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Longitudinal analysis of 25 sequential sample-pairs using a custom multiple myeloma mutation sequencing panel (M3P)

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Abstract

Recent advances in genomic sequencing technologies now allow results from deep next-generation sequencing to be obtained within clinically meaningful timeframes, making this an attractive approach to better guide personalized treatment strategies. No multiple myeloma-specific gene panel has been established so far; we therefore designed a 47-gene-targeting gene panel, containing 39 genes known to be mutated in ≥3 % of multiple myeloma cases and eight genes in pathways therapeutically targeted in multiple myeloma (MM). We performed targeted sequencing on tumor/germline DNA of 25 MM patients in which we also had a sequential sample post treatment. Mutation analysis revealed KRAS as the most commonly mutated gene (36 % in each time point), followed by NRAS (20 and 16 %), TP53 (16 and 16 %), DIS3 (16 and 16 %), FAM46C (12 and 16 %), and SP140 (12 and 12 %). We successfully tracked clonal evolution and identified mutation acquisition and/or loss in FAM46C, FAT1, KRAS, NRAS, SPEN, PRDM1, NEB, and TP53 as well as two mutations in XBP1, a gene associated with bortezomib resistance. Thus, we present the first longitudinal analysis of a MM-specific targeted sequencing gene panel that can be used for individual tumor characterization and for tracking clonal evolution over time.

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References

  1. Brioli A, Melchor L, Cavo M, Morgan GJ (2014) The impact of intra-clonal heterogeneity on the treatment of multiple myeloma. Br J Haematol 165(4):441–454. doi:10.1111/bjh.12805

    Article  PubMed  Google Scholar 

  2. Egan JB, Shi CX, Tembe W, Christoforides A, Kurdoglu A, Sinari S, Middha S, Asmann Y, Schmidt J, Braggio E, Keats JJ, Fonseca R, Bergsagel PL, Craig DW, Carpten JD, Stewart AK (2012) Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides. Blood 120(5):1060–1066. doi:10.1182/blood-2012-01-405977

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  3. Melchor L, Brioli A, Wardell CP, Murison A, Potter NE, Kaiser MF, Fryer RA, Johnson DC, Begum DB, Hulkki Wilson S, Vijayaraghavan G, Titley I, Cavo M, Davies FE, Walker BA, Morgan GJ (2014) Single-cell genetic analysis reveals the composition of initiating clones and phylogenetic patterns of branching and parallel evolution in myeloma. Leukemia 28(8):1705–1715. doi:10.1038/leu.2014.13

    Article  CAS  PubMed  Google Scholar 

  4. Keats JJ, Chesi M, Egan JB, Garbitt VM, Palmer SE, Braggio E, Van Wier S, Blackburn PR, Baker AS, Dispenzieri A, Kumar S, Rajkumar SV, Carpten JD, Barrett M, Fonseca R, Stewart AK, Bergsagel PL (2012) Clonal competition with alternating dominance in multiple myeloma. Blood 120(5):1067–1076. doi:10.1182/blood-2012-01-405985

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  5. Lonial S, Yellapantula VD, Liang W, Kurdoglu A, Aldrich J, Legendre CM, Stephenson K, Adkins J, McDonald J, Helland A, Russell M, Christofferson A, Cuyugan L, Rohrer D, Blanski A, Hodges M, CoMMpass Network M, Derome M, Auclair D, Kidd PG, Jewell S, Craig D, Carpten J, Keats JJ (2014) Interim analysis of the Mmrf Commpass Trial: identification of novel rearrangements potentially associated with disease initiation and progression. Blood 124(21):722–722

    Google Scholar 

  6. Lohr JG, Stojanov P, Carter SL, Cruz-Gordillo P, Lawrence MS, Auclair D, Sougnez C, Knoechel B, Gould J, Saksena G, Cibulskis K, McKenna A, Chapman MA, Straussman R, Levy J, Perkins LM, Keats JJ, Schumacher SE, Rosenberg M, Multiple Myeloma Research C, Getz G, Golub TR (2014) Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. Cancer Cell 25(1):91–101. doi:10.1016/j.ccr.2013.12.015

