References of "Dittmar, Gunnar"
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See detailDeconvolution of Transcriptomes and miRNomes by Independent Component Analysis Provides Insights Into Biological Processes and Clinical Outcomes of Melanoma Patients
Nazarov, Petr V.; Wienecke-Baldacchino, Anke K.; Zinovyev, Andrei et al

in BMC Medical Genomics (2019), 12 (1)(132),

Background: The amount of publicly available cancer-related“omics”data is constantly growing and can potentially be used to gain insights into the tumour biology of new cancer patients, their diagnosis ... [more ▼]

Background: The amount of publicly available cancer-related“omics”data is constantly growing and can potentially be used to gain insights into the tumour biology of new cancer patients, their diagnosis and suitable treatment options. However, the integration of different datasets is not straightforward and requires specialized approaches to deal with heterogeneity at technical and biological levels. Methods: Here we present a method that can overcome technical biases, predict clinically relevant outcomes and identify tumour-related biological processes in patients using previously collected large discovery datasets. The approach is based on independent component analysis (ICA)–an unsupervised method of signal deconvolution. We developed parallel consensus ICA that robustly decomposes transcriptomics datasets into expression profiles with minimal mutual dependency. Results: By applying the method to a small cohort of primary melanoma and control samples combined with a large discovery melanoma dataset, we demonstrate that our method distinguishes cell-type specific signals from technical biases and allows to predict clinically relevant patient characteristics. We showed the potential of the method to predict cancer subtypes and estimate the activity of key tumour-related processes such as immune response, angiogenesis and cell proliferation. ICA-based risk score was proposed and its connection to patient survival was validated with an independent cohort of patients. Additionally, through integration of components identified for mRNA and miRNA data, the proposed method helped deducing biological functions of miRNAs, which would otherwise not be possible. Conclusions: We present a method that can be used to map new transcriptomic data from cancer patient samples onto large discovery datasets. The method corrects technical biases, helps characterizing activity of biological processes or cell types in the new samples and provides the prognosis of patient survival [less ▲]

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See detailMetabolic Profiling as Well as Stable Isotope Assisted Metabolic and Proteomic Analysis of RAW 264.7 Macrophages Exposed to Ship Engine Aerosol Emissions: Different Effects of Heavy Fuel Oil and Refined Diesel Fuel.
Sapcariu, Sean UL; Kanashova, Tamara; Dilger, Marco et al

in PloS one (2016), 11(6), 0157964

Exposure to air pollution resulting from fossil fuel combustion has been linked to multiple short-term and long term health effects. In a previous study, exposure of lung epithelial cells to engine ... [more ▼]

Exposure to air pollution resulting from fossil fuel combustion has been linked to multiple short-term and long term health effects. In a previous study, exposure of lung epithelial cells to engine exhaust from heavy fuel oil (HFO) and diesel fuel (DF), two of the main fuels used in marine engines, led to an increased regulation of several pathways associated with adverse cellular effects, including pro-inflammatory pathways. In addition, DF exhaust exposure was shown to have a wider response on multiple cellular regulatory levels compared to HFO emissions, suggesting a potentially higher toxicity of DF emissions over HFO. In order to further understand these effects, as well as to validate these findings in another cell line, we investigated macrophages under the same conditions as a more inflammation-relevant model. An air-liquid interface aerosol exposure system was used to provide a more biologically relevant exposure system compared to submerged experiments, with cells exposed to either the complete aerosol (particle and gas phase), or the gas phase only (with particles filtered out). Data from cytotoxicity assays were integrated with metabolomics and proteomics analyses, including stable isotope-assisted metabolomics, in order to uncover pathways affected by combustion aerosol exposure in macrophages. Through this approach, we determined differing phenotypic effects associated with the different components of aerosol. The particle phase of diluted combustion aerosols was found to induce increased cell death in macrophages, while the gas phase was found more to affect the metabolic profile. In particular, a higher cytotoxicity of DF aerosol emission was observed in relation to the HFO aerosol. Furthermore, macrophage exposure to the gas phase of HFO leads to an induction of a pro-inflammatory metabolic and proteomic phenotype. These results validate the effects found in lung epithelial cells, confirming the role of inflammation and cellular stress in the response to combustion aerosols. [less ▲]

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See detailSimultaneous extraction of proteins and metabolites from cells in culture
Sapcariu, Sean UL; Kanashova, Tamara; Weindl, Daniel UL et al

in MethodsX (2014)

Detailed reference viewed: 171 (17 UL)