000119334 001__ 119334
000119334 005__ 20240228145433.0
000119334 0247_ $$2doi$$a10.1016/j.ymeth.2016.09.014
000119334 0247_ $$2pmid$$apmid:27725304
000119334 0247_ $$2ISSN$$a1046-2023
000119334 0247_ $$2ISSN$$a1095-9130
000119334 0247_ $$2altmetric$$aaltmetric:13072940
000119334 037__ $$aDKFZ-2017-00089
000119334 041__ $$aeng
000119334 082__ $$a540
000119334 1001_ $$aGunkel, Manuel$$b0
000119334 245__ $$aQuantification of telomere features in tumor tissue sections by an automated 3D imaging-based workflow.2
000119334 260__ $$aOrlando, Fla.$$bAcademic Press$$c2017
000119334 3367_ $$2DRIVER$$aarticle
000119334 3367_ $$2DataCite$$aOutput Types/Journal article
000119334 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1511273187_9921
000119334 3367_ $$2BibTeX$$aARTICLE
000119334 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000119334 3367_ $$00$$2EndNote$$aJournal Article
000119334 520__ $$aThe microscopic analysis of telomere features provides a wealth of information on the mechanism by which tumor cells maintain their unlimited proliferative potential. Accordingly, the analysis of telomeres in tissue sections of patient tumor samples can be exploited to obtain diagnostic information and to define tumor subgroups. In many instances, however, analysis of the image data is conducted by manual inspection of 2D images at relatively low resolution for only a small part of the sample. As the telomere feature signal distribution is frequently heterogeneous, this approach is prone to a biased selection of the information present in the image and lacks subcellular details. Here we address these issues by using an automated high-resolution imaging and analysis workflow that quantifies individual telomere features on tissue sections for a large number of cells. The approach is particularly suited to assess telomere heterogeneity and low abundant cellular subpopulations with distinct telomere characteristics in a reproducible manner. It comprises the integration of multi-color fluorescence in situ hybridization, immunofluorescence and DNA staining with targeted automated 3D fluorescence microscopy and image analysis. We apply our method to telomeres in glioblastoma and prostate cancer samples, and describe how the imaging data can be used to derive statistically reliable information on telomere length distribution or colocalization with PML nuclear bodies. We anticipate that relating this approach to clinical outcome data will prove to be valuable for pretherapeutic patient stratification.
000119334 536__ $$0G:(DE-HGF)POF3-312$$a312 - Functional and structural genomics (POF3-312)$$cPOF3-312$$fPOF III$$x0
000119334 588__ $$aDataset connected to CrossRef, PubMed,
000119334 7001_ $$0P:(DE-He78)d1a346df2019a0c0fd79b4808e502cee$$aChung, Inn$$b1$$udkfz
000119334 7001_ $$0P:(DE-He78)6dfd570c2b4fafb29ab11b616c6c2285$$aWörz, Stefan$$b2$$udkfz
000119334 7001_ $$0P:(DE-He78)307c43dc6b7bbf6ca6c8a29fdeb01851$$aDeeg, Katharina$$b3$$udkfz
000119334 7001_ $$aSimon, Ronald$$b4
000119334 7001_ $$aSauter, Guido$$b5
000119334 7001_ $$0P:(DE-He78)551bb92841f634070997aa168d818492$$aJones, David$$b6$$udkfz
000119334 7001_ $$0P:(DE-He78)8d9c904a6cea14d4c99c78ba46e41f93$$aKorshunov, Andrey$$b7$$udkfz
000119334 7001_ $$0P:(DE-He78)f1db1035ee9130131effb4f2f60553ae$$aRohr, Karl$$b8$$udkfz
000119334 7001_ $$aErfle, Holger$$b9
000119334 7001_ $$0P:(DE-He78)94de5f7413279464b6e738d91dfae1eb$$aRippe, Karsten$$b10$$eLast author$$udkfz
000119334 773__ $$0PERI:(DE-600)1471152-7$$a10.1016/j.ymeth.2016.09.014$$gVol. 114, p. 60 - 73$$p60 - 73$$tMethods$$v114$$x1046-2023$$y2017
000119334 909CO $$ooai:inrepo02.dkfz.de:119334$$pVDB
000119334 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz
000119334 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000119334 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000119334 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000119334 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bMETHODS : 2015
000119334 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000119334 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000119334 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000119334 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000119334 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000119334 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000119334 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences
000119334 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000119334 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000119334 9141_ $$y2017
000119334 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)d1a346df2019a0c0fd79b4808e502cee$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000119334 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)6dfd570c2b4fafb29ab11b616c6c2285$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000119334 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)307c43dc6b7bbf6ca6c8a29fdeb01851$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000119334 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)551bb92841f634070997aa168d818492$$aDeutsches Krebsforschungszentrum$$b6$$kDKFZ
000119334 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)8d9c904a6cea14d4c99c78ba46e41f93$$aDeutsches Krebsforschungszentrum$$b7$$kDKFZ
000119334 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)f1db1035ee9130131effb4f2f60553ae$$aDeutsches Krebsforschungszentrum$$b8$$kDKFZ
000119334 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)94de5f7413279464b6e738d91dfae1eb$$aDeutsches Krebsforschungszentrum$$b10$$kDKFZ
000119334 9131_ $$0G:(DE-HGF)POF3-312$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunctional and structural genomics$$x0
000119334 9201_ $$0I:(DE-He78)B066-20160331$$kB066$$lGenomorganisation und Funktion$$x0
000119334 9201_ $$0I:(DE-He78)B080-20160331$$kB080$$lTheoretische Bioinformatik$$x1
000119334 9201_ $$0I:(DE-He78)B062-20160331$$kB062$$lPädiatrische Neuroonkologie$$x2
000119334 9201_ $$0I:(DE-He78)G380-20160331$$kG380$$lKKE Neuropathologie$$x3
000119334 980__ $$ajournal
000119334 980__ $$aVDB
000119334 980__ $$aI:(DE-He78)B066-20160331
000119334 980__ $$aI:(DE-He78)B080-20160331
000119334 980__ $$aI:(DE-He78)B062-20160331
000119334 980__ $$aI:(DE-He78)G380-20160331
000119334 980__ $$aUNRESTRICTED