Jung, Klaus

[["dc.bibliographiccitation.firstpage","9"],["dc.bibliographiccitation.lastpage","100"],["dc.contributor.author","Leha, Andreas"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2020-04-02T10:43:45Z"],["dc.date.available","2020-04-02T10:43:45Z"],["dc.date.issued","2013"],["dc.identifier.doi","10.4230/OASIcs.GCB.2013.90"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63516"],["dc.relation.eisbn","978-3-939897-59-0"],["dc.relation.eventlocation","Dagstuhl"],["dc.relation.eventstart","2013"],["dc.relation.ispartof","German Conference on Bioinformatics 2013"],["dc.title","Utilization of ordinal response structures in classification with high-dimensional expression data"],["dc.type","conference_paper"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","127"],["dc.bibliographiccitation.journal","BMC Bioinformatics"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Leha, Andreas"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Jung, Klaus"],["dc.date.accessioned","2018-11-07T08:56:54Z"],["dc.date.available","2018-11-07T08:56:54Z"],["dc.date.issued","2011"],["dc.description.abstract","Background: Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e. g. cancer. Frequently, microarray studies are performed to identify genes of which the expression levels in pretherapeutic tissue samples are correlated to survival times of patients. Typically, such a study can take several years until the full planned sample size is available. Therefore, interim analyses are desirable, offering the possibility of stopping the study earlier, or of performing additional laboratory experiments to validate the role of the detected genes. While many methods correcting the multiple testing bias introduced by interim analyses have been proposed for studies of one single feature, there are still open questions about interim analyses of multiple features, particularly of high-dimensional microarray data, where the number of features clearly exceeds the number of samples. Therefore, we examine false discovery rates and power rates in microarray experiments performed during interim analyses of survival studies. In addition, the early stopping based on interim results of such studies is evaluated. As stop criterion we employ the achieved average power rate, i.e. the proportion of detected true positives, for which a new estimator is derived and compared to existing estimators. Results: In a simulation study, pre-specified levels of the false discovery rate are maintained in each interim analysis, where reduced levels as used in classical group sequential designs of one single feature are not necessary. Average power rates increase with each interim analysis, and many studies can be stopped prior to their planned end when a certain pre-specified power rate is achieved. The new estimator for the power rate slightly deviates from the true power rate but is comparable to other estimators. Conclusions: Interim analyses of microarray experiments can provide evidence for early stopping of long-term survival studies. The developed simulation framework, which we also offer as a new R package 'SurvGenesInterim' available at http://survgenesinter.R-Forge.R-Project.org, can be used for sample size planning of the evaluated study design."],["dc.identifier.doi","10.1186/1471-2105-12-127"],["dc.identifier.isi","000290784600001"],["dc.identifier.pmid","21527044"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/6343"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/23260"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1471-2105"],["dc.rights","CC BY 2.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.0"],["dc.title","Sequential interim analyses of survival data in DNA microarray experiments"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","400"],["dc.bibliographiccitation.issue","4_suppl"],["dc.bibliographiccitation.journal","Journal of Clinical Oncology"],["dc.bibliographiccitation.lastpage","400"],["dc.bibliographiccitation.volume","31"],["dc.contributor.author","Sprenger, Thilo"],["dc.contributor.author","Gaedcke, Jochen"],["dc.contributor.author","Conradi, Lena-Christin"],["dc.contributor.author","Jo, Peter"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Beissbarth, Tim"],["dc.contributor.author","Homayounfar, Kia"],["dc.contributor.author","Ghadimi, B. Michael"],["dc.contributor.author","Liersch, Torsten"],["dc.date.accessioned","2022-06-08T07:57:20Z"],["dc.date.available","2022-06-08T07:57:20Z"],["dc.date.issued","2013"],["dc.description.abstract","400 Background: The role of the potential stem cell marker CD133 as a predictive or prognostic marker in multimodal rectal cancer treatment is currently under debate. While CD133 has been identified as a prognostic marker in rectal cancers after preoperative radiochemotherapy (RCT) it was recently characterized as a very unspecific feature for colorectal cancer stem cells. We therefore analyzed the association between CD133 expression and mutations in the proto-oncogenes K-Ras and PI3K in rectal cancer patients receiving neoadjuvant RCT. Methods: CD133 expression was evaluated immunhistochemically in pre-treatment biopsies and surgical specimens of 128 patients with locally advanced rectal cancers (cUICC II/III) treated with