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- Djureinovic, Dijana, et al.
(author)
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Profiling cancer testis antigens in non-small-cell lung cancer
- 2016
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In: JCI INSIGHT. - : American Society for Clinical Investigation. - 2379-3708. ; 1:10
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Journal article (peer-reviewed)abstract
- Cancer testis antigens (CTAs) are of clinical interest as biomarkers and present valuable targets for immunotherapy. To comprehensively characterize the CTA landscape of non-small-cell lung cancer (NSCLC), we compared RNAseq data from 199 NSCLC tissues to the normal transcriptome of 142 samples from 32 different normal organs. Of 232 CTAs currently annotated in the Caner Testis Database (CTdatabase), 96 were confirmed in NSCLC. To obtain an unbiased CTA profile of NSCLC, we applied stringent criteria on our RNAseq data set and defined 90 genes as CTAs, of which 55 genes were not annotated in the CTdatabase, thus representing potential new CTAs. Cluster analysis revealed that CTA expression is histology dependent and concurrent expression is common. IHC confirmed tissue-specific protein expression of selected new CTAs (TKTL1, TGIF2LX, VCX, and CXORF67). Furthermore, methylation was identified as a regulatory mechanism of CTA expression based on independent data from The Cancer Genome Atlas. The proposed prognostic impact of CTAs in lung cancer was not confirmed, neither in our RNAseq cohort nor in an independent meta-analysis of 1,117 NSCLC cases. In summary, we defined a set of 90 reliable CTAs, including information on protein expression, methylation, and survival association. The detailed RNAseq catalog can guide biomarker studies and efforts to identify targets for immunotherapeutic strategies.
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| 3. |
- Grinberg, Marianna, et al.
(author)
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Toxicogenomics directory of chemically exposed human hepatocytes
- 2014
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In: Archives of Toxicology. - : Springer Science and Business Media LLC. - 1432-0738 .- 0340-5761. ; 88:12, s. 2261-2287
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Journal article (peer-reviewed)abstract
- A long-term goal of numerous research projects is to identify biomarkers for in vitro systems predicting toxicity in vivo. Often, transcriptomics data are used to identify candidates for further evaluation. However, a systematic directory summarizing key features of chemically influenced genes in human hepatocytes is not yet available. To bridge this gap, we used the Open TG-GATES database with Affymetrix files of cultivated human hepatocytes incubated with chemicals, further sets of gene array data with hepatocytes from human donors generated in this study, and publicly available genome-wide datasets of human liver tissue from patients with non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular cancer (HCC). After a curation procedure, expression data of 143 chemicals were included into a comprehensive biostatistical analysis. The results are summarized in the publicly available toxicotranscriptomics directory (http://wiki.toxbank.net/toxicogenomics-map/) which provides information for all genes whether they are up- or downregulated by chemicals and, if yes, by which compounds. The directory also informs about the following key features of chemically influenced genes: (1) Stereotypical stress response. When chemicals induce strong expression alterations, this usually includes a complex but highly reproducible pattern named 'stereotypical response.' On the other hand, more specific expression responses exist that are induced only by individual compounds or small numbers of compounds. The directory differentiates if the gene is part of the stereotypical stress response or if it represents a more specific reaction. (2) Liver disease-associated genes. Approximately 20 % of the genes influenced by chemicals are up- or downregulated, also in liver disease. Liver disease genes deregulated in cirrhosis, HCC, and NASH that overlap with genes of the aforementioned stereotypical chemical stress response include CYP3A7, normally expressed in fetal liver; the phase II metabolizing enzyme SULT1C2; ALDH8A1, known to generate the ligand of RXR, one of the master regulators of gene expression in the liver; and several genes involved in normal liver functions: CPS1, PCK1, SLC2A2, CYP8B1, CYP4A11, ABCA8, and ADH4. (3) Unstable baseline genes. The process of isolating and the cultivation of hepatocytes was sufficient to induce some stress leading to alterations in the expression of genes, the so-called unstable baseline genes. (4) Biological function. Although more than 2,000 genes are transcriptionally influenced by chemicals, they can be assigned to a relatively small group of biological functions, including energy and lipid metabolism, inflammation and immune response, protein modification, endogenous and xenobiotic metabolism, cytoskeletal organization, stress response, and DNA repair. In conclusion, the introduced toxicotranscriptomics directory offers a basis for a rationale choice of candidate genes for biomarker evaluation studies and represents an easy to use source of background information on chemically influenced genes.
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| 4. |
- Jabs, Verena, et al.
