Plasma Cell Neoplasms Tables: Recurrent Cytogenomic Alterations
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Table 1 - Recurrent Abnormalities of copy number aberration (CNAs) and copy-neutral loss-of-heterozygosity (cnLOH) in plasma cell myeloma (Literature Review). Summary table reviewing 65 papers applying FISH, CMA, NGS, and gene expression profiling for PCN diagnosis and prognosis. Table derived from Pugh et al., 2018 [PMID 30393007] with permission from Cancer Genetics.
| Chromosome | Region (whole chromosome or segmental, including cytobands) | Abnormality Type (gain, loss, LOH) | Relevant genes (if known) | Significance (Recurrent, Diagnostic, Prognostic, Targeted treatment) | Strength of Evidence (Level 1, 2, 3, see legend below table for criteria) | References PMID (year) |
| 1 | 1p32 | Loss | FAF1, CDKN2C | Poor prognostic marker | 1, 2 | [1] 24987674 (2014)[2], 25145975 (2015)[3] |
| 1p22.2-p22.1 | Loss | BARHL2, TGFBR3, and others; HSP90B3P, TGFER3, BRDT, EPHAX4, BTBD8 | Prognostic | 1, 3 | 24987674 (2014)[2] 25145975 (2015)[3] 26912802 (2016)[4] | |
| 1p21.3 | Loss | SNX7 | Recurrent | 2 | 24429703-(2014)[5] | |
| 1p13.2 | Loss | MAG13(kinase), BCL2 like and others | Recurrent | 3 | 24757046 (2014)[6] | |
| 1p12 | Loss | MAN1A2, FAM46C, GDAP2 | Recurrent | 2 | [1] 24987674 (2014)[2] | |
| 1p | cnLOH | Recurrent | 2 | 25145975 (2015)[3] | ||
| 1p | Loss | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8], 27588520 (2016)[9] | ||
| 1q21.2-q23 | Gain | CKS1B and ANP32E | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8], 27588520 (2016)[9] | |
| 1q | Gain | Poor prognostic marker | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | ||
| 2 | 2 | Gain | Recurrent | 2 | 22833442 (2012)[8] | |
| 2q | Loss | Recurrent | 3 | 23010713 (2012)[7] | ||
| 3 | 3 | Gain | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 3q21-23 | Gain | Recurrent | 2 | 25145975 (2015)[3] | ||
| 4 | 4p16.3 | Loss | FGFR3 and WHSC1 | Recurrent | 3 | 24987674 (2014)[2] |
| 4p15.2 | Loss | LGI2, SEPSECS, PI4K2B and others | Recurrent | 3 | 24987674 (2014)[2] | |
| 4q35.1 | Loss | DCTD, ING2, and others | Recurrent | 2 | 26912802 (2016)[4] | |
| 5 | 5 | Gain | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8], 27588520 (2016)[9] | |
| 5p | Gain | Recurrent | 3 | 24987674 (2014)[2] | ||
| 5p | Loss | Recurrent | 2 | 22833442 (2012)[8] | ||
| 5p14.3 | Gain | CDH12,10 | Recurrent | 3 | 24757046 (2014)[6] | |
| 5q | Gain | Recurrent | 2 | 24987674 (2014)[2] 25145975 (2015)[3] | ||
| 5q13.2 | Loss | OCLN, NAIP, and others | Recurrent | 2 | 26912802 (2016)[4] | |
| 6 | 6p | Gain | Recurrent | 2 | 25636340 (2015)[1], 24987674 (2014)[2], 22833442 (2012)[8] | |
| 6pter-p22.3 | Gain | Recurrent | 3 | 24987674 (2014)[2] | ||
| 6q | Loss | Poor prognostic marker | 2 | 25636340 (2015)[1], 24987674 (2014)[2], 25145975 (2015)[3], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | ||
| 6q11.1-q13 | Gain | MTRNR2L9 | Recurrent | 3 | 26912802 (2016)[4] | |
| 6q16.3 | Loss | COQR, GRIK2 | Recurrent | 3 | 24987674 (2014)[2] | |
| 6q25.3 | Loss | IGFR3 | Recurrent | 3 | 24757046 (2014)[6] | |
| 6q16.3 | Loss | COQR, GRIK2 | Recurrent | 3 | 24987674 (2014)[2] | |
| 7 | 7 | Gain | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 7p | Gain | Recurrent | 3 | 24987674 (2014)[2] | ||
| 7p15.2 | Gain | CBX3, etc | Recurrent | 3 | 26912802 (2016)[4] | |
| 7q | Gain | Recurrent | 2 | 24987674 (2014)[2], 25145975 (2015)[3] | ||
