@article{StandfussPospisilKlein2012, author = {Standfuß, Christoph and Pospisil, Heike and Klein, Andreas}, title = {SNP microarray analyses reveal copy number alterations and progressive genome reorganization during tumor development in SVT/t driven mice breast cancer}, series = {BMC Cancer}, volume = {12}, journal = {BMC Cancer}, number = {380}, issn = {1471-2407}, doi = {10.1186/1471-2407-12-380}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-6414}, pages = {15}, year = {2012}, abstract = {Tumor development is known to be a stepwise process involving dynamic changes that affect cellular integrity and cellular behavior. This complex interaction between genomic organization and gene, as well as protein expression is not yet fully understood. Tumor characterization by gene expression analyses is not sufficient, since expression levels are only available as a snapshot of the cell status. So far, research has mainly focused on gene expression profiling or alterations in oncogenes, even though DNA microarray platforms would allow for high-throughput analyses of copy number alterations (CNAs).}, language = {en} } @misc{StandfussKleinPospisil2013, author = {Standfuß, Christoph and Klein, Andreas and Pospisil, Heike}, title = {Einfluss von Kopienzahlvariationen auf die Tumorentwicklung}, series = {Wissenschaftliche Beitr{\"a}ge 2013}, volume = {17}, journal = {Wissenschaftliche Beitr{\"a}ge 2013}, issn = {0949-8214}, doi = {10.15771/0949-8214_2013_1_5}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-3435}, pages = {27 -- 30}, year = {2013}, abstract = {Tumorentstehung ist ein Prozess, bei dem die Abl{\"a}ufe innerhalb der Zelle schrittweise ver{\"a}ndert werden. Die vielf{\"a}ltigen Interaktionen bei der Tumorentstehung sind jedoch bislang nicht vollst{\"a}ndig erforscht. Bisher wurden vorwiegend Genexpressionsanalysen genutzt, die jedoch nur eine Zeitaufnahme aller Genexpressionen innerhalb der Zelle darstellen und somit allein nicht ausreichend zur Charakterisierung eines Tumors. Wir haben mithilfe von Affymetrix Mouse Diversity Genotyping Microarrays Mausbrustdr{\"u}sengewebe entsprechend unserem Dreistufen-Mausmodell analysiert und die Kopienzahl{\"a}nderungen berechnet. Wir fanden eine zunehmende stufenweise {\"A}nderung von den transgenen zu den Tumorproben. Die Berechnung von chromosomalen Segmenten mit gleicher Kopienzahl zeigte deutliche Fragmentmuster. Unsere Analysen zeigen, dass die Tumorentstehung ein schrittweiser Prozess ist, der sowohl durch Amplifikationen als auch Deletionen chromosomaler Abschnitte definiert ist. Wir fanden charakteristisch konservierte Fragmentierungsmuster und individuelle Unterschiede welche zur Tumorgenese beitragen.}, language = {de} } @article{KleinPospisil2014, author = {Klein, Andreas and Pospisil, Heike}, title = {Gene Expression Profiling of Pancreatic Cancer Reveals a Significant Deregulation of the TGF-β Pathway and the Discovery of Genes for Prognosis}, series = {Global Journal of Human Genetics \& Gene Therapy}, volume = {2}, journal = {Global Journal of Human Genetics \& Gene Therapy}, number = {1}, issn = {2311-0309}, doi = {10.14205/2311-0309.2014.02.01.3}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-6519}, pages = {30 -- 39}, year = {2014}, abstract = {We have re-analyzed previously published gene expression data from ninety-four pancreatic ductal adenocarcinomas (PDAC) samples. We determined the gene expression profile of genes differentially expressed in PDAC compared to non-malignant pancreatic tissue. Using the 100 top-ranked genes, we were able to discriminate between PDAC and non-malignant pancreatic tissue. A hierarchical cluster analysis revealed only a 6 \% false discovery rate. The prognostic strength of these discriminative genes was underscored by a SVM classification and 3-fold cross validation with an 89 \% correct class assignment. The annotation of the 100 top-ranked genes revealed that most of the genes were involved in the processes of signal transduction, cell adhesion, extracellular matrix organization and cell migration. The most greatly affected signal cascade was the transforming growth factor β receptor signaling pathway, which was significantly enriched in the top-ranked genes. Furthermore, we identified eleven genes that were associated with good prognosis.}, language = {en} }