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5 - The genetic and epigenetic mechanisms underlying the behavior of myeloma

from Section 2 - Biological basis for targeted therapies in myeloma

Published online by Cambridge University Press:  18 December 2013

By
Martin F. Kaiser ,
Kevin D. Boyd  and
Gareth J. Morgan
Edited by
Stephen A. Schey ,
Kwee L. Yong ,
Robert Marcus  and
Kenneth C. Anderson
Stephen A. Schey
Affiliation:
Department of Haematology, King’s College Hospital, London
Kwee L. Yong
Affiliation:
Department of Haematology, University College Hospital, London
Robert Marcus
Affiliation:
Department of Haematology, King’s College Hospital, London
Kenneth C. Anderson
Affiliation:
Dana-Farber Cancer Institute, Boston
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Summary

Background

Multiple myeloma is characterized by a clonal expansion of terminally differentiated plasma cells that reside at multiple sites in the bone marrow where they interact with different cell types of the bone marrow micro-environment. The clinical picture is heterogeneous and many of the past and present research efforts have aimed at identifying the underlying factors for this diversity. Furthermore, clinical outcome differs dramatically with a median overall survival (OS) of less than two years for a group of ultra-high risk patients in contrast to patients that achieve durable remissions for many years. Novel treatment approaches have significantly improved survival and intensively treated patients now have an overall median survival between five and nine years[1]. However, myeloma still remains an incurable disease with frequent relapses and development of drug resistance occurring in virtually every patient.

Despite the heterogeneity in disease biology, treatment decisions today are made on the basis of age and performance status rather than individual features of the disease. Understanding the genetics and epigenetics of myeloma should enable us to develop specific therapeutic strategies for individual patients but to achieve this will require the development of robust prognostic and therapeutic biomarkers to identify patient subgroups for study in well-designed clinical trials.

Type
Chapter
Information
Myeloma
Pathology, Diagnosis, and Treatment
 , pp. 48 - 63
Publisher: Cambridge University Press
Print publication year: 2013

