Abstract
POEMS syndrome is a rare plasma cell dyscrasia. Little is known about its pathogenesis and genetic features. We analyzed the mutational features of purified bone marrow plasma cells from 42 patients newly diagnosed with POEMS syndrome using a two-step strategy. Whole exome sequencing of ten patients showed a total of 170 somatic mutations in exonic regions and splicing sites, with paired peripheral blood mononuclear cells as a control. Three significantly mutated genes—LILRB1 (10%), HEATR9 (20%), and FMNL2 (10%)—and eight mutated known driver genes (MYD88, NFKB2, CHD4, SH2B3, POLE, STAT3, CHD3, and CUX1) were identified. Target region sequencing of 77 genes were then analyzed to validate the mutations in an additional 32 patients. A total of 32 mutated genes were identified, and genes recurrently mutated in more than three patients included CUX1 (19%), DNAH5 (16%), USH2A (16%), KMT2D (16%), and RYR1 (12%). Driver genes of multiple myeloma (BIRC3, LRP1B, KDM6A, and ATM) and eleven genes reported in light-chain amyloidosis were also identified in target region sequencing. Notably, VEGFA mutations were detected in one patient. Our study revealed heterogeneous genomic profiles of bone marrow plasma cells in POEMS syndrome, which might share some similarity to that of other plasma cell diseases.
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References
Suichi T, Misawa S, Beppu M, Takahashi S, Sekiguchi Y, Shibuya K, et al. Prevalence, clinical profiles, and prognosis of POEMS syndrome in Japanese nationwide survey. Neurology. 2019;93:e975–83.
Dispenzieri A. POEMS Syndrome: 2019 Update on diagnosis, risk-stratification, and management. Am J Hematol. 2019;94:812–27.
Dao LN, Hanson CA, Dispenzieri A, Morice WG, Kurtin PJ, Hoyer JD. Bone marrow histopathology in POEMS syndrome: a distinctive combination of plasma cell, lymphoid, and myeloid findings in 87 patients. Blood. 2011;117:6438–44.
Shim H, Seol CA, Park CJ, Cho YU, Seo EJ, Lee JH, et al. POEMS syndrome: bone marrow, laboratory, and clinical findings in 24 Korean patients. Ann Lab Med. 2019;39:561–5.
Li J, Huang Z, Duan MH, Zhang W, Chen M, Cao XX, et al. Characterization of immunoglobulin λ light chain variable region (IGLV) gene and its relationship with clinical features in patients with POEMS syndrome. Ann Hematol. 2012;91:1251–5.
Kawajiri-Manako C, Mimura N, Fukuyo M, Namba H, Rahmutulla B, Nagao Y, et al. Clonal immunoglobulin lambda light-chain gene rearrangements detected by next generation sequencing in POEMS syndrome. Am J Hematol. 2018;93:1161–8.
Bender S, Javaugue V, Saintamand A, Ayala MV, Alizadeh M, Filloux M, et al. Immunoglobulin variable domain high-throughput sequencing reveals specific novel mutational patterns in POEMS syndrome. Blood. 2020;135:1750–8.
Kang WY, Shen KN, Duan MH, Zhang W, Cao XX, Zhou DB, et al. 14q32 translocations and 13q14 deletions are common cytogenetic abnormalities in POEMS syndrome. Eur J Haematol. 2013;91:490–6.
Nagao Y, Mimura N, Takeda J, Yoshida K, Shiozawa Y, Oshima M, et al. Genetic and transcriptional landscape of plasma cells in POEMS syndrome. Leukemia. 2019;33:1723–35.
Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, et al. The human genome browser at UCSC. Genome Res. 2002;12:996–1006.
Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:174–60.
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–9.
Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol. 2013;31:213–9.
Saunders CT, Wong WS, Swamy S, Becq J, Murray LJ, Cheetham RK. Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics. 2012;28:1811–7.
Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38:e164.
Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 2011;39:W316–22.
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a mapreduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–303.
Huang XF, Jian S, Lu JL, Shen KN, Feng J, Zhang CL, et al. Genomic profiling in amyloid light-chain amyloidosis reveals mutation profiles associated with overall survival. Amyloid. 2020;27:36–44.
Hosono N. Genetic abnormalities and pathophysiology of MDS. Int J Clin Oncol. 2019;24:885–92.