| 8 | 8p | Loss | Recurrent | 2 | 25636340 (2015)[1], 24987674 (2014)[2] 25145975 (2015)[3], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 8p23.1 | Loss | DEFB4 and others | Recurrent | 2 | 26912802 (2016)[4] | |
| 8p21.3/p21.2 | Loss | TNFRSF10B, DOCK5 and others | Recurrent | 3 | 24757046 (2014)[6] | |
| 8q | Gain | Recurrent | 3 | 24987674 (2014)[2] | ||
| 8q24.2 | Gain/amplification and Loss | MYC | Recurrent | 2 | 24987674 (2014)[2], 24757046 (2014)[6], 27588520 (2016)[9], 26338801 (2016)[10], 27811368-(2016)[11] | |
| 8q24.3 | Gain | MAPK15, TOP1MT, CYP11B11 (P450), ZNF41, 616, 707 and ZNF517 | Recurrent | 3 | 24757046 (2014)[6], 27811368-(2016)[11] | |
| 9 | 9 | Gain | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 9p | Gain | Recurrent | 2 | 24987674 (2014)[2], 25145975 (2015)[3] | ||
| 9q | Gain | Recurrent | 24987674 (2014)[2], 25145975 (2015)[3] | |||
| 9q34.3 | Gain | ZNF79, CDK9, SET | Recurrent | 3 | 24757046 (2014)[6] | |
| 10 | 10p | Loss | Recurrent | 3 | 24987674 (2014)[2] | |
| 10q | Loss | Recurrent | 3 | 24987674 (2014)[2] | ||
| 10q23.31 | Loss | PTEN | Recurrent | 2 | 16112193 (2006)[12] | |
| 11 | 11 | Gain | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 11p | Gain | Recurrent | 3 | 24987674 (2014)[2] | ||
| 11q | Gain | Recurrent | 2 | 25145975 (2015)[3], 23010713 (2012)[7] | ||
| 11q13.1/q13.4 | Gain | SCYL1, MAP3K11, CCND1, FGF4, FGF3, NUMA, and RELT | Recurrent | 3 | 24757046 (2014)[6] | |
| 11q22 | Loss | Recurrent | 3 | 24987674 (2014)[2] | ||
| 11q22.1-q22.3 | Homozygous Loss | BIRC3, BIRC2, MMP cluster | Recurrent | 3 | 24987674 (2014)[2], 22529291 (2012)[13] | |
| 12 | 12p | Loss | Recurrent | 2 | 25636340 (2015)[1], 24987674 (2014)[2], 24757046 (2014)[6], 22833442 (2012)[8] | |
| 12p | LOH | Recurrent | 2 | 25145975 (2015)[3], 22833442 (2012)[8] | ||
| 12p13.1 | Loss | CDKN1B, APOLD1 | Recurrent | 3 | 24987674 (2014)[2] | |
| 13 | 13q/13 | Loss | Poor prognostic marker | 1 | 25145975 (2015)[3] 24987674 (2014)[2], 22833442 (2012)[8], 23010713 (2012)[7], 24757046 (2014)[6], 27588520 (2016)[9], | |
| 13q14.11/q14.2 | Loss | TNFSF11, RB1, P2RY5, RCBTB2 | Poor prognostic marker | 1 | 24757046 (2014)[6], 24987674 (2014)[2], 25636340 (2015)[1] | |
| 13q32.2 | Loss | TGDS | Recurrent | 2 | 24429703-(2014)[5] | |
| 14 | 14q/14 | Loss | Better prognostic marker | 2 | 25636340 (2015)[1], 24987674 (2014)[2], 25145975 (2015)[3], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 14q/14 | Gain | Recurrent | 3 | 23010713 (2012)[7] | ||
| 14q | cnLOH | Recurrent | 2 | 25145975 (2015)[3], 22833442 (2012)[8] | ||
| 14q24.1-q24.3 | Loss | MLH3 | Recurrent | 2 | 26912802 (2016)[4] | |
| 14q32.32 | Homozygous Loss | RCOR1, TRAF3, AMN, CDC42BPB | Recurrent | 3 | 24987674 (2014)[2] | |
| 15 | 15 | Gain | Recurrent | 1 | 24987674 (2014)[2], 25145975 (2015)[3], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8], | |
| 15q24.1 | Gain | CYP11A1, ARID3B, CSK, etc. | Recurrent | 3 | 26912802 (2016)[4] | |
| 16 | 16p11.2 | Loss | TP53TG3 | Recurrent | 3 | 26912802 (2016)[4] |
| 16q | Loss | Recurrent | 1 | 25636340 (2015)[1], 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | ||
| 16q12.1-q12.2 | Homozygous Loss | CYLD, SALL1 | Recurrent | 3 | 24987674 (2014)[2] | |
| 16q24.3 | Loss | CBFA2T3 and others | Recurrent | 3 | 24757046 (2014)[6] | |
| 16 | cnLOH | Recurrent | 2 | 22833442 (2012)[8] | ||
| 17 | 17p/17 | Gain | Recurrent | 3, 3 | 24987674 (2014)[2], 23010713 (2012)[7] | |
| 17p | Loss | Predictive & prognostic | 1 | 24429703-(2014)[5], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | ||
