000169863 001__ 169863
000169863 005__ 20240229140928.0
000169863 0247_ $$2doi$$a10.1007/s00262-021-03002-6
000169863 0247_ $$2pmid$$apmid:34269847
000169863 0247_ $$2ISSN$$a0340-7004
000169863 0247_ $$2ISSN$$a1432-0851
000169863 0247_ $$2altmetric$$aaltmetric:109752894
000169863 037__ $$aDKFZ-2021-01597
000169863 041__ $$aEnglish
000169863 082__ $$a610
000169863 1001_ $$aHoffmann, Elgin$$b0
000169863 245__ $$aRadiotherapy planning parameters correlate with changes in the peripheral immune status of patients undergoing curative radiotherapy for localized prostate cancer.
000169863 260__ $$aHeidelberg$$bSpringer$$c2022
000169863 3367_ $$2DRIVER$$aarticle
000169863 3367_ $$2DataCite$$aOutput Types/Journal article
000169863 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1646135803_20517
000169863 3367_ $$2BibTeX$$aARTICLE
000169863 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000169863 3367_ $$00$$2EndNote$$aJournal Article
000169863 500__ $$a71, pages 541–552 (2022)
000169863 520__ $$aThe influence of radiotherapy on patient immune cell subsets has been established by several groups. Following a previously published analysis of immune changes during and after curative radiotherapy for prostate cancer, this analysis focused on describing correlations of changes of immune cell subsets with radiation treatment parameters.For 13 patients treated in a prospective trial with radiotherapy to the prostate region (primary analysis) and five patients treated with radiotherapy to prostate and pelvic nodal regions (exploratory analysis), already published immune monitoring data were correlated with clinical data as well as radiation planning parameters such as clinical target volume (CTV) and volumes receiving 20 Gy (V20) for newly contoured volumes of pelvic blood vessels and bone marrow.Most significant changes among immune cell subsets were observed at the end of radiotherapy. In contrast, correlations of age and CD8+ subsets (effector and memory cells) were observed early during and 3 months after radiotherapy. Ratios of T cells and T cell proliferation compared to baseline correlated with CTV. Early changes in regulatory T cells (Treg cells) and CD8+ effector T cells correlated with V20 of blood vessels and bone volumes.Patient age as well as radiotherapy planning parameters correlated with immune changes during radiotherapy. Larger irradiated volumes seem to correlate with early suppression of anti-cancer immunity. For immune cell analysis during normofractionated radiotherapy and correlations with treatment planning parameters, different time points should be looked at in future projects.NCT01376674, 20.06.2011.
000169863 536__ $$0G:(DE-HGF)POF4-899$$a899 - ohne Topic (POF4-899)$$cPOF4-899$$fPOF IV$$x0
000169863 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo01.inet.dkfz-heidelberg.de
000169863 650_7 $$2Other$$aDVH
000169863 650_7 $$2Other$$aIMRT
000169863 650_7 $$2Other$$aImmune status
000169863 650_7 $$2Other$$aLocalized
000169863 650_7 $$2Other$$aProstate cancer
000169863 650_7 $$2Other$$aT cells
000169863 7001_ $$aPaulsen, Frank$$b1
000169863 7001_ $$aSchaedle, Philipp$$b2
000169863 7001_ $$0P:(DE-HGF)0$$aZips, Daniel$$b3
000169863 7001_ $$0P:(DE-HGF)0$$aGani, Cihan$$b4
000169863 7001_ $$0P:(DE-He78)58a4f09f3edfdce451d520a5be7979fc$$aRammensee, Hans-Georg$$b5$$udkfz
000169863 7001_ $$0P:(DE-HGF)0$$aGouttefangeas, Cécile$$b6
000169863 7001_ $$00000-0002-4742-3962$$aEckert, Franziska$$b7
000169863 773__ $$0PERI:(DE-600)1458489-X$$a10.1007/s00262-021-03002-6$$p541–552$$tCancer immunology immunotherapy$$v71$$x1432-0851$$y2022
000169863 909CO $$ooai:inrepo02.dkfz.de:169863$$pVDB
000169863 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000169863 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000169863 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)58a4f09f3edfdce451d520a5be7979fc$$aDeutsches Krebsforschungszentrum$$b5$$kDKFZ
000169863 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b6$$kDKFZ
000169863 9101_ $$0I:(DE-588b)2036810-0$$60000-0002-4742-3962$$aDeutsches Krebsforschungszentrum$$b7$$kDKFZ
000169863 9131_ $$0G:(DE-HGF)POF4-899$$1G:(DE-HGF)POF4-890$$2G:(DE-HGF)POF4-800$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bProgrammungebundene Forschung$$lohne Programm$$vohne Topic$$x0
000169863 9130_ $$0G:(DE-HGF)POF3-899$$1G:(DE-HGF)POF3-890$$2G:(DE-HGF)POF3-800$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bProgrammungebundene Forschung$$lohne Programm$$vohne Topic$$x0
000169863 9141_ $$y2021
000169863 915__ $$0StatID:(DE-HGF)3002$$2StatID$$aDEAL Springer$$d2021-01-31$$wger
000169863 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-01-31
000169863 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2021-01-31
000169863 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2021-01-31
000169863 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2022-11-18
000169863 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2022-11-18
000169863 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2022-11-18
000169863 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2022-11-18
000169863 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2022-11-18
000169863 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2022-11-18
000169863 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2022-11-18
000169863 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2022-11-18
000169863 9201_ $$0I:(DE-He78)TU01-20160331$$kTU01$$lDKTK TU zentral$$x0
000169863 980__ $$ajournal
000169863 980__ $$aVDB
000169863 980__ $$aI:(DE-He78)TU01-20160331
000169863 980__ $$aUNRESTRICTED