Skip to main content
SpringerLink
Log in

The use of molecular-based risk stratification and pharmacogenomics for outcome prediction and personalized therapeutic management of multiple myeloma

  • Progress in Hematology
  • Understanding the pathogenesis and the evolving treatment paradigm for multiple myeloma in the era of novel agents
  • Published:
International Journal of Hematology Aims and scope Submit manuscript

Abstract

Despite improvement in therapeutic efficacy, multiple myeloma (MM) remains incurable with a median survival of approximately 10 years. Gene-expression profiling (GEP) can be used to elucidate the molecular basis for resistance to chemotherapy through global assessment of molecular alterations that exist at diagnosis, after therapeutic treatment and that evolve during tumor progression. Unique GEP signatures associated with recurrent chromosomal translocations and ploidy changes have defined molecular classes with differing clinical features and outcomes. When compared to other stratification systems the GEP70 test remained a significant predictor of outcome, reduced the number of patients classified with a poor prognosis, and identified patients at increased risk of relapse despite their standard clinico-pathologic and genetic findings. GEP studies of serial samples showed that risk increases over time, with relapsed disease showing GEP shifts toward a signature of poor outcomes. GEP signatures of myeloma cells after therapy were prognostic for event-free and overall survival and thus may be used to identify novel strategies for overcoming drug resistance. This brief review will focus on the use of GEP of MM to define high-risk myeloma, and elucidate underlying mechanisms that are beginning to change clinical decision-making and inform drug design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Palumbo A, Anderson KC. Multiple myeloma. N Engl J Med. 2011;364:1046–60.

    Article  CAS  PubMed  Google Scholar 

  2. Barlogie B, Zangari M, Bolejack V, Hollmig K, Anaissie E, van RF, et al. Superior 12-year survival after at least 4-year continuous remission with tandem transplantations for multiple myeloma. Clin Lymphoma Myeloma. 2006;6:469–74.

    Article  PubMed  Google Scholar 

  3. Anderson KC. Oncogenomics to target myeloma in the bone marrow microenvironment. Clin Cancer Res. 2011;17:1225–33.

    Article  CAS  PubMed  Google Scholar 

  4. Palumbo A, Attal M, Roussel M. Shifts in the therapeutic paradigm for patients newly diagnosed with multiple myeloma: maintenance therapy and overall survival. Clin Cancer Res. 2011;17:1253–63.

    Article  PubMed  Google Scholar 

  5. Lonial S, Mitsiades CS, Richardson PG. Treatment options for relapsed and refractory multiple myeloma. Clin Cancer Res. 2011;17:1264–77.

    Article  PubMed  Google Scholar 

  6. Hoering A, Crowley J, Shaughnessy JD Jr, Hollmig K, Alsayed Y, Szymonifka J, et al. Complete remission in multiple myeloma examined as time-dependent variable in terms of both onset and duration in Total Therapy protocols. Blood. 2009;114:1299–305.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Barlogie B, Tricot G, Anaissie E, Shaughnessy J, Rasmussen E, van RF, et al. Thalidomide and hematopoietic-cell transplantation for multiple myeloma. N Engl J Med. 2006;354:1021–30.

    Article  CAS  PubMed  Google Scholar 

  8. Mitsiades CS, Davies FE, Laubach JP, Joshua D, San MJ, Anderson KC, et al. Future directions of next-generation novel therapies, combination approaches, and the development of personalized medicine in myeloma. J Clin Oncol. 2011;29:1916–23.

    Article  PubMed  Google Scholar 

  9. Barlogie B, Tricot G, Haessler J, van RF, Cottler-Fox M, Anaissie E, et al. Cytogenetically defined myelodysplasia after melphalan-based autotransplantation for multiple myeloma linked to poor hematopoietic stem-cell mobilization: the Arkansas experience in more than 3,000 patients treated since 1989. Blood. 2008;111:94–100.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Zhan F, Huang Y, Colla S, Stewart JP, Hanamura I, Gupta S, et al. The molecular classification of multiple myeloma. Blood. 2006;108:2020–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Nair B, Shaughnessy JD Jr, Zhou Y, Astrid-Cartron M, Qu P, van RF, et al. Gene expression profiling of plasma cells at myeloma relapse from tandem transplantation trial Total Therapy 2 predicts subsequent survival. Blood. 2009;113:6572–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Fonseca R, Barlogie B, Bataille R, Bastard C, Bergsagel PL, Chesi M, et al. Genetics and cytogenetics of multiple myeloma: a workshop report. Cancer Res. 2004;64:1546–58.