(author)
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Integrative analysis of genome-wide gene copy number changes and gene expression in non-small cell lung cancer
- 2017
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:11
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Journal article (peer-reviewed)abstract
- Non-small cell lung cancer (NSCLC) represents a genomically unstable cancer type with extensive copy number aberrations. The relationship of gene copy number alterations and subsequent mRNA levels has only fragmentarily been described. The aim of this study was to conduct a genome-wide analysis of gene copy number gains and corresponding gene expression levels in a clinically well annotated NSCLC patient cohort (n = 190) and their association with survival. While more than half of all analyzed gene copy number-gene expression pairs showed statistically significant correlations (10,296 of 18,756 genes), high correlations, with a correlation coefficient >0.7, were obtained only in a subset of 301 genes (1.6%), including KRAS, EGFR and MDM2. Higher correlation coefficients were associated with higher copy number and expression levels. Strong correlations were frequently based on few tumors with high copy number gains and correspondingly increased mRNA expression. Among the highly correlating genes, GO groups associated with posttranslational protein modifications were particularly frequent, including ubiquitination and neddylation. In a meta-analysis including 1,779 patients we found that survival associated genes were overrepresented among highly correlating genes (61 of the 301 highly correlating genes, FDR adjusted p<0.05). Among them are the chaperone CCT2, the core complex protein NUP107 and the ubiquitination and neddylation associated protein CAND1. In conclusion, in a comprehensive analysis we described a distinct set of highly correlating genes. These genes were found to be overrepresented among survival-associated genes based on gene expression in a large collection of publicly available datasets.
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| 5. |
- Lohr, Miriam, et al.
(author)
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Identification of sample annotation errors in gene expression datasets
- 2015
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In: Archives of Toxicology. - : Springer Science and Business Media LLC. - 0340-5761 .- 1432-0738. ; 89:12, s. 2265-2272
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Journal article (peer-reviewed)abstract
- The comprehensive transcriptomic analysis of clinically annotated human tissue has found widespread use in oncology, cell biology, immunology, and toxicology. In cancer research, microarray-based gene expression profiling has successfully been applied to subclassify disease entities, predict therapy response, and identify cellular mechanisms. Public accessibility of raw data, together with corresponding information on clinicopathological parameters, offers the opportunity to reuse previously analyzed data and to gain statistical power by combining multiple datasets. However, results and conclusions obviously depend on the reliability of the available information. Here, we propose gene expression-based methods for identifying sample misannotations in public transcriptomic datasets. Sample mix-up can be detected by a classifier that differentiates between samples from male and female patients. Correlation analysis identifies multiple measurements of material from the same sample. The analysis of 45 datasets (including 4913 patients) revealed that erroneous sample annotation, affecting 40 % of the analyzed datasets, may be a more widespread phenomenon than previously thought. Removal of erroneously labelled samples may influence the results of the statistical evaluation in some datasets. Our methods may help to identify individual datasets that contain numerous discrepancies and could be routinely included into the statistical analysis of clinical gene expression data.
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| 7. |
- Micke, Patrick, et al.
(author)
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Aberrantly activated claudin 6 and 18.2 as potential therapy targets in non-small-cell lung cancer
- 2014
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In: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 135:9, s. 2206-2214
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Journal article (peer-reviewed)abstract
- Claudins (CLDNs) are central components of tight junctions that regulate epithelial-cell barrier function and polarity. Altered CLDN expression patterns have been demonstrated in numerous cancer types and lineage-specific CLDNs have been proposed as therapy targets. The objective of this study was to assess which fraction of patients with non-small-cell lung cancer (NSCLC) express CLDN6 and CLDN18 isoform 2 (CLDN18.2). Protein expression of CLDN6 and CLDN18.2 was examined by immunohistochemistry on a tissue microarray (n=355) and transcript levels were supportively determined based on gene expression microarray data from fresh-frozen NSCLC tissues (n=196). Both were analyzed with regard to frequency, distribution and association with clinical parameters. Immunohistochemical analysis of tissue sections revealed distinct membranous positivity of CLDN6 (6.5%) and CLDN18.2 (3.7%) proteins in virtually non-overlapping subgroups of adenocarcinomas and large-cell carcinomas. Pneumocytes and bronchial epithelial cells were consistently negative. Corresponding to the protein expression, in subsets of non-squamous lung carcinoma high mRNA levels of CLDN6 (7-16%) and total CLDN18 (5-12%) were observed. Protein expression correlated well with total mRNA expression of the corresponding gene (rho=0.4-0.8). CLDN18.2 positive tumors were enriched among slowly proliferating, thyroid transcription factor 1 (TTF-1)-negative adenocarcinomas, suggesting that isoform-specific CLDN expression may delineate a specific subtype. Noteworthy, high CLDN6 protein expression was associated with worse prognosis in lung adenocarcinoma in the univariate [hazard ratio (HR): 1.8; p=0.03] and multivariate COX regression model (HR: 1.9; p=0.02). These findings encourage further clinical exploration of targeting ectopically activated CLDN expression as a valuable treatment concept in NSCLC.
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