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References

Barlogie, B., Attal, M., Crowley, J. et al. Long-term follow-up of autotransplantation trials for multiple myeloma: update of protocols conducted by the intergroupe francophone du myelome, southwest oncology group, and university of arkansas for medical sciences. J. Clin. Oncol. 2010;28:1209–14.CrossRefGoogle Scholar
Kyle, R. A., Rajkumar, S. V., Larson, D. R. et al. Prevalence of monocloncal gammopathy of undetermined significance. New Engl. J. Med. 2006;354:1362–9.CrossRefGoogle Scholar
Fonseca, R., Bergsagel, P. L., Drach, J. et al. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia 2009;23:2210–21.CrossRefGoogle Scholar
Debes-Marun, C. S., Dewald, G. W., Bryant, S. et al. Chromosome abnormalities clustering and its implications for pathogenesis and prognosis in myeloma. Leukemia 2003;17:427–36.CrossRefGoogle Scholar
Ross, F. M., Ibrahim, A. H., Vilain-Holmes, A. et al. Age has a profound effect on the incidence and significance of chromosome abnormalities in myeloma. Leukemia 2005;19:1634–42.CrossRefGoogle Scholar
Boyd, K. D., Ross, F. M., Chiecchio, L. et al. Gender disparities in the tumor genetics and clinical outcome of multiple myeloma. Cancer Epidemiol Biomarkers Prev. 2011;20:1703–7.CrossRefGoogle ScholarPubMed
Walker, B. A., Leone, P. E., Chiecchio, L. et al. A compendium of myeloma-associated chromosomal copy number abnormalities and their prognostic value. Blood 2010;116:e56–65.CrossRefGoogle ScholarPubMed
Fonseca, R., Debes-Marun, C. S., Picken, E. B. et al. The recurrent IgH translocations are highly associated with nonhyperdiploid variant multiple myeloma. Blood 2003;102:2562–7.CrossRefGoogle ScholarPubMed
Avet-Loiseau, H., Li, J. Y., Facon, T. et al. High incidence of translocations t(11;14)(q13;q32) and t(4;14)(p16;q32) in patients with plasma cell malignancies. Cancer Res. 1998;58:5640–5.Google Scholar
Gonzalez, D., van der Burg, M., Garcia-Sanz, R. et al. Immunoglobulin gene rearrangements and the pathogenesis of multiple myeloma. Blood 2007;110:3112–21.CrossRefGoogle ScholarPubMed
Chesi, M., Nardini, E., Lim, R. S. et al. 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.Google Scholar
Onwuazor, O. N., Wen, X. Y., Wang, D. Y. et al. Mutation, SNP, and isoform analysis of fibroblast growth factor receptor 3 (FGFR3) in 150 newly diagnosed multiple myeloma patients. Blood 2003;102:772–3.CrossRefGoogle ScholarPubMed
Chen, J., Lee, B. H., Williams, I. R. et al. FGFR3 as a therapeutic target of the small molecule inhibitor PKC412 in hematopoietic malignancies. Oncogene 2005;24:8259–67.CrossRefGoogle ScholarPubMed
Keats, J. J., Reiman, T., Maxwell, C. A. et al. In multiple myeloma, t(4;14)(p16;q32) is an adverse prognostic factor irrespective of FGFR3 expression. Blood 2003;101:1520–9.CrossRefGoogle Scholar
Fonseca, R., Griepp, P. R.The t(4;14)(p16.3;q32) is strongly associated with chromosome 13 abnormalities in both multiple myeloma and monocloncal gammopathy of undetermined significance. Blood. 2001;98:1271–2.CrossRefGoogle Scholar
Fonseca, R., Blood, E. A., Oken, M. M. et al. Myeloma and the t(11;14)(q13;q32); evidence for a biologically defined unique subset of patients. Blood 2002;99:3735–41.CrossRefGoogle Scholar
Garand, R., Avet-Loiseau, H., Accard, F. et al. t(11;14) and t(4;14) translocations correlated with mature lymphoplasmacytoid and immature morphology, respectively, in multiple myeloma. Leukemia 2003;17:2032–5.CrossRefGoogle Scholar
Chesi, M., Bergsagel, P. L., Shonukan, O. O. et al. Frequent dysregulation of the c-maf proto-oncogene at 16q23 by translocation to an Ig locus in multiple myeloma. Blood 1998;91:4457–63.Google Scholar
Hurt, E. M., Wiestner, A., Rosenwald, A. 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.CrossRefGoogle ScholarPubMed
