The proteogenomic landscape of multiple myeloma reveals insights into disease biology and therapeutic opportunities.


Journal

Nature cancer
ISSN: 2662-1347
Titre abrégé: Nat Cancer
Pays: England
ID NLM: 101761119

Informations de publication

Date de publication:
28 Jun 2024
Historique:
received: 21 12 2022
accepted: 15 05 2024
medline: 29 6 2024
pubmed: 29 6 2024
entrez: 28 6 2024
Statut: aheadofprint

Résumé

Multiple myeloma (MM) is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, MM remains incurable, and better risk stratification as well as new therapies are therefore highly needed. The proteome of MM has not been systematically assessed before and holds the potential to uncover insight into disease biology and improved prognostication in addition to genetic and transcriptomic studies. Here we provide a comprehensive multiomics analysis including deep tandem mass tag-based quantitative global (phospho)proteomics, RNA sequencing, and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive MM, plasma cell leukemia and the premalignancy monoclonal gammopathy of undetermined significance, as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells are highly deregulated as compared with healthy plasma cells and is both defined by chromosomal alterations as well as posttranscriptional regulation. A prognostic protein signature was identified that is associated with aggressive disease independent of established risk factors in MM. Integration with functional genetics and single-cell RNA sequencing revealed general and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include potential targets for (immuno)therapies. Our study demonstrates the potential of proteogenomics in cancer and provides an easily accessible resource for investigating protein regulation and new therapeutic approaches in MM.

Identifiants

pubmed: 38942927
doi: 10.1038/s43018-024-00784-3
pii: 10.1038/s43018-024-00784-3
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Emmy-Noether Program Kr3886/ 2-2 and SBF-1074
Organisme : Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research)
ID : 031L0220B

Informations de copyright

© 2024. The Author(s).