preoperative RCT within the phase-III German Rectal Cancer Trials. K-Ras mutations were analyzed by sequencing of exons 1, 2, and 3. PI3K mutations were detected by sequencing the p110α subunit (PIK3CA) and correlated with histopathologic parameters, tumor regression and survival. Results: CD133 expression was significantly associated with mutations in the K-Ras gene in both pre-treatment biopsies and post-treatment tumor specimens in uni- and multivariate analyses. However, no significant correlation was observed between CD133 and PI3K mutations. Post-treatment CD133 levels were correlated with neoadjuvant RCT (50.4 Gy/5-FU vs. 50.4 Gy/5-FU+Ox) and tumor regression grading. Anyway, there was no significant association between pre- and post-treatment CD133 expression and disease-free survival. Conclusions: CD133 expression levels are strongly associated with mutations in the K-Ras proto-oncogene in rectal cancers before and after preoperative RCT. Our results strengthen the hypothesis that CD133 is not a specific marker for colorectal stem cells but might be integrated in proliferation pathways like the ras-raf axis."],["dc.identifier.doi","10.1200/jco.2013.31.4_suppl.400"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/110058"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-575"],["dc.relation.eissn","1527-7755"],["dc.relation.issn","0732-183X"],["dc.title","Association of CD133 expression levels with the k-ras mutation status in rectal cancers before and after preoperative radiochemotherapy."],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","5640"],["dc.bibliographiccitation.lastpage","5640"],["dc.contributor.author","Gaedcke, Jochen"],["dc.contributor.author","Grade, Marian"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Wolff, Hendrik A."],["dc.contributor.author","Beissbarth, Tim"],["dc.contributor.author","Becker, Heinz"],["dc.contributor.author","Ried, Thomas"],["dc.contributor.author","Ghadimi, Michael"],["dc.date.accessioned","2022-06-08T07:57:08Z"],["dc.date.available","2022-06-08T07:57:08Z"],["dc.date.issued","2014"],["dc.identifier.doi","10.1158/1538-7445.AM10-5640"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/110007"],["dc.notes.intern","DOI-Import GROB-575"],["dc.publisher","American Association for Cancer Research"],["dc.relation.conference","Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC"],["dc.title","Abstract 5640: KRAS and BRAF in rectal cancer treated with preoperative chemoradiotherapy"],["dc.type","conference_paper"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","401"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Statistical Applications in Genetics and Molecular Biology"],["dc.bibliographiccitation.lastpage","414"],["dc.bibliographiccitation.volume","15"],["dc.contributor.author","Kruppa, Jochen"],["dc.contributor.author","Kramer, Frank"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Jung, Klaus"],["dc.date.accessioned","2018-11-07T10:07:53Z"],["dc.date.available","2018-11-07T10:07:53Z"],["dc.date.issued","2016"],["dc.description.abstract","As part of the data processing of high-throughput-sequencing experiments count data are produced representing the amount of reads that map to specific genomic regions. Count data also arise in mass spectrometric experiments for the detection of protein-protein interactions. For evaluating new computational methods for the analysis of sequencing count data or spectral count data from proteomics experiments artificial count data is thus required. Although, some methods for the generation of artificial sequencing count data have been proposed, all of them simulate single sequencing runs, omitting thus the correlation structure between the individual genomic features, or they are limited to specific structures. We propose to draw correlated data from the multivariate normal distribution and round these continuous data in order to obtain discrete counts. In our approach, the required distribution parameters can either be constructed in different ways or estimated from real count data. Because rounding affects the correlation structure we evaluate the use of shrinkage estimators that have already been used in the context of artificial expression data from DNA microarrays. Our approach turned out to be useful for the simulation of counts for defined subsets of features such as individual pathways or GO categories."],["dc.identifier.doi","10.1515/sagmb-2015-0082"],["dc.identifier.isi","000385368900003"],["dc.identifier.pmid","27655448"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/39364"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Walter De Gruyter Gmbh"],["dc.relation.issn","1544-6115"],["dc.relation.issn","2194-6302"],["dc.title","A simulation framework for correlated count data of features subsets in high-throughput sequencing or proteomics experiments"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","564"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Surgery"],["dc.bibliographiccitation.lastpage","570"],["dc.bibliographiccitation.volume","151"],["dc.contributor.author","Jo, Peter"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Grade, Marian"],["dc.contributor.author","Conradi, Lena-Christin"],["dc.contributor.author","Wolff, Hendrik