Boersma-Vreugdenhil, G. R., Kuipers, J., Van Straler, E. et al. The recurrent translocation t(14;20)9q32;q12) in multiple myeloma results in aberrant expression of MAFB: a molecular and genetic analysis of the chromosomal breakpoint. Br. J. Haematol. 2004;126:355–63.CrossRefGoogle Scholar
van Stralen, E., van de Wetering, M., Agnelli, L. et al. Identification of primary MAFB target genes in multiple myeloma. Exp. Hematol. 2009;37:78–86.CrossRefGoogle ScholarPubMed
Dib, A., Gabrea, A., Glebov, O. K., Bergsagel, P. L., Kuehl, W. M. Characterization of MYC translocations in multiple myeloma cell lines. J. Natl Cancer Inst. Monogr. 2008:25–31.
Avet-Loiseau, H., Gerson, F., Magrangeas, F. et al. Rearrangements of the c-myc oncogene are present in 15% of primary human multiple myeloma tumors. Blood 2001;98:3082–6.CrossRefGoogle ScholarPubMed
Chng, W. J., Gertz, M. A., Chung, T. H. et al. Correlation between array-comparative genomic hybridization-defined genomic gains and losses and survival: identification of 1p31–32 deletion as a prognostic factor in myeloma. Leukemia 2010;24:833–42.CrossRefGoogle Scholar
Kim, H. J., Song, E. J., Lee, Y. S., Kim, E., Lee, K. J.Human Fas-associated factor 1 interacts with heat shock protein 70 and negatively regulates chaperone activity. J. Biol. Chem. 2005;280:8125–33.CrossRefGoogle ScholarPubMed
Park, M. Y., Moon, J. H., Lee, K. S. et al. FAF1 suppresses IkappaB kinase (IKK) activation by disrupting the IKK complex assembly. J. Biol. Chem. 2007;282:27 572–7.CrossRefGoogle ScholarPubMed
Shaughnessy, J. D., Zhan, F., Burington, B. E. 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.CrossRefGoogle ScholarPubMed
Avet-Loiseau, H., Li, C., Magrangeas, F. et al. Prognostic significance of copy-number alterations in multiple myeloma. J. Clin. Oncol. 2009; 27:4585.CrossRefGoogle ScholarPubMed
Tapper, W., Chiecchio, L., Dagrada, G. P. et al. Heterogeneity in the prognostic significance of 12p deletion and chromosome 5 amplification in multiple myeloma. J. Clin. Oncol. 2011;29:e37–9; author reply e40–1.CrossRefGoogle ScholarPubMed
Avet-Loiseau, H., Leleu, X., Roussel, M. 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.CrossRefGoogle Scholar
Boyd, K. D., Ross, F. M., Tapper, W. J. et al. The clinical impact and molecular biology of del(17p) in multiple myeloma treated with conventional or Thalidomide-based therapy. Genes Chromosomes Cancer 2011;50:765–74.CrossRefGoogle ScholarPubMed
Jenner, M. W., Leone, P. E., Walker, B. A. et al. Gene mapping and expression analysis of 16q loss of heterozygosity identifies WWOX and CYLD as being important in determining clinical outcome in multiple myeloma. Blood 2007;110:3291–300.CrossRefGoogle ScholarPubMed
Qin, H. R., Iliopoulos, D., Semba, S. et al. A role for the WWOX gene in prostate cancer. Cancer Res. 2006;66:6477–81.CrossRefGoogle ScholarPubMed
Kovalenko, A., Chable-Bessia, C., Cantarella, G. et al. The tumour suppressor CYLD negatively regulates NF-kappaB signalling by deubiquitination. Nature 2003;424:801–5.CrossRefGoogle ScholarPubMed
Chapman, M. A., Lawrence, M. S., Keats, J. J. et al. Initial genome sequencing and analysis of multiple myeloma. Nature 2011;471:467–72.CrossRefGoogle ScholarPubMed
Walker, B. A., Wardell, C. P., Melchor, L. 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.CrossRefGoogle Scholar
Ashworth, A., Lord, C. J., Reis-Filho, J. S.Genetic interactions in cancer progression and treatment. Cell 2011;145:30–8.CrossRefGoogle ScholarPubMed
Chng, W. J., Gonzalez-Paz, N., Price-Troska, T. et al. Clinical and biological significance of RAS mutations in multiple myeloma. Leukemia 2008;22:2280–4.CrossRefGoogle ScholarPubMed
Chapman, P. B., Hauschild, A., Robert, C. et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N. Engl. J. Med. 2011;364:2507–16.CrossRefGoogle ScholarPubMed