Références

van de Donk, N. W. C. J., Pawlyn, C. & Yong, K. L. Multiple myeloma. Lancet 397, 410–427 (2021).
pubmed: 33516340 doi: 10.1016/S0140-6736(21)00135-5
Manier, S. et al. Genomic complexity of multiple myeloma and its clinical implications. Nat. Rev. Clin. Oncol. 14, 100–113 (2017).
pubmed: 27531699 doi: 10.1038/nrclinonc.2016.122
Zhan, F. et al. The molecular classification of multiple myeloma. Blood https://doi.org/10.1182/blood-2005-11-013458 (2006).
Shaughnessy, J. D. Jr et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood 109, 2276–2284 (2007).
pubmed: 17105813 doi: 10.1182/blood-2006-07-038430
Lohr, J. G. et al. Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. Cancer Cell 25, 91–101 (2014).
pubmed: 24434212 pmcid: 4241387 doi: 10.1016/j.ccr.2013.12.015
Walker, B. A. et al. Mutational spectrum, copy number changes, and outcome: results of a sequencing study of patients with newly diagnosed myeloma. J. Clin. Oncol. 33, 3911–3920 (2015).
pubmed: 26282654 doi: 10.1200/JCO.2014.59.1503
Chapman, M. A. et al. Initial genome sequencing and analysis of multiple myeloma. Nature 471, 467–472 (2011).
pubmed: 21430775 pmcid: 3560292 doi: 10.1038/nature09837
Mani, D. R. et al. Cancer proteogenomics: current impact and future prospects. Nat. Rev. Cancer 22, 298–313 (2022).
pubmed: 35236940 doi: 10.1038/s41568-022-00446-5
Vasaikar, S. et al. Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities. Cell 177, 1035–1049.e19 (2019).
pubmed: 31031003 pmcid: 6768830 doi: 10.1016/j.cell.2019.03.030
Satpathy, S. et al. A proteogenomic portrait of lung squamous cell carcinoma. Cell 184, 4348–4371.e40 (2021).
pubmed: 34358469 pmcid: 8475722 doi: 10.1016/j.cell.2021.07.016
Mertins, P. et al. Proteogenomics connects somatic mutations to signalling in breast cancer. Nature 534, 55–62 (2016).
pubmed: 27251275 pmcid: 5102256 doi: 10.1038/nature18003
Jayavelu, A. K. et al. The proteogenomic subtypes of acute myeloid leukemia. Cancer Cell 40, 301–317.e12 (2022).
pubmed: 35245447 doi: 10.1016/j.ccell.2022.02.006
Meier-Abt, F. et al. The protein landscape of chronic lymphocytic leukemia. Blood 138, 2514–2525 (2021).
pubmed: 34189564 doi: 10.1182/blood.2020009741
Herbst, S. A. et al. Proteogenomics refines the molecular classification of chronic lymphocytic leukemia. Nat. Commun. 13, 6226 (2022).
pubmed: 36266272 pmcid: 9584885 doi: 10.1038/s41467-022-33385-8
Petralia, F. et al. Integrated proteogenomic characterization across major histological types of pediatric brain cancer. Cell 183, 1962–1985.e31 (2020).
pubmed: 33242424 pmcid: 8143193 doi: 10.1016/j.cell.2020.10.044
Griffen, T. L. et al. Proteomic profiling based classification of CLL provides prognostication for modern therapy and identifies novel therapeutic targets. Blood Cancer J. 12, 43 (2022).
pubmed: 35301276 pmcid: 8931092 doi: 10.1038/s41408-022-00623-7
Janker, L. et al. Metabolic, anti-apoptotic and immune evasion strategies of primary human myeloma cells indicate adaptations to hypoxia. Mol. Cell. Proteomics 18, 936–953 (2019).
pubmed: 30792264 pmcid: 6495257 doi: 10.1074/mcp.RA119.001390
Mohamed, A. et al. Concurrent lipidomics and proteomics on malignant plasma cells from multiple myeloma patients: probing the lipid metabolome. PLoS ONE 15, e0227455 (2020).
pubmed: 31914155 pmcid: 6948732 doi: 10.1371/journal.pone.0227455
Ng, Y. L. D. et al. Proteomic profiling reveals CDK6 upregulation as a targetable resistance mechanism for lenalidomide in multiple myeloma. Nat. Commun. 13, 1009 (2022).
pubmed: 35197447 pmcid: 8866544 doi: 10.1038/s41467-022-28515-1
Koomen, D. C. et al. Metabolic changes are associated with melphalan resistance in multiple myeloma. J. Proteome Res. 20, 3134–3149 (2021).
pubmed: 34014671 doi: 10.1021/acs.jproteome.1c00022
