000300743 001__ 300743
000300743 005__ 20250525020715.0
000300743 0247_ $$2doi$$a10.1158/0008-5472.CAN-24-1607
000300743 0247_ $$2pmid$$apmid:40298430
000300743 0247_ $$2ISSN$$a0099-7013
000300743 0247_ $$2ISSN$$a0099-7374
000300743 0247_ $$2ISSN$$a0008-5472
000300743 0247_ $$2ISSN$$a1538-7445
000300743 0247_ $$2altmetric$$aaltmetric:176822013
000300743 037__ $$aDKFZ-2025-00903
000300743 041__ $$aEnglish
000300743 082__ $$a610
000300743 1001_ $$00000-0002-8592-5269$$aCai, Ling$$b0
000300743 245__ $$aThe Lung Cancer Autochthonous Model Gene Expression Database Enables Cross-Study Comparisons of the Transcriptomic Landscapes Across Mouse Models.
000300743 260__ $$aPhiladelphia, Pa.$$bAACR$$c2025
000300743 3367_ $$2DRIVER$$aarticle
000300743 3367_ $$2DataCite$$aOutput Types/Journal article
000300743 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1747725754_3488
000300743 3367_ $$2BibTeX$$aARTICLE
000300743 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000300743 3367_ $$00$$2EndNote$$aJournal Article
000300743 500__ $$a2025 May 15;85(10):1769-1783
000300743 520__ $$aLung cancer, the leading cause of cancer mortality, exhibits diverse histologic subtypes and genetic complexities. Numerous preclinical mouse models have been developed to study lung cancer, but data from these models are disparate, siloed, and difficult to compare in a centralized fashion. In this study, we established the Lung Cancer Autochthonous Model Gene Expression Database (LCAMGDB), an extensive repository of 1,354 samples from 77 transcriptomic datasets covering 974 samples from genetically engineered mouse models (GEMM), 368 samples from carcinogen-induced models, and 12 samples from a spontaneous model. Meticulous curation and collaboration with data depositors produced a robust and comprehensive database, enhancing the fidelity of the genetic landscape it depicts. The LCAMGDB aligned 859 tumors from GEMMs with human lung cancer mutations, enabling comparative analysis and revealing a pressing need to broaden the diversity of genetic aberrations modeled in the GEMMs. To accompany this resource, a web application was developed that offers researchers intuitive tools for in-depth gene expression analysis. With standardized reprocessing of gene expression data, the LCAMGDB serves as a powerful platform for cross-study comparison and lays the groundwork for future research, aiming to bridge the gap between mouse models and human lung cancer for improved translational relevance. Significance: The Lung Cancer Autochthonous Model Gene Expression Database (LCAMGDB) provides a comprehensive and accessible resource for the research community to investigate lung cancer biology in mouse models.
000300743 536__ $$0G:(DE-HGF)POF4-312$$a312 - Funktionelle und strukturelle Genomforschung (POF4-312)$$cPOF4-312$$fPOF IV$$x0
000300743 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000300743 7001_ $$00000-0001-8812-8655$$aWu, Fangjiang$$b1
000300743 7001_ $$00000-0002-7967-2138$$aZhou, Qinbo$$b2
000300743 7001_ $$00009-0006-5110-1268$$aGao, Ying$$b3
000300743 7001_ $$00009-0002-2225-9956$$aYao, Bo$$b4
000300743 7001_ $$00000-0002-2705-7432$$aDeBerardinis, Ralph J$$b5
000300743 7001_ $$00000-0003-3984-8327$$aAcquaah-Mensah, George K$$b6
