected with NCSRM showed a better overlap with the interactome network Reactome compared to GANs derived from BETR detected genes. After exposure to 1 Gy the normal sensitive cells showed only sparse response compared to cells with increased sensitivity, which exhibited a strong response mainly of genes related to the senescence pathway. After exposure to 10 Gy the response of the normal sensitive cells was mainly associated with senescence and that of cells with increased sensitivity with apoptosis. We discuss these results in a clinical context and underline the impact of senescence-associated pathways in acute radiation response of normal cells. The workflow of this novel approach is implemented in the open-source Bioconductor R-package splineTimeR. [ABSTRACT FROM AUTHOR]

Histone demethylases have recently gained interest as potential targets in cancer treatment and several histone demethylases have been implicated in the DNA damage response. We investigated the effects of siRNA-mediated depletion of histone demethylase Jarid1A (KDM5A, RBP2), which demethylates transcription activating tri- and dimethylated lysine 4 at histone H3 (H3K4me3/me2), on growth characteristics and cellular response to radiation in several cancer cell lines. In unirradiated cells Jarid1A depletion lead to histone hyperacetylation while not affecting cell growth. In irradiated cells, depletion of Jarid1A significantly increased cellular radiosensitivity. Unexpectedly, the hyperacetylation phenotype did not lead to disturbed accumulation of DNA damage response and repair factors 53BP1, BRCA1, or Rad51 at damage sites, nor did it influence resolution of radiation-induced foci or rejoining of reporter constructs. We conclude that the radiation sensitivity observed following depletion of Jarid1A is not caused by a deficiency in repair of DNA double-strand breaks. [ABSTRACT FROM AUTHOR]

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method "miRlastic", which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic. [ABSTRACT FROM AUTHOR]

A previous study on papillary thyroid carcinomas (PTC) in young patients who were exposed to 131iodine from the Chernobyl fallout revealed an exclusive gain of chromosomal band 7q11.23 in exposed cases compared to an age-matched control cohort. CLIP2, a gene located within band 7q11.23 was shown to be differentially expressed between exposed and nonexposed cases at messenger RNA and protein level. Therefore, a standardized procedure for CLIP2 typing of PTCs has been developed in a follow-up study. Here we used CLIP2 typing data on 117 post-Chernobyl PTCs from two cohorts of exposed patients with individual dose estimates and 24 non-exposed controls to investigate a possible quantitative dose-response relationship of the CLIP2 marker. The 'Genrisk-T' cohort consisted of 45 PTCs and the 'UkrAm' cohort of 72 PTCs. Both cohorts differed in mean dose (0.59 Gy Genrisk-T, 1.2 Gy UkrAm) and mean age at exposure (AaE) (2 years Genrisk-T, 8 years UkrAm), whilst the median latency (16 years Genrisk-T, 18 years UkrAm) was comparable. We analyzed the association between the binary CLIP2 typing and continuous thyroid dose with logistic regression. A clear positive dose-response relationship was found for young PTC cases [age at operation (AaO) < 20 years, AaE < 5 years]. In the elder age group a higher proportion of sporadic tumors is assumed due to a negligible dose response, suggesting different molecular mechanisms in sporadic and radiation-induced cases. This is further supported by the association of elder patients (AaO > 20 years) with positivity for BRAF V600E mutation. [ABSTRACT FROM AUTHOR]

Maximisation of the ratio of normal tissue preservation and tumour cell reduction is the main concept of radiotherapy alone or combined with chemo-, immuno- or biologically targeted therapy. The foremost parameter influencing this ratio is radiation sensitivity and its modulation towards a more efficient killing of tumour cells and a better preservation of normal tissue at the same time is the overall aim of modern therapy schemas. Nevertheless, this requires a deep understanding of the molecular mechanisms of radiation sensitivity in order to identify its key players as potential therapeutic targets. Moreover, the success of conventional approaches that tried to statistically associate altered radiation sensitivity with any molecular phenotype such as gene expression proofed to be somewhat limited since the number of clinically used targets is rather sparse. However, currently a paradigm shift is taking place from pure frequentistic association analysis to the rather holistic systems biology approach that seeks to mathematically model the system to be investigated and to allow the prediction of an altered phenotype as the function of one single or a signature of biomarkers. Integrative systems biology also considers the data from different molecular levels such as the genome, transcriptome or proteome in order to partially or fully comprehend the causal chain of molecular mechanisms. An example for the application of this concept currently carried out at the Clinical Cooperation Group "Personalized Radiotherapy in Head and Neck Cancer" of the Helmholtz-Zentrum München and the LMU Munich is described. This review article strives for providing a compact overview on the state of the art of systems biology, its actual challenges, potential applications, chances and limitations in radiation oncology research working towards improved personalised therapy concepts using this relatively new methodology. [ABSTRACT FROM AUTHOR]