Kropivsek, K. et al. Ex vivo drug response heterogeneity reveals personalized therapeutic strategies for patients with multiple myeloma. Nat. Cancer 4, 734–753 (2023).
pubmed: 37081258 pmcid: 10212768 doi: 10.1038/s43018-023-00544-9
Kumar, S. et al. Efficacy of venetoclax as targeted therapy for relapsed/refractory t(11;14) multiple myeloma. Blood 130, 2401–2409 (2017).
pubmed: 29018077 doi: 10.1182/blood-2017-06-788786
Kitadate, A. et al. Multiple myeloma with t(11;14)-associated immature phenotype has lower CD38 expression and higher BCL2 dependence. Cancer Sci. 112, 3645–3654 (2021).
pubmed: 34288263 pmcid: 8409299 doi: 10.1111/cas.15073
Gupta, V. A. et al. Venetoclax sensitivity in multiple myeloma is associated with B-cell gene expression. Blood 137, 3604–3615 (2021).
pubmed: 33649772 pmcid: 8462405 doi: 10.1182/blood.2020007899
Santra, M., Zhan, F., Tian, E., Barlogie, B. & Shaughnessy, J. A subset of multiple myeloma harboring the t(4;14)(p16;q32) translocation lacks FGFR3 expression but maintains anIGH/MMSET fusion transcript. Blood https://doi.org/10.1182/blood-2002-09-2801 (2003).
Walker, B. A. et al. A compendium of myeloma-associated chromosomal copy number abnormalities and their prognostic value. Blood 116, e56–e65 (2010).
pubmed: 20616218 doi: 10.1182/blood-2010-04-279596
Keats, J. J. et al. In multiple myeloma, t(4;14)(p16;q32) is an adverse prognostic factor irrespective of FGFR3 expression. Blood 101, 1520–1529 (2003).
pubmed: 12393535 doi: 10.1182/blood-2002-06-1675
Ghandi, M. et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature 569, 503–508 (2019).
pubmed: 31068700 pmcid: 6697103 doi: 10.1038/s41586-019-1186-3
DepMap, B. DepMap 22Q2 public. Figshare https://doi.org/10.6084/m9.figshare.19700056.v2 (2022).
Hussain, S., Bedekovics, T., Chesi, M., Bergsagel, P. L. & Galardy, P. J. UCHL1 is a biomarker of aggressive multiple myeloma required for disease progression. Oncotarget 6, 40704–40718 (2015).
pubmed: 26513019 pmcid: 4747363 doi: 10.18632/oncotarget.5727
Guo, Q., Xie, J., Dang, C. V., Liu, E. T. & Bishop, J. M. Identification of a large Myc-binding protein that contains RCC1-like repeats. Proc. Natl Acad. Sci. USA 95, 9172–9177 (1998).
pubmed: 9689053 pmcid: 21311 doi: 10.1073/pnas.95.16.9172
Fan, Y. et al. FXR1 regulates transcription and is required for growth of human cancer cells with homozygous deletion. eLife 6, e26129 (2017).
pubmed: 28767039 pmcid: 5595435 doi: 10.7554/eLife.26129
Schmidt, T. M., Fonseca, R. & Usmani, S. Z. Chromosome 1q21 abnormalities in multiple myeloma. Blood Cancer J. 11, 83 (2021).
pubmed: 33927196 pmcid: 8085148 doi: 10.1038/s41408-021-00474-8
Slomp, A. et al. Multiple myeloma with 1q21 amplification is highly sensitive to MCL-1 targeting. Blood Adv. 3, 4202–4214 (2019).
pubmed: 31856269 pmcid: 6929383 doi: 10.1182/bloodadvances.2019000702
Zhang, J. et al. Disruption of KMT2D perturbs germinal center B cell development and promotes lymphomagenesis. Nat. Med. 21, 1190–1198 (2015).
pubmed: 26366712 pmcid: 5145002 doi: 10.1038/nm.3940
Raffel, S. et al. Quantitative proteomics reveals specific metabolic features of acute myeloid leukemia stem cells. Blood 136, 1507–1519 (2020).
pubmed: 32556243 doi: 10.1182/blood.2019003654
Sohn, M. et al. Ahnak promotes tumor metastasis through transforming growth factor-β-mediated epithelial-mesenchymal transition. Sci. Rep. 8, 14379 (2018).
pubmed: 30258109 pmcid: 6158194 doi: 10.1038/s41598-018-32796-2
de Matos Simoes, R. et al. Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias. Nat. Cancer 4, 754–773 (2023).
pubmed: 37237081 pmcid: 10918623 doi: 10.1038/s43018-023-00550-x
Krönke, J. et al. Lenalidomide causes selective degradation of IKZF1 and IKZF3 in multiple myeloma cells. Science 343, 301–305 (2014).