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. Bolli N, Avet-Loiseau H, Wedge DC, Van Loo P, Alexandrov LB, Martincorena I, Dawson KJ, Iorio F, Nik-Zainal S, Bignell GR, Hinton JW, Li Y, Tubio JM, McLaren S, O’ Meara S, Butler AP, Teague JW, Mudie L, Anderson E, Rashid N, Tai YT, Shammas MA, Sperling AS, Fulciniti M, Richardson PG, Parmigiani G, Magrangeas F, Minvielle S, Moreau P, Attal M, Facon T, Futreal PA, Anderson KC, Campbell PJ, Munshi NC (2014) Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. Nat Commun 5:2997. doi:10.1038/ncomms3997

    Article  PubMed Central  PubMed  Google Scholar 

  8. Faiman B (2014) Myeloma Genetics and Genomics: Practice Implications and Future Directions. Clin Lymphoma Myeloma Leuk. doi:10.1016/j.clml.2014.07.008

    Google Scholar 

  9. Kortum KM, Langer C, Monge J, Bruins L, Egan JB, Zhu YX, Shi CX, Jedlowski P, Schmidt J, Ojha J, Bullinger L, Liebisch P, Kull M, Champion MD, Van Wier S, Ahmann G, Rasche L, Knop S, Fonseca R, Einsele H, Stewart AK, Braggio E (2014) Targeted sequencing using a 47 gene multiple myeloma mutation panel (M P) in -17p high risk disease. Br J Haematol. doi:10.1111/bjh.13171

    PubMed Central  Google Scholar 

  10. Chapman MA, Lawrence MS, Keats JJ, Cibulskis K, Sougnez C, Schinzel AC, Harview CL, Brunet JP, Ahmann GJ, Adli M, Anderson KC, Ardlie KG, Auclair D, Baker A, Bergsagel PL, Bernstein BE, Drier Y, Fonseca R, Gabriel SB, Hofmeister CC, Jagannath S, Jakubowiak AJ, Krishnan A, Levy J, Liefeld T, Lonial S, Mahan S, Mfuko B, Monti S, Perkins LM, Onofrio R, Pugh TJ, Rajkumar SV, Ramos AH, Siegel DS, Sivachenko A, Stewart AK, Trudel S, Vij R, Voet D, Winckler W, Zimmerman T, Carpten J, Trent J, Hahn WC, Garraway LA, Meyerson M, Lander ES, Getz G, Golub TR (2011) Initial genome sequencing and analysis of multiple myeloma. Nature 471(7339):467–472. doi:10.1038/nature09837

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Kumar P, Henikoff S, Ng PC (2009) Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4(7):1073–1081. doi:10.1038/nprot.2009.86

    Article  CAS  PubMed  Google Scholar 

  12. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP (2012) Predicting the functional effect of amino acid substitutions and indels. PLoS One 7(10):e46688. doi:10.1371/journal.pone.0046688

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  13. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR (2010) A method and server for predicting damaging missense mutations. Nat Methods 7(4):248–249. doi:10.1038/nmeth0410-248

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  14. Forbes SA, Tang G, Bindal N, Bamford S, Dawson E, Cole C, Kok CY, Jia M, Ewing R, Menzies A, Teague JW, Stratton MR, Futreal PA (2010) COSMIC (the Catalogue of Somatic Mutations in Cancer): a resource to investigate acquired mutations in human cancer. Nucleic Acids Res 38(Database issue):D652–D657. doi:10.1093/nar/gkp995

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Egan JB, Kortuem KM, Kurdoglu A, Izatt T, Aldrich J, Reiman R, Phillips L, Baker A, Shi CX, Schmidt J, Liang WS, Craig DW, Carpten JD, Stewart AK (2013) Extramedullary myeloma whole genome sequencing reveals novel mutations in Cereblon, proteasome subunit G2 and the glucocorticoid receptor in multi drug resistant disease. Br J Haematol 161(5):748–751. doi:10.1111/bjh.12291