    Article  CAS  PubMed  Google Scholar 

  13. Munshi NC, Avet-Loiseau H. Genomics in multiple myeloma. Clin Cancer Res. 2011;17:1234–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chapman MA, Lawrence MS, Keats JJ, Cibulskis K, Sougnez C, Schinzel AC, et al. Initial genome sequencing and analysis of multiple myeloma. Nature. 2011;471:467–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Stewart AK. Union of forces advances myeloma care. Blood. 2010;116:674–5.

    Article  CAS  PubMed  Google Scholar 

  16. Zhan F, Hardin J, Kordsmeier B, Bumm K, Zheng M, Tian E, et al. Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells. Blood. 2002;99:1745–57.

    Article  CAS  PubMed  Google Scholar 

  17. Ribatti D, Nico B, Vacca A. Importance of the bone marrow microenvironment in inducing the angiogenic response in multiple myeloma. Oncogene. 2006;25:4257–66.

    Article  CAS  PubMed  Google Scholar 

  18. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403:503–11.

    Article  CAS  PubMed  Google Scholar 

  19. Shaughnessy JD Jr, Zhan F, Burington BE, Huang Y, Colla S, Hanamura I, et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood. 2007;109:2276–84.

    Article  CAS  PubMed  Google Scholar 

  20. Shaughnessy JD Jr, Haessler J, van RF, Anaissie E, Pineda-Roman M, Cottler-Fox M, et al. Testing standard and genetic parameters in 220 patients with multiple myeloma with complete data sets: superiority of molecular genetics. Br J Haematol. 2007;137:530–6.

    Article  CAS  PubMed  Google Scholar 

  21. Waheed S, Shaughnessy JD, van RF, Alsayed Y, Nair B, Anaissie E, et al. International staging system and metaphase cytogenetic abnormalities in the era of gene expression profiling data in multiple myeloma treated with total therapy 2 and 3 protocols. Cancer. 2011;117:1001–9.

    Article  PubMed  Google Scholar 

  22. Decaux O, Lode L, Magrangeas F, Charbonnel C, Gouraud W, Jezequel P, et al. Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myelome. J Clin Oncol. 2008;26:4798–805.

    Article  CAS  PubMed  Google Scholar 

  23. Mulligan G, Mitsiades C, Bryant B, Zhan F, Chng WJ, Roels S, et al. Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib. Blood. 2007;109:3177–88.

    Article  CAS  PubMed  Google Scholar 

  24. Zhan F, Barlogie B, Mulligan G, Shaughnessy JD Jr, Bryant B. High-risk myeloma: a gene expression based risk-stratification model for newly diagnosed multiple myeloma treated with high-dose therapy is predictive of outcome in relapsed disease treated with single-agent bortezomib or high-dose dexamethasone. Blood. 2008;111:968–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Chng WJ, Kuehl WM, Bergsagel PL, Fonseca R. Translocation t(4;14) retains prognostic significance even in the setting of high-risk molecular signature. Leukemia. 2008;22:459–61.

    Article  CAS  PubMed  Google Scholar 

  26. Kuehl WM, Bergsagel PL. Multiple myeloma: evolving genetic events and host interactions. Nat Rev Cancer. 2002;2:175–87.

    Article  CAS  PubMed  Google Scholar 

  27. Keats JJ, Reiman T, Maxwell CA, Taylor BJ, Larratt LM, Mant MJ, et al. In multiple myeloma, t(4;14)(p16;q32) is an adverse prognostic factor irrespective of FGFR3 expression. Blood. 2003;101:1520–9.

