Home > Publications database > Living human lung slices for ex vivo modelling of lung cancer. > print

001     304483
005     20250914022647.0
024 7 _ |a 10.1172/jci.insight.190703
|2 doi
024 7 _ |a pmid:40728884
|2 pmid
024 7 _ |a altmetric:179735489
|2 altmetric
037 _ _ |a DKFZ-2025-01875
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Mansouri, Siavash
|b 0
245 _ _ |a Living human lung slices for ex vivo modelling of lung cancer.
260 _ _ |a Ann Arbor, Michigan
|c 2025
|b JCI Insight
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1757570399_26502
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a The tumor microenvironment (TME) markedly affects cancer progression, yet traditional animal models do not fully recapitulate the situation in humans. To address this, we developed tumor-derived precision lung slices (TD-PCLS), an ex vivo platform for studying the lung TME and evaluating therapies. TD-PCLS, viable for 8-10 days, preserve the heterogeneity and metabolic activity of primary tumors, as confirmed by seahorse analysis. Using multispectral FACS and phenocycler multiplex imaging, we spatially profiled TME components and cancer cell functionality. Additionally, TD-PCLS revealed patient-specific responses to chemo- and immunotherapies. To complement TD-PCLS, we established tumor-cell-seeded PCLS (TCS-PCLS) by introducing tumor and immune cells into healthy lung slices. This model highlighted macrophage-tumor interactions as critical for tumor cell proliferation, migration, and immune modulation. Together, these platforms provide a robust tool for lung cancer research, enabling precision medicine and advancing therapeutic discovery.
536 _ _ |a 312 - Funktionelle und strukturelle Genomforschung (POF4-312)
|0 G:(DE-HGF)POF4-312
|c POF4-312
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 7 |a Immunology
|2 Other
650 _ 7 |a Immunotherapy
|2 Other
650 _ 7 |a Lung cancer
|2 Other
650 _ 7 |a Oncology
|2 Other
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Lung Neoplasms: pathology
|2 MeSH
650 _ 2 |a Lung Neoplasms: immunology
|2 MeSH
650 _ 2 |a Lung Neoplasms: therapy
|2 MeSH
650 _ 2 |a Tumor Microenvironment: immunology
|2 MeSH
650 _ 2 |a Lung: pathology
|2 MeSH
650 _ 2 |a Lung: immunology
|2 MeSH
650 _ 2 |a Cell Proliferation
|2 MeSH
650 _ 2 |a Cell Line, Tumor
|2 MeSH
650 _ 2 |a Macrophages: immunology
|2 MeSH
650 _ 2 |a Cell Movement
|2 MeSH
700 1 _ |a Karger, Annika
|b 1
700 1 _ |a Ruppert, Clemens
|b 2
700 1 _ |a Schneider, Marc A
|b 3
700 1 _ |a Weigert, Andreas
|b 4
700 1 _ |a Nandigama, Rajender
|b 5
700 1 _ |a Aliraj, Blerina
|b 6
700 1 _ |a Strotmann, Lisa
|0 P:(DE-He78)b0217be22a29dfdb8927f227016fd33b
|b 7
|u dkfz
700 1 _ |a Cherian, Anoop V
|b 8
700 1 _ |a Pruefer, Diethard
|b 9
700 1 _ |a Dorfmuller, Peter
|b 10
700 1 _ |a Fink, Ludger
|b 11
700 1 _ |a Alkoudmani, Ibrahim
|b 12
700 1 _ |a Gattenlöhner, Stefan
|b 13
700 1 _ |a Eul, Bastian
|b 14
700 1 _ |a Althoff, Andre
|b 15
700 1 _ |a Kleine, Peter
|b 16
700 1 _ |a Winter, Hauke
|b 17
700 1 _ |a Guenther, Andreas
|b 18
700 1 _ |a Ghofrani, Hossein-Ardeschir
|b 19
700 1 _ |a Pullamsetti, Soni S
|b 20
700 1 _ |a Grimminger, Friedrich
|b 21
700 1 _ |a Seeger, Werner
|b 22
700 1 _ |a Savai, Rajkumar
|b 23
773 _ _ |a 10.1172/jci.insight.190703
|g Vol. 10, no. 17, p. e190703
|0 PERI:(DE-600)2874757-4
|n 17
|p e190703
|t JCI insight
|v 10
|y 2025
|x 2379-3708
909 C O |o oai:inrepo02.dkfz.de:304483
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 7
|6 P:(DE-He78)b0217be22a29dfdb8927f227016fd33b
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-312
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Funktionelle und strukturelle Genomforschung
|x 0
914 1 _ |y 2025
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b JCI INSIGHT : 2022
|d 2025-01-02
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2025-01-02
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2025-01-02
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2022-05-18T13:47:27Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2022-05-18T13:47:27Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2022-05-18T13:47:27Z
915 _ _ |a Creative Commons Attribution CC BY (No Version)
|0 LIC:(DE-HGF)CCBYNV
|2 V:(DE-HGF)
|b DOAJ
|d 2022-05-18T13:47:27Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2025-01-02
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2025-01-02
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2025-01-02
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2025-01-02
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2025-01-02
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b JCI INSIGHT : 2022
|d 2025-01-02
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2025-01-02
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2025-01-02
920 1 _ |0 I:(DE-He78)B200-20160331
|k B200
|l B200 Systembiologie der Signaltransduktion
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)B200-20160331
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21