pubmed: 24292625 doi: 10.1126/science.1244851
Lu, G. et al. The myeloma drug lenalidomide promotes the cereblon-dependent destruction of Ikaros proteins. Science 343, 305–309 (2014).
pubmed: 24292623 doi: 10.1126/science.1244917
Shaffer, A. L. et al. IRF4 addiction in multiple myeloma. Nature 454, 226–231 (2008).
pubmed: 18568025 pmcid: 2542904 doi: 10.1038/nature07064
Herbst, D. A. et al. Structure of the human SAGA coactivator complex. Nat. Struct. Mol. Biol. 28, 989–996 (2021).
pubmed: 34811519 pmcid: 8660637 doi: 10.1038/s41594-021-00682-7
Chapuy, B. et al. Discovery and characterization of super-enhancer-associated dependencies in diffuse large B cell lymphoma. Cancer Cell 24, 777–790 (2013).
pubmed: 24332044 pmcid: 4018722 doi: 10.1016/j.ccr.2013.11.003
Zhao, C. et al. POU2AF1, an amplification target at 11q23, promotes growth of multiple myeloma cells by directly regulating expression of a B-cell maturation factor, TNFRSF17. Oncogene 27, 63–75 (2008).
pubmed: 17621271 doi: 10.1038/sj.onc.1210637
Ge, N. L. & Rudikoff, S. Insulin-like growth factor I is a dual effector of multiple myeloma cell growth. Blood 96, 2856–2861 (2000).
pubmed: 11023522 doi: 10.1182/blood.V96.8.2856
Gonçalves, E. et al. Pan-cancer proteomic map of 949 human cell lines. Cancer Cell 40, 835–849.e8 (2022).
pubmed: 35839778 pmcid: 9387775 doi: 10.1016/j.ccell.2022.06.010
Garofalo, C. et al. Preclinical effectiveness of selective inhibitor of IRS-1/2 NT157 in osteosarcoma cell lines. Front. Endocrinol. 6, 74 (2015).
doi: 10.3389/fendo.2015.00074
Berdeja, J. G. et al. Ciltacabtagene autoleucel, a B-cell maturation antigen-directed chimeric antigen receptor T-cell therapy in patients with relapsed or refractory multiple myeloma (CARTITUDE-1): a phase 1b/2 open-label study. Lancet 398, 314–324 (2021).
pubmed: 34175021 doi: 10.1016/S0140-6736(21)00933-8
Munshi, N. C. et al. Idecabtagene vicleucel in relapsed and refractory multiple myeloma. N. Engl. J. Med. 384, 705–716 (2021).
pubmed: 33626253 doi: 10.1056/NEJMoa2024850
Hu, Z. et al. The Cancer Surfaceome Atlas integrates genomic, functional and drug response data to identify actionable targets. Nat. Cancer 2, 1406–1422 (2021).
pubmed: 35121907 pmcid: 9940627 doi: 10.1038/s43018-021-00282-w
Lutz, R. et al. Multiple myeloma long-term survivors display sustained immune alterations decades after first line therapy. Preprint at bioRxiv https://doi.org/10.1101/2023.05.27.542555 (2023).
Cohen, A. D. et al. Initial clinical activity and safety of BFCR4350A, a FcRH5/CD3 T-cell-engaging bispecific antibody, in relapsed/refractory multiple myeloma. Blood 136, 42–43 (2020).
doi: 10.1182/blood-2020-136985
Karlsson, M. et al. A single-cell type transcriptomics map of human tissues. Sci. Adv. 7, eabh2169 (2021).
pubmed: 34321199 pmcid: 8318366 doi: 10.1126/sciadv.abh2169
Chang, R. et al. Upregulated expression of ubiquitin-conjugating enzyme E2Q1 (UBE2Q1) is associated with enhanced cell proliferation and poor prognosis in human hapatocellular carcinoma. J. Mol. Histol. 46, 45–56 (2015).
pubmed: 25311764 doi: 10.1007/s10735-014-9596-x
Topno, R., Singh, I., Kumar, M. & Agarwal, P. Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer. BMC Cancer 21, 220 (2021).
pubmed: 33663405 pmcid: 7934452 doi: 10.1186/s12885-021-07928-z
Li, C. et al. Genetic analysis of multiple myeloma identifies cytogenetic alterations implicated in disease complexity and progression. Cancers 13, 517 (2021).
pubmed: 33572851 pmcid: 7866300 doi: 10.3390/cancers13030517
Kuiper, R. et al. A gene expression signature for high-risk multiple myeloma. Leukemia 26, 2406–2413 (2012).
pubmed: 22722715 doi: 10.1038/leu.2012.127
Patel, J. H. et al. The c-MYC oncoprotein is a substrate of the acetyltransferases hGCN5/PCAF and TIP60. Mol. Cell. Biol. 24, 10826–10834 (2004).