    Article  CAS  PubMed  Google Scholar 

  28. Chesi M, Nardini E, Lim RS, Smith KD, Kuehl WM, Bergsagel PL. The t(4;14) translocation in myeloma dysregulates both FGFR3 and a novel gene, MMSET, resulting in IgH/MMSET hybrid transcripts. Blood. 1998;92:3025–34.

    CAS  PubMed  Google Scholar 

  29. Santra M, Zhan F, Tian E, Barlogie B, Shaughnessy J Jr. A subset of multiple myeloma harboring the t(4;14)(p16;q32) translocation lacks FGFR3 expression but maintains an IGH/MMSET fusion transcript. Blood. 2003;101:2374–6.

    Article  CAS  PubMed  Google Scholar 

  30. Dring AM, Davies FE, Fenton JA, Roddam PL, Scott K, Gonzalez D, et al. A global expression-based analysis of the consequences of the t(4;14) translocation in myeloma. Clin Cancer Res. 2004;10:5692–701.

    Article  CAS  PubMed  Google Scholar 

  31. Hurt EM, Wiestner A, Rosenwald A, Shaffer AL, Campo E, Grogan T, et al. Overexpression of c-maf is a frequent oncogenic event in multiple myeloma that promotes proliferation and pathological interactions with bone marrow stroma. Cancer Cell. 2004;5:191–9.

    Article  CAS  PubMed  Google Scholar 

  32. Tian E, Zhan F, Walker R, Rasmussen E, Ma Y, Barlogie B, et al. The role of the Wnt-signaling antagonist DKK1 in the development of osteolytic lesions in multiple myeloma. N Engl J Med. 2003;349:2483–94.

    Article  CAS  PubMed  Google Scholar 

  33. Lin P, Mahdavy M, Zhan F, Zhang HZ, Katz RL, Shaughnessy JD. Expression of PAX5 in CD20-positive multiple myeloma assessed by immunohistochemistry and oligonucleotide microarray. Mod Pathol. 2004;17:1217–22.

    Article  CAS  PubMed  Google Scholar 

  34. Bergsagel PL, Kuehl WM. Molecular pathogenesis and a consequent classification of multiple myeloma. J Clin Oncol. 2005;23:6333–8.

    Article  CAS  PubMed  Google Scholar 

  35. Bartel TB, Haessler J, Brown TL, Shaughnessy JD Jr, van RF, Anaissie E, et al. F18-fluorodeoxyglucose positron emission tomography in the context of other imaging techniques and prognostic factors in multiple myeloma. Blood. 2009;114:2068–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Yin JJ, Mohammad KS, Kakonen SM, Harris S, Wu-Wong JR, Wessale JL, et al. A causal role for endothelin-1 in the pathogenesis of osteoblastic bone metastases. Proc Natl Acad Sci USA. 2003;100:10954–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Clines GA, Mohammad KS, Bao Y, Stephens OW, Suva LJ, Shaughnessy JD Jr, et al. Dickkopf homolog 1 mediates endothelin-1-stimulated new bone formation. Mol Endocrinol. 2007;21:486–98.

    Article  CAS  PubMed  Google Scholar 

  38. Bergsagel PL, Kuehl WM, Zhan F, Sawyer J, Barlogie B, Shaughnessy J Jr. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood. 2005;106:296–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Chesi M, Bergsagel PL, Brents LA, Smith CM, Gerhard DS, Kuehl WM. Dysregulation of cyclin D1 by translocation into an IgH gamma switch region in two multiple myeloma cell lines. Blood. 1996;88:674–81.

    CAS  PubMed  Google Scholar 

  40. Shaughnessy J Jr, Gabrea A, Qi Y, Brents L, Zhan F, Tian E, et al. Cyclin D3 at 6p21 is dysregulated by recurrent chromosomal translocations to immunoglobulin loci in multiple myeloma. Blood. 2001;98:217–23.