Chng, W. J., Price-Troska, T., Gonzalez-Paz, N. et al. Clinical significance of TP53 mutation in myeloma. Leukemia 2007;21:582–4.CrossRefGoogle Scholar
Lode, L., Eveillard, M., Trichet, V. et al. Mutations in TP53 are exclusively associated with del(17p) in multiple myeloma. Haematologica 2010;95:1973–6.CrossRefGoogle Scholar
Annunziata, C. M., Davis, R. E., Demchenko, Y. et al. Frequent engagement of the classical and alternative NF-kappaB pathways by diverse genetic abnormalities in multiple myeloma. Cancer Cell 2007;12:115–30.CrossRefGoogle ScholarPubMed
Keats, J. J., Fonseca, R., Chesi, M. et al. Promiscuous mutations activate the noncanonical NF-kappaB pathway in multiple myeloma. Cancer Cell 2007;12:131–44.CrossRefGoogle ScholarPubMed
Rajan, N., Elliott, R., Clewes, O. et al. Dysregulated TRK signalling is a therapeutic target in CYLD defective tumours. Oncogene 2011;30:4243–60.CrossRefGoogle ScholarPubMed
Bergsagel, P. L., Kuehl, W. M., Zhan, F. et al. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood 2005;106:296–303.CrossRefGoogle ScholarPubMed
Brito, J. L., Walker, B., Jenner, M. et al. MMSET deregulation affects cell cycle progression and adhesion regulons in t(4;14) myeloma plasma cells. Haematologica 2009;94:78–86.CrossRefGoogle Scholar
Kaiser, M. F., Walker, B. A., Hockley, S. L. et al. A TC classification based predictor for multiple myeloma using multiplexed real-time quantitative PCR. Leukemia 2013. (In the press.)
Zhou, Y., Zhang, Q., Stephens, O. et al. Prediction of cytogenetic abnormalities with gene expression profiles. Blood 2012;119:e148–50.CrossRefGoogle ScholarPubMed
Decaux, O., Lode, L., Magrangeas, F. 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.CrossRefGoogle ScholarPubMed
Dickens, N. J., Walker, B. A., Leone, P. E. 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.CrossRefGoogle ScholarPubMed
Kuiper, R., Broyl, A., de Knegt, Y. et al. A gene expression signature for high-risk multiple myeloma. Leukemia 2012;26:2406–13.CrossRefGoogle ScholarPubMed
Pichiorri, F., Suh, S. S., Ladetto, M. et al. MicroRNAs regulate critical genes associated with multiple myeloma pathogenesis. Proc. Natl Acad. Sci. USA 2008;105:12;885–90.CrossRefGoogle ScholarPubMed
Chesi, M., Robbiani, D. F., Sebag, M. et al. AID-dependent activation of a MYC transgene induces multiple myeloma in a conditional mouse model of post-germinal center malignancies. Cancer Cell 2008;13:167–80.CrossRefGoogle Scholar
Rio-Machin, A., Ferreira, B. I., Henry, T. et al. Downregulation of specific miRNAs in hyperdiploid multiple myeloma mimics the oncogenic effect of IgH translocations occurring in the non-hyperdiploid subtype. Leukemia 2012; 27(4):925–31.CrossRefGoogle ScholarPubMed
Gutierrez, N. C., Sarasquete, M. E., Misiewicz-Krzeminska, I. et al. Deregulation of microRNA expression in the different genetic subtypes of multiple myeloma and correlation with gene expression profiling. Leukemia 2010;24:629–37.CrossRefGoogle ScholarPubMed
Pichiorri, F., Suh, S. S., Rocci, A. et al. Downregulation of p53-inducible microRNAs 192, 194, and 215 impairs the p53/MDM2 autoregulatory loop in multiple myeloma development. Cancer Cell 2010;18:367–81.CrossRefGoogle ScholarPubMed
Zhou, Y., Chen, L., Barlogie, B. et al. High-risk myeloma is associated with global elevation of miRNAs and overexpression of EIF2C2/AGO2. Proc. Natl Acad. Sci. USA 2010;107:7904–9.CrossRefGoogle ScholarPubMed
Kalari, S., Pfeifer, G. P.Identification of driver and passenger DNA methylation in cancer by epigenomic analysis. Adv. Genet. 2010;70:277–308.Google ScholarPubMed
Kovacs, J. J., Murphy, P. J., Gaillard, S. et al. HDAC6 regulates Hsp90 acetylation and chaperone-dependent activation of glucocorticoid receptor. Mol. Cell 2005;18:601–7.CrossRefGoogle ScholarPubMed