pubmed: 15572685 pmcid: 533976 doi: 10.1128/MCB.24.24.10826-10834.2004
Lee, H. et al. Mechanisms of antigen escape from BCMA- or GPRC5D-targeted immunotherapies in multiple myeloma. Nat. Med. 29, 2295–2306 (2023).
pubmed: 37653344 pmcid: 10504087 doi: 10.1038/s41591-023-02491-5
Da Vià, M. C. et al. Homozygous BCMA gene deletion in response to anti-BCMA CAR T cells in a patient with multiple myeloma. Nat. Med. 27, 616–619 (2021).
pubmed: 33619368 doi: 10.1038/s41591-021-01245-5
Anderson, G. S. F. et al. Unbiased cell surface proteomics identifies SEMA4A as an effective immunotherapy target for myeloma. Blood 139, 2471–2482 (2022).
pubmed: 35134130 pmcid: 11022854 doi: 10.1182/blood.2021015161
Ferguson, I. D. et al. The surfaceome of multiple myeloma cells suggests potential immunotherapeutic strategies and protein markers of drug resistance. Nat. Commun. 13, 4121 (2022).
pubmed: 35840578 pmcid: 9287322 doi: 10.1038/s41467-022-31810-6
Li, F. J. et al. FCRL2 expression predicts IGHV mutation status and clinical progression in chronic lymphocytic leukemia. Blood 112, 179–187 (2008).
pubmed: 18314442 pmcid: 2435687 doi: 10.1182/blood-2008-01-131359
Knop, S. et al. Lenalidomide, adriamycin, dexamethasone for induction followed by stem-cell transplant in newly diagnosed myeloma. Leukemia 31, 1816–1819 (2017).
pubmed: 28439106 doi: 10.1038/leu.2017.124
Mertins, P. et al. Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography–mass spectrometry. Nat. Protoc. 13, 1632–1661 (2018).
pubmed: 29988108 pmcid: 6211289 doi: 10.1038/s41596-018-0006-9
Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).
pubmed: 19029910 doi: 10.1038/nbt.1511
Wang, Z. et al. Direct-to-biology, automated, nano-scale synthesis, and phenotypic screening-enabled E3 ligase modulator discovery. Nat. Commun. 14, 8437 (2023).
pubmed: 38114468 pmcid: 10730884 doi: 10.1038/s41467-023-43614-3
Demichev, V., Messner, C. B., Vernardis, S. I., Lilley, K. S. & Ralser, M. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods 17, 41–44 (2020).
pubmed: 31768060 doi: 10.1038/s41592-019-0638-x
Konermann, S. et al. Genome-scale transcriptional activation by an engineered CRISPR–Cas9 complex. Nature 517, 583–588 (2015).
pubmed: 25494202 doi: 10.1038/nature14136
Sanson, K. R. et al. Optimized libraries for CRISPR–Cas9 genetic screens with multiple modalities. Nat. Commun. 9, 5416 (2018).
pubmed: 30575746 pmcid: 6303322 doi: 10.1038/s41467-018-07901-8
Gaujoux, R. & Seoighe, C. A flexible R package for nonnegative matrix factorization. BMC Bioinformatics 11, 367 (2010).
pubmed: 20598126 pmcid: 2912887 doi: 10.1186/1471-2105-11-367
Gillette, M. A. et al. Proteogenomic characterization reveals therapeutic vulnerabilities in lung adenocarcinoma. Cell 182, 200–225.e35 (2020).
pubmed: 32649874 pmcid: 7373300 doi: 10.1016/j.cell.2020.06.013
Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1523 (2019).
pubmed: 30944313 pmcid: 6447622 doi: 10.1038/s41467-019-09234-6
Pacini, C. et al. Integrated cross-study datasets of genetic dependencies in cancer. Nat. Commun. 12, 1–14 (2021).
doi: 10.1038/s41467-021-21898-7
Krug, K. et al. Proteogenomic landscape of breast cancer tumorigenesis and targeted therapy. Cell 183, 1436–1456.e31 (2020).
pubmed: 33212010 pmcid: 8077737 doi: 10.1016/j.cell.2020.10.036
Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).
pubmed: 29750242 pmcid: 6137996 doi: 10.1093/bioinformatics/bty191
Poell, J. B. et al. ACE: absolute copy number estimation from low-coverage whole-genome sequencing data. Bioinformatics 35, 2847–2849 (2019).
pubmed: 30596895 doi: 10.1093/bioinformatics/bty1055
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).
pubmed: 34062119 pmcid: 8238499 doi: 10.1016/j.cell.2021.04.048