    Article  CAS  PubMed  Google Scholar 

  41. Hanamura I, Stewart JP, Huang Y, Zhan F, Santra M, Sawyer JR, et al. Frequent gain of chromosome band 1q21 in plasma-cell dyscrasias detected by fluorescence in situ hybridization: incidence increases from MGUS to relapsed myeloma and is related to prognosis and disease progression following tandem stem-cell transplantation. Blood. 2006;108:1724–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Carrasco DR, Tonon G, Huang Y, Zhang Y, Sinha R, Feng B, et al. High-resolution genomic profiles define distinct clinico-pathogenetic subgroups of multiple myeloma patients. Cancer Cell. 2006;9:313–25.

    Article  CAS  PubMed  Google Scholar 

  43. Rosinol L, Carrio A, Blade J, Queralt R, Aymerich M, Cibeira MT, et al. Comparative genomic hybridisation identifies two variants of smoldering multiple myeloma. Br J Haematol. 2005;130:729–32.

    Article  CAS  PubMed  Google Scholar 

  44. Fabris S, Ronchetti D, Agnelli L, Baldini L, Morabito F, Bicciato S, et al. Transcriptional features of multiple myeloma patients with chromosome 1q gain. Leukemia. 2007;21:1113–6.

    CAS  PubMed  Google Scholar 

  45. Agnelli L, Mosca L, Fabris S, Lionetti M, Andronache A, Kwee I, et al. A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide gene dosage effect. Genes Chromosomes Cancer. 2009;48:603–14.

    Article  CAS  PubMed  Google Scholar 

  46. Carew JS, Nawrocki ST, Krupnik YV, Dunner K Jr, McConkey DJ, Keating MJ, et al. Targeting endoplasmic reticulum protein transport: a novel strategy to kill malignant B cells and overcome fludarabine resistance in CLL. Blood. 2006;107:222–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Avet-Loiseau H, Attal M, Moreau P, Charbonnel C, Garban F, Hulin C, et al. Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myelome. Blood. 2007;109:3489–95.

    Article  CAS  PubMed  Google Scholar 

  48. Fonseca R, Blood E, Rue M, Harrington D, Oken MM, Kyle RA, et al. Clinical and biologic implications of recurrent genomic aberrations in myeloma. Blood. 2003;101:4569–75.

    Article  CAS  PubMed  Google Scholar 

  49. Pineda-Roman M, Zangari M, Haessler J, Anaissie E, Tricot G, van RF, et al. Sustained complete remissions in multiple myeloma linked to bortezomib in total therapy 3: comparison with total therapy 2. Br J Haematol. 2008;140:625–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. San Miguel JF, Schlag R, Khuageva NK, Dimopoulos MA, Shpilberg O, Kropff M, et al. Bortezomib plus melphalan and prednisone for initial treatment of multiple myeloma. N Engl J Med. 2008;359:906–17.

    Article  CAS  PubMed  Google Scholar 

  51. Avet-Loiseau H, Leleu X, Roussel M, Moreau P, Guerin-Charbonnel C, Caillot D, et al. Bortezomib plus dexamethasone induction improves outcome of patients with t(4;14) myeloma but not outcome of patients with del(17p). J Clin Oncol. 2010;28:4630–4.

    Article  CAS  PubMed  Google Scholar 

  52. Xiong W, Wu X, Starnes S, Johnson SK, Haessler J, Wang S, et al. An analysis of the clinical and biologic significance of TP53 loss and the identification of potential novel transcriptional targets of TP53 in multiple myeloma. Blood. 2008;112:4235–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Zhou Y, Chen L, Barlogie B, Stephens O, Wu X, Williams D, et al. High-risk myeloma is associated with global elevation of miRNAs and overexpression of EIF2C2/AGO2. PNAS. 2010;107(17):7904–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Chauhan D, Auclair D, Robinson EK, Hideshima T, Li G, Podar K, et al. Identification of genes regulated by dexamethasone in multiple myeloma cells using oligonucleotide arrays. Oncogene. 2002;21:1346–58.

    Article  CAS  PubMed  Google Scholar 

  55. Mitsiades N, Mitsiades CS, Poulaki V, Chauhan D, Fanourakis G, Gu X, et al. Molecular sequelae of proteasome inhibition in human multiple myeloma cells. Proc Natl Acad Sci USA. 2002;99:14374–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Mitsiades N, Mitsiades CS, Richardson PG, Poulaki V, Tai YT, Chauhan D, et al. The proteasome inhibitor PS-341 potentiates sensitivity of multiple myeloma cells to conventional chemotherapeutic agents: therapeutic applications. Blood. 2003;101:2377–80.