000300743 7001_ $$00000-0001-9531-7729$$aAidinis, Vassilis$$b7
000300743 7001_ $$00000-0002-6699-2132$$aBeane, Jennifer E$$b8
000300743 7001_ $$00009-0000-5794-3403$$aBiswal, Shyam$$b9
000300743 7001_ $$00000-0003-1725-7956$$aChen, Ting$$b10
000300743 7001_ $$00000-0003-0529-7360$$aConcepcion-Crisol, Carla P$$b11
000300743 7001_ $$aGrüner, Barbara M$$b12
000300743 7001_ $$00000-0002-2784-126X$$aJia, Deshui$$b13
000300743 7001_ $$00000-0001-7665-9301$$aJones, Robert A$$b14
000300743 7001_ $$00000-0002-1472-8719$$aKurie, Jonathan M$$b15
000300743 7001_ $$00000-0003-0859-0642$$aLee, Min Gyu$$b16
000300743 7001_ $$00000-0001-9539-3959$$aLindahl, Per$$b17
000300743 7001_ $$00000-0003-1024-5303$$aLissanu, Yonathan$$b18
000300743 7001_ $$00000-0001-8214-9076$$aLorz, Corina$$b19
000300743 7001_ $$00000-0003-3729-907X$$aMacPherson, David$$b20
000300743 7001_ $$00000-0002-6524-6752$$aMartinelli, Rosanna$$b21
000300743 7001_ $$00000-0002-5820-8344$$aMazur, Pawel K$$b22
000300743 7001_ $$00000-0002-9187-2722$$aMazzilli, Sarah A$$b23
000300743 7001_ $$00000-0001-8266-3235$$aMii, Shinji$$b24
000300743 7001_ $$00000-0001-6438-9068$$aMoll, Herwig P$$b25
000300743 7001_ $$00000-0001-9539-6295$$aMoorehead, Roger A$$b26
000300743 7001_ $$00000-0001-5785-1939$$aMorrisey, Edward E$$b27
000300743 7001_ $$00000-0003-1655-2443$$aNg, Sheng Rong$$b28
000300743 7001_ $$00000-0003-2047-0969$$aOser, Matthew G$$b29
000300743 7001_ $$00000-0003-0963-9073$$aPandiri, Arun R$$b30
000300743 7001_ $$00000-0003-3509-891X$$aPowell, Charles A$$b31
000300743 7001_ $$00000-0003-0194-3257$$aRamadori, Giorgio$$b32
000300743 7001_ $$00009-0009-9451-2624$$aSantos, Mirentxu$$b33
000300743 7001_ $$00000-0003-3591-3195$$aSnyder, Eric L$$b34
000300743 7001_ $$00000-0002-0855-7917$$aSotillo, Rocio$$b35
000300743 7001_ $$00000-0002-6538-9526$$aSu, Kang-Yi$$b36
000300743 7001_ $$00000-0001-8654-6896$$aTaki, Tetsuro$$b37
000300743 7001_ $$00000-0001-8493-3868$$aTaparra, Kekoa$$b38
000300743 7001_ $$00000-0002-0147-0376$$aTran, Phuoc T$$b39
000300743 7001_ $$00000-0001-9709-7395$$aXia, Yifeng$$b40
000300743 7001_ $$00000-0003-1798-3210$$avan Veen, J Edward$$b41
000300743 7001_ $$00000-0002-5730-9573$$aWinslow, Monte M$$b42
000300743 7001_ $$00000-0001-9387-9883$$aXiao, Guanghua$$b43
000300743 7001_ $$00000-0001-5204-3465$$aRudin, Charles M$$b44
000300743 7001_ $$00000-0003-2082-2397$$aOliver, Trudy G$$b45
000300743 7001_ $$aXie, Yang$$b46
000300743 7001_ $$00000-0002-7776-0767$$aMinna, John D$$b47
000300743 773__ $$0PERI:(DE-600)2036785-5$$a10.1158/0008-5472.CAN-24-1607$$gp. OF1 - OF15$$n10$$p1769-1783$$tCancer research$$v85$$x0099-7013$$y2025
000300743 909CO $$ooai:inrepo02.dkfz.de:300743$$pVDB
000300743 9101_ $$0I:(DE-588b)2036810-0$$60000-0002-0855-7917$$aDeutsches Krebsforschungszentrum$$b35$$kDKFZ
000300743 9131_ $$0G:(DE-HGF)POF4-312$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunktionelle und strukturelle Genomforschung$$x0
000300743 9141_ $$y2025
000300743 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-21
000300743 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-21
000300743 9201_ $$0I:(DE-He78)B220-20160331$$kB220$$lB220 Molekulare Grundlagen thorakaler Tumoren$$x0
000300743 980__ $$ajournal
000300743 980__ $$aVDB
000300743 980__ $$aI:(DE-He78)B220-20160331
000300743 980__ $$aUNRESTRICTED