Andreas"],["dc.contributor.author","Kitz, Julia"],["dc.contributor.author","Becker, Heinz"],["dc.contributor.author","Rüschoff, Josef R."],["dc.contributor.author","Hartmann, Arndt"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Müller-Dornieden, Annegret"],["dc.contributor.author","Ghadimi, Michael B."],["dc.contributor.author","Schneider-Stock, Regine"],["dc.contributor.author","Gaedcke, Jochen"],["dc.date.accessioned","2018-11-07T09:11:55Z"],["dc.date.available","2018-11-07T09:11:55Z"],["dc.date.issued","2012"],["dc.description.abstract","Background. Locally advanced rectal cancers are treated with preoperative radiochemotherapy (RCT). However, subsets of patients have no benefit from preoperative treatment. Since epigenetic modifications, including DNA methylation, may influence response to neoadjuvant treatment we studied the CpG island methylator phenotype (CIMP) in patients who received a 5-fluouracil based RCT Methods. One hundred fifty patients, with locally advanced rectal cancer, treated within a phase HI clinical trial (CAO/ARO/AIO-94 and -04), were included in this analysis. CIMP was assessed by methylation specific PCR (MSP) using RUNX3, SOCS1, NEUROG1, IGF2, and CACNA1G as a marker panel. Loss of mismatch repair gene (MMR) expression was assessed by immunohistochemistry for a subset of patients. KRAS and BRAF mutation status were assessed using Sanger sequencing. Results. The CIMP status could be established in all 150 patients. Fifteen (10%) revealed CIMP positivity >= 3 methylated promoters), whereas 135 patients (90%) where classified as CIMP negative. Analysis for MMR status. did not reveal any microsatellite instability (MSI). A single mutation of the BRAF gene (D594G) was detected. The KRAS gene (exon 1, 2, and 3) was mutated in 65 tumors (43%) but was not correlated to a specific CIMP status. Three- and 5-year disease-free survival was notably worse in CIMP positive patients (56% and 0% vs 80% and 75%; P < .01) suggesting an increased likelihood of poor clinical outcome (HR 5.5; 95% CI: [2.1, 13.9]). Conclusion. CIMP positivity, defined by methylation of at least 3 specific gene promoters, is an infrequent event in locally advanced rectal cancer. However it increases the likelihood of distant metastases. Therefore, the CIMP status may be included as a molecular marker for the identification of high-risk patients and might contribute to individual treatment stratification. (Surgery 2012;151:564-70.)"],["dc.identifier.doi","10.1016/j.surg.2011.08.013"],["dc.identifier.isi","000301996600010"],["dc.identifier.pmid","22001634"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/26829"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Mosby-elsevier"],["dc.relation.issn","0039-6060"],["dc.title","CpG island methylator phenotype infers a poor disease-free survival in locally advanced rectal cancer"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","36"],["dc.bibliographiccitation.journal","BMC Medical Genomics"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Opitz, Lennart"],["dc.contributor.author","Salinas-Riester, Gabriela"],["dc.contributor.author","Grade, Marian"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Jo, Peter"],["dc.contributor.author","Emons, Georg"],["dc.contributor.author","Ghadimi, Michael B."],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Gaedcke, Jochen"],["dc.date.accessioned","2018-11-07T08:40:26Z"],["dc.date.available","2018-11-07T08:40:26Z"],["dc.date.issued","2010"],["dc.description.abstract","Background: Gene expression profiling is a highly sensitive technique which is used for profiling tumor samples for medical prognosis. RNA quality and degradation influence the analysis results of gene expression profiles. The impact of this influence on the profiles and its medical impact is not fully understood. As patient samples are very valuable for clinical studies, it is necessary to establish criteria for the RNA quality to be able to use these samples in later analysis. Methods: To investigate the effects of RNA integrity on gene expression profiling, whole genome expression arrays were used. We used tumor biopsies from patients diagnosed with locally advanced rectal cancer. To simulate degradation, the isolated total RNA of all patients was subjected to heat-induced degradation in a time-dependent manner. Expression profiling was then performed and data were analyzed bioinformatically to assess the differences. Results: The differences introduced by RNA degradation were largely outweighed by the biological differences between the patients. Only a relatively small number of probes (275 out of 41,000) show a significant effect due to degradation. The genes that show the strongest effect due to RNA degradation were, especially, those with short mRNAs and probe positions near the 5' end. Conclusions: Degraded RNA from tumor samples (RIN > 5) can still be used to perform gene expression analysis. A much higher biological variance between patients is observed compared to the effect that is imposed by degradation of RNA. Nevertheless there are genes, very short ones and those with the probe binding side close to the 5' end that should be excluded from gene expression analysis when working with degraded RNA. These results are limited to the Agilent 44 k microarray platform and should be carefully interpreted when transferring to other settings."