000285713 001__ 285713
000285713 005__ 20240229155116.0
000285713 0247_ $$2doi$$a10.3389/fimmu.2023.1286700
000285713 0247_ $$2pmid$$apmid:38035078
000285713 0247_ $$2pmc$$apmc:PMC10684778
000285713 0247_ $$2altmetric$$aaltmetric:156965122
000285713 037__ $$aDKFZ-2023-02521
000285713 041__ $$aEnglish
000285713 082__ $$a610
000285713 1001_ $$aEmde-Rajaratnam, Martina$$b0
000285713 245__ $$aRNA-sequencing based first choice of treatment and determination of risk in multiple myeloma.
000285713 260__ $$aLausanne$$bFrontiers Media$$c2023
000285713 3367_ $$2DRIVER$$aarticle
000285713 3367_ $$2DataCite$$aOutput Types/Journal article
000285713 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1701441067_30227
000285713 3367_ $$2BibTeX$$aARTICLE
000285713 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000285713 3367_ $$00$$2EndNote$$aJournal Article
000285713 520__ $$aImmunotherapeutic targets in multiple myeloma (MM) have variable expression height and are partly expressed in subfractions of patients only. With increasing numbers of available compounds, strategies for appropriate choice of targets (combinations) are warranted. Simultaneously, risk assessment is advisable as patient's life expectancy varies between months and decades.We first assess feasibility of RNA-sequencing in a multicenter trial (GMMG-MM5, n=604 patients). Next, we use a clinical routine cohort of untreated symptomatic myeloma patients undergoing autologous stem cell transplantation (n=535, median follow-up (FU) 64 months) to perform RNA-sequencing, gene expression profiling (GEP), and iFISH by ten-probe panel on CD138-purified malignant plasma cells. We subsequently compare target expression to plasma cell precursors, MGUS (n=59), asymptomatic (n=142) and relapsed (n=69) myeloma patients, myeloma cell lines (n=26), and between longitudinal samples (MM vs. relapsed MM). Data are validated using the independent MMRF CoMMpass-cohort (n=767, FU 31 months).RNA-sequencing is feasible in 90.8% of patients (GMMG-MM5). Actionable immune-oncological targets (n=19) can be divided in those expressed in all normal and >99% of MM-patients (CD38, SLAMF7, BCMA, GPRC5D, FCRH5, TACI, CD74, CD44, CD37, CD79B), those with expression loss in subfractions of MM-patients (BAFF-R [81.3%], CD19 [57.9%], CD20 [82.8%], CD22 [28.4%]), aberrantly expressed in MM (NY-ESO1/2 [12%], MUC1 [12.7%], CD30 [4.9%], mutated BRAF V600E/K [2.1%]), and resistance-conveying target-mutations e.g., against part but not all BCMA-directed treatments. Risk is assessable regarding proliferation, translated GEP- (UAMS70-, SKY92-, RS-score) and de novo (LfM-HRS) defined risk scores. LfM-HRS delineates three groups of 40%, 38%, and 22% of patients with 5-year and 12-year survival rates of 84% (49%), 67% (18%), and 32% (0%). R-ISS and RNA-sequencing identify partially overlapping patient populations, with R-ISS missing, e.g., 30% (22/72) of highly proliferative myeloma.RNA-sequencing based assessment of risk and targets for first choice treatment is possible in clinical routine.
000285713 536__ $$0G:(DE-HGF)POF4-313$$a313 - Krebsrisikofaktoren und Prävention (POF4-313)$$cPOF4-313$$fPOF IV$$x0
000285713 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000285713 650_7 $$2Other$$aRNA-sequencing
000285713 650_7 $$2Other$$aimmunotherapeutic targets
000285713 650_7 $$2Other$$amultiple myeloma
000285713 650_7 $$2Other$$apersonalized treatment
000285713 650_7 $$2Other$$aproliferation
000285713 650_7 $$2Other$$arisk-adapted treatment
000285713 650_7 $$2Other$$asurvival
000285713 7001_ $$aBeck, Susanne$$b1
000285713 7001_ $$aBenes, Vladimir$$b2
000285713 7001_ $$aSalwender, Hans$$b3
000285713 7001_ $$aBertsch, Uta$$b4
000285713 7001_ $$aScheid, Christoph$$b5
000285713 7001_ $$aHänel, Mathias$$b6
000285713 7001_ $$aWeisel, Katja$$b7
000285713 7001_ $$0P:(DE-He78)743a4a82daab55306a2c88b9f6bf8c2f$$aHielscher, Thomas$$b8$$udkfz
000285713 7001_ $$aRaab, Marc S$$b9
000285713 7001_ $$aGoldschmidt, Hartmut$$b10
000285713 7001_ $$aJauch, Anna$$b11
000285713 7001_ $$aMaes, Ken$$b12
000285713 7001_ $$aDe Bruyne, Elke$$b13
000285713 7001_ $$aMenu, Eline$$b14
000285713 7001_ $$aDe Veirman, Kim$$b15
000285713 7001_ $$aMoreaux, Jérôme$$b16
000285713 7001_ $$aVanderkerken, Karin$$b17
000285713 7001_ $$aSeckinger, Anja$$b18
000285713 7001_ $$aHose, Dirk$$b19
000285713 773__ $$0PERI:(DE-600)2606827-8$$a10.3389/fimmu.2023.1286700$$gVol. 14, p. 1286700$$p1286700$$tFrontiers in immunology$$v14$$x1664-3224$$y2023
000285713 909CO $$ooai:inrepo02.dkfz.de:285713$$pVDB
000285713 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)743a4a82daab55306a2c88b9f6bf8c2f$$aDeutsches Krebsforschungszentrum$$b8$$kDKFZ
000285713 9131_ $$0G:(DE-HGF)POF4-313$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vKrebsrisikofaktoren und Prävention$$x0
000285713 9141_ $$y2023
000285713 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bFRONT IMMUNOL : 2022$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2021-05-11T10:28:02Z
000285713 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2021-05-11T10:28:02Z
000285713 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2021-05-11T10:28:02Z
000285713 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ$$d2021-05-11T10:28:02Z
000285713 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bFRONT IMMUNOL : 2022$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2023-10-26
000285713 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2023-10-26
000285713 9201_ $$0I:(DE-He78)C060-20160331$$kC060$$lC060 Biostatistik$$x0
000285713 980__ $$ajournal
000285713 980__ $$aVDB
000285713 980__ $$aI:(DE-He78)C060-20160331
000285713 980__ $$aUNRESTRICTED