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. Leung-Hagesteijn C, Erdmann N, Cheung G, Keats JJ, Stewart AK, Reece DE, Chung KC, Tiedemann RE (2013) Xbp1s-negative tumor B cells and pre-plasmablasts mediate therapeutic proteasome inhibitor resistance in multiple myeloma. Cancer Cell 24(3):289–304. doi:10.1016/j.ccr.2013.08.009

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  17. Walker BA, Wardell CP, Melchor L, Brioli A, Johnson DC, Kaiser MF, Mirabella F, Lopez-Corral L, Humphray S, Murray L, Ross M, Bentley D, Gutierrez NC, Garcia-Sanz R, San Miguel J, Davies FE, Gonzalez D, Morgan GJ (2014) Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms. Leukemia 28(2):384–390. doi:10.1038/leu.2013.199

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  18. Walker BA, Wardell CP, Melchor L, Hulkki S, Potter NE, Johnson DC, Fenwick K, Kozarewa I, Gonzalez D, Lord CJ, Ashworth A, Davies FE, Morgan GJ (2012) Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4;14) and t(11;14) myeloma. Blood 120(5):1077–1086. doi:10.1182/blood-2012-03-412981

    Article  CAS  PubMed  Google Scholar 

  19. Basu U, Meng FL, Keim C, Grinstein V, Pefanis E, Eccleston J, Zhang T, Myers D, Wasserman CR, Wesemann DR, Januszyk K, Gregory RI, Deng H, Lima CD, Alt FW (2011) The RNA exosome targets the AID cytidine deaminase to both strands of transcribed duplex DNA substrates. Cell 144(3):353–363. doi:10.1016/j.cell.2011.01.001

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. Parsons DW, Li M, Zhang X, Jones S, Leary RJ, Lin JC, Boca SM, Carter H, Samayoa J, Bettegowda C, Gallia GL, Jallo GI, Binder ZA, Nikolsky Y, Hartigan J, Smith DR, Gerhard DS, Fults DW, VandenBerg S, Berger MS, Marie SK, Shinjo SM, Clara C, Phillips PC, Minturn JE, Biegel JA, Judkins AR, Resnick AC, Storm PB, Curran T, He Y, Rasheed BA, Friedman HS, Keir ST, McLendon R, Northcott PA, Taylor MD, Burger PC, Riggins GJ, Karchin R, Parmigiani G, Bigner DD, Yan H, Papadopoulos N, Vogelstein B, Kinzler KW, Velculescu VE (2011) The genetic landscape of the childhood cancer medulloblastoma. Science 331(6016):435–439. doi:10.1126/science.1198056

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Ding L, Ley TJ, Larson DE, Miller CA, Koboldt DC, Welch JS, Ritchey JK, Young MA, Lamprecht T, McLellan MD, McMichael JF, Wallis JW, Lu C, Shen D, Harris CC, Dooling DJ, Fulton RS, Fulton LL, Chen K, Schmidt H, Kalicki-Veizer J, Magrini VJ, Cook L, McGrath SD, Vickery TL, Wendl MC, Heath S, Watson MA, Link DC, Tomasson MH, Shannon WD, Payton JE, Kulkarni S, Westervelt P, Walter MJ, Graubert TA, Mardis ER, Wilson RK, DiPersio JF (2012) Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature 481(7382):506–510. doi:10.1038/nature10738

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  22. Rose AE, Poliseno L, Wang J, Clark M, Pearlman A, Wang G, Vega Y Saenz de Miera EC, Medicherla R, Christos PJ, Shapiro R, Pavlick A, Darvishian F, Zavadil J, Polsky D, Hernando E, Ostrer H, Osman I (2011) Integrative genomics identifies molecular alterations that challenge the linear model of melanoma progression. Cancer Res 71(7):2561–2571. doi:10.1158/0008-5472.CAN-10-2958

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. Tomecki R, Drazkowska K, Kucinski I, Stodus K, Szczesny RJ, Gruchota J, Owczarek EP, Kalisiak K, Dziembowski A (2014) Multiple myeloma-associated hDIS3 mutations cause perturbations in cellular RNA metabolism and suggest hDIS3 PIN domain as a potential drug target. Nucleic Acids Res 42(2):1270–1290. doi:10.1093/nar/gkt930