Auteurs

Evelyn Ramberger (E)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Max Delbrück Center for Molecular Medicine, Berlin, Germany.
German Cancer Consortium (DKTK), partner site Berlin, DKFZ and Charité - Universitätsmedizin Berlin, Berlin, Germany.

Valeriia Sapozhnikova (V)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Max Delbrück Center for Molecular Medicine, Berlin, Germany.
German Cancer Consortium (DKTK), partner site Berlin, DKFZ and Charité - Universitätsmedizin Berlin, Berlin, Germany.

Yuen Lam Dora Ng (YLD)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Anna Dolnik (A)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Matthias Ziehm (M)

Max Delbrück Center for Molecular Medicine, Berlin, Germany.
Berlin Institute of Health, Berlin, Germany.

Oliver Popp (O)

Max Delbrück Center for Molecular Medicine, Berlin, Germany.
Berlin Institute of Health, Berlin, Germany.

Eric Sträng (E)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Miriam Kull (M)

Internal Medicine III, University Hospital Ulm, Ulm, Germany.

Florian Grünschläger (F)

German Cancer Research Center (DKFZ), Heidelberg, Germany.
Heidelberg Institute for Stem Cell Technology and Experimental Medicine, Heidelberg, Germany.
Faculty of Biosciences, Heidelberg University, Heidelberg, Germany.

Josefine Krüger (J)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Manuela Benary (M)

Berlin Institute of Health, Berlin, Germany.

Sina Müller (S)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Xiang Gao (X)

Internal Medicine III, University Hospital Ulm, Ulm, Germany.

Arunima Murgai (A)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
German Cancer Consortium (DKTK), partner site Berlin, DKFZ and Charité - Universitätsmedizin Berlin, Berlin, Germany.

Mohamed Haji (M)

Max Delbrück Center for Molecular Medicine, Berlin, Germany.
Berlin Institute of Health, Berlin, Germany.

Annika Schmidt (A)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Raphael Lutz (R)

German Cancer Research Center (DKFZ), Heidelberg, Germany.
Heidelberg Institute for Stem Cell Technology and Experimental Medicine, Heidelberg, Germany.
Department of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.

Axel Nogai (A)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Jan Braune (J)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Dominik Laue (D)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Christian Langer (C)

Internal Medicine III, University Hospital Ulm, Ulm, Germany.

Cyrus Khandanpour (C)

Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Muenster, Muenster, Germany.

Florian Bassermann (F)

Department of Medicine III, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany.

Hartmut Döhner (H)

Internal Medicine III, University Hospital Ulm, Ulm, Germany.

Monika Engelhardt (M)

Freiburg University Hospital, Freiburg, Germany.

Christian Straka (C)

Medizinische Klinik, München Klinik Schwabing, Munich, Germany.

Michael Hundemer (M)

Department of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.

Dieter Beule (D)

Berlin Institute of Health, Berlin, Germany.

Simon Haas (S)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Max Delbrück Center for Molecular Medicine, Berlin, Germany.
German Cancer Consortium (DKTK), partner site Berlin, DKFZ and Charité - Universitätsmedizin Berlin, Berlin, Germany.
Berlin Institute of Health, Berlin, Germany.
German Cancer Research Center (DKFZ), Heidelberg, Germany.
Heidelberg Institute for Stem Cell Technology and Experimental Medicine, Heidelberg, Germany.

Ulrich Keller (U)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Max Delbrück Center for Molecular Medicine, Berlin, Germany.
German Cancer Consortium (DKTK), partner site Berlin, DKFZ and Charité - Universitätsmedizin Berlin, Berlin, Germany.

Hermann Einsele (H)

Department of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany.

Lars Bullinger (L)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
German Cancer Consortium (DKTK), partner site Berlin, DKFZ and Charité - Universitätsmedizin Berlin, Berlin, Germany.

Stefan Knop (S)

Department of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany. stefan.knop@klinikum-nuernberg.de.
Nuremberg General Hospital, Nuremberg, Germany. stefan.knop@klinikum-nuernberg.de.
Paracelsus Medical School, Nuremberg, Germany. stefan.knop@klinikum-nuernberg.de.

Philipp Mertins (P)

Max Delbrück Center for Molecular Medicine, Berlin, Germany. philipp.mertins@mdc-berlin.de.
Berlin Institute of Health, Berlin, Germany. philipp.mertins@mdc-berlin.de.

Jan Krönke (J)

Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany. jan.kroenke@charite.de.
German Cancer Consortium (DKTK), partner site Berlin, DKFZ and Charité - Universitätsmedizin Berlin, Berlin, Germany. jan.kroenke@charite.de.

Classifications MeSH