Marks, P., Rifkind, R. A., Richon, V. M. et al. Histone deacetylases and cancer: causes and therapies. Nat. Rev. Cancer 2001;1:194–202.CrossRefGoogle ScholarPubMed
Smith, E. M., Boyd, K., Davies, F. E.The potential role of epigenetic therapy in multiple myeloma. Br J Haematol. 2010;148:702–13.CrossRefGoogle ScholarPubMed
Choudhary, C., Kumar, C., Gnad, F. et al. Lysine acetylation targets protein complexes and co-regulates major cellular functions. Science (New York, NY) 2009;325:834–40.Google Scholar
Namdar, M., Perez, G., Ngo, L., Marks, P. A.Selective inhibition of histone deacetylase 6 (HDAC6) induces DNA damage and sensitizes transformed cells to anticancer agents. Proc. Natl Acad. Sci. USA 2010;107:20 003–8.CrossRefGoogle ScholarPubMed
Croonquist, P. A., Van Ness, B.The polycomb group protein enhancer of zeste homolog 2 (EZH 2) is an oncogene that influences myeloma cell growth and the mutant ras phenotype. Oncogene 2005;24:6269–80.CrossRefGoogle ScholarPubMed
Kalushkova, A., Fryknas, M., Lemaire, M. et al. Polycomb target genes are silenced in multiple myeloma. PLoS One 2010;5:e11 483.CrossRefGoogle ScholarPubMed
Wang, J. K., Tsai, M. C., Poulin, G. et al. The histone demethylase UTX enables RB-dependent cell fate control. Genes Dev. 2010;24:327–32.CrossRefGoogle ScholarPubMed
Herz, H. M., Madden, L. D., Chen, Z. et al. The H3K27me3 demethylase dUTX is a suppressor of Notch- and Rb-dependent tumors in Drosophila. Mol. Cell Biol. 2010;30:2485–97.CrossRefGoogle ScholarPubMed
Keats, J. J., Maxwell, C. A., Taylor, B. J. et al. Overexpression of transcripts originating from the MMSET locus characterizes all t(4;14)(p16;q32)-positive multiple myeloma patients. Blood 2005;105:4060–9.CrossRefGoogle Scholar
Pei, H., Zhang, L., Luo, K. et al. MMSET regulates histone H4K20 methylation and 53BP1 accumulation at DNA damage sites. Nature 2011;470:124–8.CrossRefGoogle ScholarPubMed
Lauring, J., Abukhdeir, A. M., Konishi, H. et al. The multiple myeloma associated MMSET gene contributes to cellular adhesion, clonogenic growth, and tumorigenicity. Blood 2008;111:856–64.CrossRefGoogle ScholarPubMed
Martinez-Garcia, E., Popovic, R., Min, D. J. et al. The MMSET histone methyl transferase switches global histone methylation and alters gene expression in t(4;14) multiple myeloma cells. Blood 2011;117:211–20.CrossRefGoogle Scholar
Kim, J. Y., Kee, H. J., Choe, N. W. et al. Multiple-myeloma-related WHSC1/MMSET isoform RE-IIBP is a histone methyltransferase with transcriptional repression activity. Mol. Cell Biol. 2008;28:2023–34.CrossRefGoogle ScholarPubMed
Todoerti, K., Ronchetti, D., Agnelli, L. et al. Transcription repression activity is associated with the type I isoform of the MMSET gene involved in t(4;14) in multiple myeloma. Br. J. Haematol. 2005;131:214–18.CrossRefGoogle Scholar
Walker, B. A., Wardell, C. P., Chiecchio, L. et al. Aberrant global methylation patterns affect the molecular pathogenesis and prognosis of multiple myeloma. Blood 2011;117:553–62.CrossRefGoogle ScholarPubMed
Ehrlich, M.DNA methylation in cancer: too much, but also too little. Oncogene 2002;21:5400–13.CrossRefGoogle ScholarPubMed
Sharma, A., Heuck, C. J., Fazzari, M. J. et al. DNA methylation alterations in multiple myeloma as a model for epigenetic changes in cancer. Wiley Interdiscip. Rev. Syst. Biol. Med. 2010;2:654–69.CrossRefGoogle Scholar
Bollati, V., Fabris, S., Pegoraro, V. et al. Differential repetitive DNA methylation in multiple myeloma molecular subgroups. Carcinogenesis 2009;30:1330–5.CrossRefGoogle ScholarPubMed
Boyd, K. D., Ross, F. M., Chiecchio, L. et al. A novel prognostic model in myeloma based on co-segregating adverse FISH lesions and the ISS: analysis of patients treated in the MRC Myeloma IX trial. Leukemia 2012;26:349–55.CrossRefGoogle ScholarPubMed

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