    Article  CAS  PubMed  Google Scholar 

  57. Chauhan D, Li G, Auclair D, Hideshima T, Richardson P, Podar K, et al. Identification of genes regulated by 2-methoxyestradiol (2ME2) in multiple myeloma cells using oligonucleotide arrays. Blood. 2003;101:3606–14.

    Article  CAS  PubMed  Google Scholar 

  58. Mitsiades CS, Mitsiades NS, McMullan CJ, Poulaki V, Shringarpure R, Hideshima T, et al. Transcriptional signature of histone deacetylase inhibition in multiple myeloma: biological and clinical implications. Proc Natl Acad Sci USA. 2004;101:540–5.

    Article  CAS  PubMed  Google Scholar 

  59. Neri P, Tagliaferri P, Di Martino MT, Calimeri T, Amodio N, Bulotta A, et al. In vivo anti-myeloma activity and modulation of gene expression profile induced by valproic acid, a histone deacetylase inhibitor. Br J Haematol. 2008;143:520–31.

    CAS  PubMed  Google Scholar 

  60. Mitsiades CS, Mitsiades NS, McMullan CJ, Poulaki V, Shringarpure R, Akiyama M, et al. Inhibition of the insulin-like growth factor receptor-1 tyrosine kinase activity as a therapeutic strategy for multiple myeloma, other hematologic malignancies, and solid tumors. Cancer Cell. 2004;5:221–30.

    Article  CAS  PubMed  Google Scholar 

  61. Tassone P, Neri P, Burger R, Savino R, Shammas M, Catley L, et al. Combination therapy with interleukin-6 receptor superantagonist Sant7 and dexamethasone induces antitumor effects in a novel SCID-hu In vivo model of human multiple myeloma. Clin Cancer Res. 2005;11:4251–8.

    Article  CAS  PubMed  Google Scholar 

  62. Sukhdeo K, Mani M, Zhang Y, Dutta J, Yasui H, Rooney MD, et al. Targeting the beta-catenin/TCF transcriptional complex in the treatment of multiple myeloma. Proc Natl Acad Sci USA. 2007;104:7516–21.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Raje N, Kumar S, Hideshima T, Ishitsuka K, Yasui H, Chhetri S, et al. Didox, a ribonucleotide reductase inhibitor, induces apoptosis and inhibits DNA repair in multiple myeloma cells. Br J Haematol. 2006;135:52–61.

    Article  CAS  PubMed  Google Scholar 

  64. Neri P, Tassone P, Shammas M, Yasui H, Schipani E, Batchu RB, et al. Biological pathways and in vivo antitumor activity induced by Atiprimod in myeloma. Leukemia. 2007;21:2519–26.

    Article  CAS  PubMed  Google Scholar 

  65. Heller G, Schmidt WM, Ziegler B, Holzer S, Mullauer L, Bilban M, et al. Genome-wide transcriptional response to 5-aza-2′-deoxycytidine and trichostatin a in multiple myeloma cells. Cancer Res. 2008;68:44–54.

    Article  CAS  PubMed  Google Scholar 

  66. Duus J, Bahar HI, Venkataraman G, Ozpuyan F, Izban KF, Al-Masri H, et al. Analysis of expression of heat shock protein-90 (HSP90) and the effects of HSP90 inhibitor (17-AAG) in multiple myeloma. Leuk Lymphoma. 2006;47:1369–78.

    Article  CAS  PubMed  Google Scholar 

  67. Ocio EM, Maiso P, Chen X, Garayoa M, Alvarez-Fernandez S, San-Segundo L, et al. Zalypsis: a novel marine-derived compound with potent antimyeloma activity that reveals high sensitivity of malignant plasma cells to DNA double-strand breaks. Blood. 2009;113:3781–91.