For an identification of novel candidate genes in thyroid tumourigenesis, we have investigated gene copy number changes in a Trk-T1 transgenic mouse model of thyroid neoplasia. For this aim, 30 thyroid tumours from Trk-T1 transgenics were investigated by comparative genomic hybridisation. Recurrent gene copy number alterations were identified and genes located in the altered chromosomal regions were analysed by Gene Ontology term enrichment analysis in order to reveal gene functions potentially associated with thyroid tumourigenesis. In thyroid neoplasms from Trk-T1 mice, a recurrent gain on chromosomal bands 1C4-E2.3 (10.0% of cases), and losses on 3H1-H3 (13.3%), 4D2.3-E2 (43.3%) and 14E4-E5 (6.7%) were identified. The genes Twist2, Ptma, Pde6d, Bmpr1b, Pdlim5, Unc5c, Srm, Trp73, Ythdf2, Taf12 and Slitrk5 are located in these chromosomal bands. Copy number changes of these genes were studied by fluorescence in situ hybridisation on 30 human papillary thyroid carcinoma (PTC) samples and altered gene expression was studied by qRT-PCR analyses in 67 human PTC. Copy number gains were detected in 83% of cases for TWIST2 and in 100% of cases for PTMA and PDE6D. DNA losses of SLITRK1 and SLITRK5 were observed in 21% of cases and of SLITRK6 in 16% of cases. Gene expression was significantly up-regulated for UNC5C and TP73 and significantly down-regulated for SLITRK5 in tumours compared with normal tissue. In conclusion, a global genomic copy number analysis of thyroid tumours from Trk-T1 transgenic mice revealed a number of novel gene alterations in thyroid tumourigenesis that are also prevalent in human PTCs. [ABSTRACT FROM AUTHOR]

Background: An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms. Results: We describe, illustrate and discuss six matching procedures. They are implemented in the R-package sigaR (available from Bioconductor). The principles underlying the presented matching procedures are generic, and can be combined to form new matching approaches or be applied to the matching of other platforms. Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes. Conclusions: Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new. They have been implemented in the R-package sigaR, available from Bioconductor. [ABSTRACT FROM AUTHOR]

Osteosarcomas are genetically complex tumors with abundant structural and numerical alterations. The molecular pathogenesis of the disease is, however, still poorly understood. Aside from various oncogenes and tumor suppressor genes, deregulated microRNAs (miRNAs) are known to influence tumor development and biology. We therefore investigated six well-established osteosarcoma cell lines (HOS58, U2-OS, Saos-2, MNNG/HOS, SJSA-1, and MG-63) for genome-wide miRNA expression (miRBase Version 15.0, http://www.mirbase.org/) and correlated our findings with gene expression. Cultured osteoblasts (hFOB 1.19) and mesenchymal stem cells (L87/4) were used as normal references. Focusing only on miRNAs that were deregulated in the majority of osteosarcoma cell lines, we identified several miRNAs with oncogenic and tumor suppressor properties, including various members of the oncogenic miR-17-92 cluster. In addition, several genes involved in differentiation (RGMB, LRRC17), cell cycle control (CCNE1), and apoptosis (LIMA1, CAMK2N1) were found to be deregulated in osteosarcoma cell lines, most likely due to altered miRNA expression patterns. Our findings indicate a crucial impact of deregulated miRNAs with consecutive changes in gene expression in osteosarcomas, which strongly suggests pathogenetic and potentially therapeutic implications. [ABSTRACT FROM AUTHOR]

Abstract: Thyroid cancer derived from the follicular cell is characterised by specific gene alterations that are closely linked to the various pathological types comprising papillary, follicular and anaplastic thyroid cancer. However, the correlation between molecular biology and pathology is not absolute, since about 30% of cases do not harbour the typical gene alterations. This situation, coupled with the demonstration of genetic heterogeneity in thyroid cancer, is a strong motivation for the search of novel gene alterations. Chromosomal aberrations are a good starting point to initiate this search and therefore the current knowledge on chromosomal alterations in thyroid follicular-cell neoplasia is reviewed in this article. An overview on molecular cytogenetic approaches for this strategy is also provided. The identification of novel genetic markers in thyroid cancer will be further improved by integrative approaches combining data from genomic and expression analyses with clinical data. This approach is powerful to identify genetic markers as well as new therapeutic targets in follicular-cell thyroid cancer. [Copyright &y& Elsevier]