| 17p13 | Loss | ATP1B2, TP53, WRAP5, EFNB3 | Predictive & prognostic | 1 | 24987674 (2014)[2], 27588520 (2016)[9] | |
| 17 | cnLOH | Recurrent | 2 | 22833442 (2012)[8] | ||
| 17q21.33 and 17qter | Gain | Recurrent | 3 | 24987674 (2014)[2] | ||
| 17q25 | Gain | Recurrent | 2 | 22833442 (2012)[8] | ||
| 18 | 18 | Gain | Recurrent | 2, 3 | 24987674 (2014)[2], 22833442 (2012)[8] | |
| 19 | 19 | Gain | Recurrent | 2 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 19p/ 19p13 | Gain | ICAM4,ICAM4, IBCL2L12, TYK2, IL2, and DNMT1 | Recurrent | 3 | 24987674 (2014)[2], 26912802 (2016)[4], 24757046 (2014)[6] | |
| 19q | Gain | Recurrent | 2 | 24987674 (2014)[2], 25145975 (2015)[3] | ||
| 20 | 20p | Loss | Recurrent | 2 | 24987674 (2014)[2], 22833442 (2012)[8] | |
| 20/20q | Gain | Recurrent | 2 | 24987674 (2014)[2], 22833442 (2012)[8] | ||
| 20/20q | Loss | Recurrent | 3 | 24987674 (2014)[2], 23010713 (2012)[7] | ||
| 21 | 21 | Gain | Recurrent | 1 | 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 22 | 22 | Loss | Recurrent | 2 | 25636340 (2015)[1], 24987674 (2014)[2], 24757046 (2014)[6], 23010713 (2012)[7], 22833442 (2012)[8] | |
| 22q21 | mostly Gain | PRAME | Recurrent, Associated with relapse | 2 | 27811368-(2016)[11] | |
| X | X | Gain/ Loss | Recurrent | 2 | 25145975 (2015)[3], 22833442 (2012)[8] | |
| X | LOH | Recurrent | 2 | 25145975 (2015)[3] | ||
| Xp | Loss | Recurrent | 3 | 24987674 (2014)[2] | ||
| Xp22.33 | Loss | SHOX, CRLF2, IL3RA | Recurrent | 3 | 26912802 (2016)[4] | |
| Xq | Gain (in males) | Poor prognostic marker | 2 | 25636340 (2015)[1], 24987674 (2014)[2] | ||
| Xq | Loss | Recurrent | 3 | 24987674 (2014)[2] | ||
| Xq21.31-q21.32 | Loss | PABPC5, PCDHX | Recurrent | 3 | 26912802 (2016)[4] | |
| Xq27.3-q28 | Gain | AFF2, MTMR1, etc | Recurrent | 3 | 26912802 (2016)[4] | |
| Y | Y | Loss | 2 | 25636340 (2015)[1] | ||
| Genome wide load of CNA > 100Mb | gain/loss | associated with significant change in GEP at relapse | 2 | 27811368-(2016)[11] |
cnLOH = copy neutral LOH, LOH = Loss of Heterozygosity, GEP = Gene Expression Profile
Level of evidence:
Level 1: well established evidence (in NCCN guideline, WHO criteria, FDA-approved, COG recommendation, or based on large body of publications)
Level 2: emerging evidence (by one large study or multiple case reports)
Level 3: presumptive evidence (multiple case reports or expert opinion)
Reference
- ↑ 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 B, Hebraud; et al. (2015). "Role of additional chromosomal changes in the prognostic value of t(4;14) and del(17p) in multiple myeloma: the IFM experience". doi:10.1182/blood-2014-07-587964. PMC 4375107. PMID 25636340.CS1 maint: PMC format (link)
- ↑ 2.00 2.01 2.02 2.03 2.04 2.05 2.06 2.07 2.08 2.09 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17 2.18 2.19 2.20 2.21 2.22 2.23 2.24 2.25 2.26 2.27 2.28 2.29 2.30 2.31 2.32 2.33 2.34 2.35 2.36 2.37 2.38 2.39 2.40 2.41 2.42 2.43 2.44 2.45 2.46 2.47 2.48 2.49 2.50 2.51 2.52 2.53 2.54 2.55 J, Smetana; et al. (2014). "Genome-wide screening of cytogenetic abnormalities in multiple myeloma patients using array-CGH technique: a Czech multicenter experience". doi:10.1155/2014/209670. PMC 4060785. PMID 24987674.CS1 maint: PMC format (link)
- ↑ 3.00 3.01 3.02 3.03 3.04 3.05 3.06 3.07 3.08 3.09 3.10 3.11 3.12 3.13 3.14 3.15 3.16 3.17 3.18 M, Kim; et al. (2015). "Copy number variations could predict the outcome of bortezomib plus melphalan and prednisone for initial treatment of multiple myeloma". PMID 25145975.