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Ling PD, Peng RS, Nakajima A, Yu JH, Tan J, Moses SM, Yang WH, Zhao B, Kieff E, Bloch KD, Bloch DB (2005) Mediation of Epstein-Barr virus EBNA-LP transcriptional coactivation by Sp100. EMBO J 24(20):3565–3575. doi:10.1038/sj.emboj.7600820

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  25. Di Bernardo MC, Crowther-Swanepoel D, Broderick P, Webb E, Sellick G, Wild R, Sullivan K, Vijayakrishnan J, Wang Y, Pittman AM, Sunter NJ, Hall AG, Dyer MJ, Matutes E, Dearden C, Mainou-Fowler T, Jackson GH, Summerfield G, Harris RJ, Pettitt AR, Hillmen P, Allsup DJ, Bailey JR, Pratt G, Pepper C, Fegan C, Allan JM, Catovsky D, Houlston RS (2008) A genome-wide association study identifies six susceptibility loci for chronic lymphocytic leukemia. Nat Genet 40(10):1204–1210. doi:10.1038/ng.219

    Article  PubMed  Google Scholar 

  26. Zhou JR, Fu ZX, Wei LZ, Li YP, Li JC (2007) Identification of tumor-associated proteins in laryngeal squamous cell carcinoma by proteomics. Chin J Otorhinolaryngol Head Neck Surg 42(12):934–938

    Google Scholar 

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Funding source supporting this work

This work is supported by grants R01 CA83724, CA167511, and CA183968, ECOG CA 21115 T, Predolin Foundation, Mayo Clinic Cancer Center, the Mayo Foundation, and the DFG (Ko 4604/1-1 to KMK, BU 1339/7-2 and BU 1339/3-1 to LBu, and LA 2414/2-1 to CL); EB has support by the Henry Predolin Foundation, the Marriott Specialized Workforce Development Awards in Individualized Medicine and the Fraternal Order of Eagles.

Conflict of interests

KMK, CL, JM, LBr, YXZ, CXS, PJ, JBE, JO, LBu, MK, GA, LR, SK, HE, AKS, and EB declare that they have no conflict of interest. RF is a Clinical Investigator of the Damon Runyon Cancer Research Fund and received a patent for the prognostication of MM based on genetic categorization of the disease. He has received consulting fees from Medtronic, Otsuka, Celgene, Genzyme, BMS, Lilly, Onyx, Binding Site, Millennium, and AMGEN. He also has sponsored research from Cylene and Onyx.

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Authors and Affiliations

  1. Division of Hematology - Oncology, Mayo Clinic, Scottsdale, AZ, USA

    K. M. Kortüm, J. Monge, L. Bruins, Y. X. Zhu, C. X. Shi, P. Jedlowski, J. Ojha, G. Ahmann, R. Fonseca, A. K. Stewart & Esteban Braggio

  2. Department of Internal Medicine III, University Hospital of Ulm, Ulm, Germany

    C. Langer, L. Bullinger & M. Kull

  3. Comprehensive Cancer Center, Mayo Clinic, Scottsdale, AZ, USA

    J. B. Egan

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

    L. Rasche, S Knop & H. Einsele

Authors
  1. K. M. Kortüm
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  2. C. Langer
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  3. J. Monge
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  4. L. Bruins
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  5. Y. X. Zhu
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  6. C. X. Shi
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  7. P. Jedlowski
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  8. J. B. Egan
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  9. J. Ojha
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  10. L. Bullinger
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  11. M. Kull
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  12. G. Ahmann
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  13. L. Rasche
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  14. S Knop
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  15. R. Fonseca
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  17. A. K. Stewart
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  18. Esteban Braggio
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Correspondence to Esteban Braggio.

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Kortüm, K.M., Langer, C., Monge, J. et al. Longitudinal analysis of 25 sequential sample-pairs using a custom multiple myeloma mutation sequencing panel (M3P). Ann Hematol 94, 1205–1211 (2015). https://doi.org/10.1007/s00277-015-2344-9

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  • DOI: https://doi.org/10.1007/s00277-015-2344-9

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