Aly M, Ramdzan ZM, Nagata Y, Balasubramanian SK, Hosono N, Makishima H, et al. Distinct clinical and biological implications of CUX1 in myeloid neoplasms. Blood Adv. 2019;3:2164–78.
Richter J, Schlesner M, Hoffmann S, Kreuz M, Leich E, Burkhardt B, et al. Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing. Nat Genet. 2012;44:1316–20.
Wong TN, Miller CA, Jotte MRM, Bagegni N, Baty JD, Schmidt AP, et al. Cellular stressors contribute to the expansion of hematopoietic clones of varying leukemic potential. Nat Commun. 2018;9:455.
Roberts KG, Li Y, Payne-Turner D, Harvey RC, Yang Y-L, Pei D, et al. Targetable kinase-activating lesions in Ph-like acute lymphoblastic leukemia. N Engl J Med. 2014;371:1005–15.
Walker BA, Wardell CP, Melchor L, Hulkki S, Potter NE, Johnson DC, et al. Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4;14) and t(11;14) myeloma. Blood. 2012;120:1077–86.
Morin RD, Assouline S, Alcaide M, Mohajeri A, Johnston RL, Chong L, et al. Genetic landscapes of relapsed and refractory diffuse large B-cell lymphomas. Clin Cancer Res. 2016;22:2290–300.
Morin RD, Mendez-Lago M, Mungall AJ, Goya R, Mungall KL, Corbett RD, et al. Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma. Nature. 2011;476:298–303.
Bolli N, Avet-Loiseau H, Wedge DC, Van Loo P, Alexandrov LB, Martincorena I, et al. Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. Nat Commun. 2014;5:2997.
Manier S, Salem KZ, Park J, Landau DA, Getz G, Ghobrial IM. Genomic complexity of multiple myeloma and its clinical implications. Nat Rev Clin Oncol. 2017;14:100–13.
Szalat R, Munshi NC. Genomic heterogeneity in multiple myeloma. Curr Opin Genet Dev. 2015;30:56–65.
Boyle EM, Ashby C, Wardell CP, Rowczenio D, Sachchithanantham S, Wang Y, et al. The genomic landscape of plasma cells in systemic light chain amyloidosis. Blood. 2018;132:2775–7.
Paiva B, Martinez-Lopez J, Corchete LA, Sanchez-Vega B, Rapado I, Puig N, et al. Phenotypic, transcriptomic, and genomic features of clonal plasma cells in light-chain amyloidosis. Blood. 2016;127:3035–9.
Chyra Z, Sevcikova T, Vojta P, Puterova J, Brozova L, Growkova K, et al. Heterogenous mutation spectrum and deregulated cellular pathways in aberrant plasma cells underline molecular pathology of light-chain amyloidosis. Haematologica. 2020;239756. Online ahead of print.
Nagy A, Bhaduri A, Shahmarvand N, Shahryari J, Zehnder JL, Warnke RA, et al. Next-generation sequencing of idiopathic multicentric and unicentric Castleman disease and follicular dendritic cell sarcomas. Blood Adv. 2018;2:481–91.
Stieglitz E, Taylor-Weiner AN, Chang TY, Gelston LC, Wang YD, Mazor T, et al. The genomic landscape of juvenile myelomonocytic leukemia. Nat Genet. 2015;47:1326–33.
Hulsen T, de Vlieg J, Alkema W. BioVenn—a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams. BMC Genom. 2008;9:488.
Acknowledgements
Institutional research funding was provided by the National Natural Science Foundation of China (Grant No. 81974011, for Jian Li), Beijing Natural Science Foundation (Grant No. 7182128, for Jian Li), The Capital Health Research and Development of Special Fund (no.2018-2-4015, for Jian Li), The CAMS Innovation Fund for Medical Sciences (Grant No. 2016-12M-1-002, for Jian Li), and The National Key Research and Development Program of China (Grant No. 2016YFC0901503, for Jian Li).
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Chen, J., Gao, Xm., Zhao, H. et al. A highly heterogeneous mutational pattern in POEMS syndrome. Leukemia 35, 1100–1107 (2021). https://doi.org/10.1038/s41375-020-01101-4
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DOI: https://doi.org/10.1038/s41375-020-01101-4
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