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft [KFO 179]; BMBF [01GS0890]; BreastSys"],["dc.identifier.doi","10.1186/1755-8794-3-36"],["dc.identifier.isi","000283179600001"],["dc.identifier.pmid","20696062"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/5664"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/19230"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1755-8794"],["dc.rights","CC BY 2.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.0"],["dc.title","Impact of RNA degradation on gene expression profiling"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e38365"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Artmann, Stephan"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2018-11-07T09:09:13Z"],["dc.date.available","2018-11-07T09:09:13Z"],["dc.date.issued","2012"],["dc.description.abstract","Expression levels of mRNAs are among other factors regulated by microRNAs. A particular microRNA can bind specifically to several target mRNAs and lead to their degradation. Expression levels of both, mRNAs and microRNAs, can be obtained by microarray experiments. In order to increase the power of detecting microRNAs that are differentially expressed between two different groups of samples, we incorporate expression levels of their related target gene sets. Group effects are determined individually for each microRNA, and by enrichment tests and global tests for target gene sets. The resulting lists of p-values from individual and set-wise testing are combined by means of meta analysis. We propose a new approach to connect microRNA-wise and gene set-wise information by means of p-value combination as often used in meta-analysis. In this context, we evaluate the usefulness of different approaches of gene set tests. In a simulation study we reveal that our combination approach is more powerful than microRNA-wise testing alone. Furthermore, we show that combining microRNA-wise results with 'competitive' gene set tests maintains a pre-specified false discovery rate. In contrast, a combination with 'self-contained' gene set tests can harm the false discovery rate, particularly when gene sets are not disjunct."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2012"],["dc.identifier.doi","10.1371/journal.pone.0038365"],["dc.identifier.isi","000305652700014"],["dc.identifier.pmid","22723856"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/7745"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/26206"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 2.5"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.5"],["dc.title","Detection of Simultaneous Group Effects in MicroRNA Expression and Related Target Gene Sets"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","334"],["dc.bibliographiccitation.journal","BMC Bioinformatics"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Bayerlová, Michaela"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Kramer, Frank"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2018-11-07T09:50:02Z"],["dc.date.available","2018-11-07T09:50:02Z"],["dc.date.issued","2015"],["dc.description.abstract","Background: Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. Methods: We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. Results: In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. Conclusions: We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps."],["dc.description.sponsorship","Open-Access Publikationsfonds 2015"],["dc.identifier.doi","10.1186/s12859-015-0751-5"],["dc.identifier.isi","000363615900001"],["dc.identifier.pmid","26489510"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12346"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35629"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1471-2105"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Comparative study on gene set and pathway topology-based enrichment methods"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Journal of Clinical Oncology"],["dc.bibliographiccitation.volume","31"],["dc.contributor.author","Sprenger, Thilo"],["dc.contributor.author","Gaedcke, Jochen"],["dc.contributor.author","Conradi, Lena-Christin"],["dc.contributor.author","Jo, Peter"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Homayounfar, Kia"],["dc.contributor.author","Ghadimi, Michael B."],["dc.contributor.author","Liersch, Torsten"],["dc.date.accessioned","2018-11-07T09:28:52Z"],["dc.date.available","2018-11-07T09:28:52Z"],["dc.date.issued","2013"],["dc.identifier.isi","000333679000393"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/30890"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Amer Soc Clinical Oncology"],["dc.publisher.place","Alexandria"],["dc.relation.conference","Gastrointestinal Cancers Symposium of the American-Society-of-Clinical-Oncology (ASCO)"],["dc.relation.eventlocation","San Francisco, CA"],["dc.relation.issn","1527-7755"],["dc.relation.issn","0732-183X"],["dc.title","Association of CD133 expression levels with the k-ras mutation status in rectal cancers before and after preoperative radiochemotherapy"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]