    Article  CAS  PubMed  Google Scholar 

  68. Burington B, Barlogie B, Zhan F, Crowley J, Shaughnessy JD Jr. Tumor cell gene expression changes following short-term in vivo exposure to single agent chemotherapeutics are related to survival in multiple myeloma. Clin Cancer Res. 2008;14:4821–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Shaughnessy JD, Jr., Qu P, Usmani S, Heuck CJ, Zhang Q, Zhou Y, et al. Pharmacogenomics of bortezomib test-dosing identifies hyperexpression of proteasome genes, especially PSMD4, as novel high-risk feature in myeloma treated with total therapy 3. Blood 2011 (Epub 2011 May 31).

  70. Kumar SK, Jacobus SJ, Van Wier SA, Ahmann GJ, Henderson KJ, Callander NS, et al. Impact of gene expression profiling-based risk stratification in patients with myeloma receiving initial therapy with lenalidomide and dexamethasone. Blood. 2011 (Epub 2011 Aug 22).

  71. Hose D, Rème T, Hielscher T, Moreaux J, Messner T, Seckinger A, et al. Proliferation is a central independent prognostic factor and target for personalized and risk-adapted treatment in multiple myeloma. Haematologica. 2011;96(1):87–95.

    Article  PubMed  Google Scholar 

  72. Dickens N, Walker B, Leone P, Johnson D, Brito J, Zeisig A, et al. Homozygous deletion mapping in myeloma samples identifies genes and an expression signature relevant to pathogenesis and outcome. Clin Cancer Res. 2010;16:1856–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Fabris S, Agnelli L, Mattioli M, Baldini L, Ronchetti D, Morabito F, et al. Characterization of oncogene dysregulation in multiple myeloma by combined FISH and DNA microarray analyses. Genes Chromosomes Cancer. 2005;42:117–27.

    Article  CAS  PubMed  Google Scholar 

  74. Broyl A, Hose D, Lokhorst H, de Knegt Y, Peeters J, Jauch A, et al. Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients. Blood. 2010;116:2543–53.

    Article  CAS  PubMed  Google Scholar 

  75. Shaughnessy J, Jacobson J, Sawyer J, McCoy J, Fassas A, Zhan F, et al. Continuous absence of metaphase-defined cytogenetic abnormalities, especially of chromosome 13 and hypodiploidy, ensures long-term survival in multiple myeloma treated with Total Therapy I: interpretation in the context of global gene expression. Blood. 2003;101:3849–56.

    Article  CAS  PubMed  Google Scholar 

  76. Shaughnessy J. Amplification and overexpression of CKS1B at chromosome band 1q21 is associated with reduced levels of p27Kip1 and an aggressive clinical course in multiple myeloma. Hematology. 2005;10(Suppl 1):117–26.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by the Lebow Fund to Cure Myeloma.

Author information

Authors and Affiliations

  1. Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, AR, USA

    Sarah K. Johnson

  2. Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, 4301 West Markham, Slot 776, Little Rock, AR, 72205, USA

    Christoph J. Heuck, Qing Zhang, Bart Barlogie & John D. Shaughnessy Jr.

  3. Signal Genetics LLC, 667 Madison Ave, New York, NY, 10065, USA

    Anthony P. Albino

  4. Cancer Research and Biostatistics, Seattle, WA, USA

    Pingping Qu

  5. Donna D and Donald M Lambert Laboratory for Myeloma Genetics, University of Arkansas for Medical Sciences, Little Rock, AR, USA

    John D. Shaughnessy Jr.

  6. Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA

    John D. Shaughnessy Jr.

Authors
  1. Sarah K. Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christoph J. Heuck
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anthony P. Albino
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pingping Qu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bart Barlogie
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. John D. Shaughnessy Jr.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to John D. Shaughnessy Jr..

About this article

Cite this article

Johnson, S.K., Heuck, C.J., Albino, A.P. et al. The use of molecular-based risk stratification and pharmacogenomics for outcome prediction and personalized therapeutic management of multiple myeloma. Int J Hematol 94, 321–333 (2011). https://doi.org/10.1007/s12185-011-0948-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12185-011-0948-y

Keywords

Search

Navigation