- ↑ 4.00 4.01 4.02 4.03 4.04 4.05 4.06 4.07 4.08 4.09 4.10 4.11 4.12 E, Kjeldsen (2016). "Identification of Prognostically Relevant Chromosomal Abnormalities in Routine Diagnostics of Multiple Myeloma Using Genomic Profiling". PMID 26912802.
- ↑ 5.0 5.1 5.2 N, Bolli; et al. (2014). "Heterogeneity of genomic evolution and mutational profiles in multiple myeloma". doi:10.1038/ncomms3997. PMC 3905727. PMID 24429703.CS1 maint: PMC format (link)
- ↑ 6.00 6.01 6.02 6.03 6.04 6.05 6.06 6.07 6.08 6.09 6.10 6.11 6.12 6.13 6.14 6.15 6.16 6.17 6.18 6.19 6.20 6.21 6.22 6.23 6.24 6.25 6.26 6.27 6.28 6.29 T, Boneva; et al. (2014). "Can genome array screening replace FISH as a front-line test in multiple myeloma?". PMID 24757046.
- ↑ 7.00 7.01 7.02 7.03 7.04 7.05 7.06 7.07 7.08 7.09 7.10 7.11 7.12 7.13 7.14 7.15 7.16 7.17 7.18 7.19 7.20 7.21 7.22 Bk, Zehentner; et al. (2012). "Array-based karyotyping in plasma cell neoplasia after plasma cell enrichment increases detection of genomic aberrations". PMID 23010713.
- ↑ 8.00 8.01 8.02 8.03 8.04 8.05 8.06 8.07 8.08 8.09 8.10 8.11 8.12 8.13 8.14 8.15 8.16 8.17 8.18 8.19 8.20 8.21 8.22 8.23 8.24 8.25 8.26 8.27 8.28 8.29 8.30 M, Stevens-Kroef; et al. (2012). "High detection rate of clinically relevant genomic abnormalities in plasma cells enriched from patients with multiple myeloma". PMID 22833442.
- ↑ 9.0 9.1 9.2 9.3 9.4 9.5 N, Bolli; et al. (2016). "A DNA target-enrichment approach to detect mutations, copy number changes and immunoglobulin translocations in multiple myeloma". doi:10.1038/bcj.2016.72. PMC 5056967. PMID 27588520.CS1 maint: PMC format (link)
- ↑ K, Rack; et al. (2016). "Genomic profiling of myeloma: the best approach, a comparison of cytogenetics, FISH and array-CGH of 112 myeloma cases". PMID 26338801.
- ↑ 11.0 11.1 11.2 11.3 P, Krzeminski; et al. (2016). "Integrative analysis of DNA copy number, DNA methylation and gene expression in multiple myeloma reveals alterations related to relapse". doi:10.18632/oncotarget.13025. PMC 5348347. PMID 27811368.CS1 maint: PMC format (link)
- ↑ H, Chang; et al. (2006). "Analysis of PTEN deletions and mutations in multiple myeloma". PMID 16112193.
- ↑ Jb, Egan; et al. (2012). "Whole-genome sequencing of multiple myeloma from diagnosis to plasma cell leukemia reveals genomic initiating events, evolution, and clonal tides". doi:10.1182/blood-2012-01-405977. PMC 3412329. PMID 22529291.CS1 maint: PMC format (link)