Niels Weinhold

Common variation at 3p22.1 and 7p15.3 influences multiple myeloma risk

To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 × 10−9) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 × 10−15). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 × 10−7). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights.

Common variation at 3q26.2, 6p21.33, 17p11.2 and 22q13.1 influences multiple myeloma risk

To identify variants for multiple myeloma risk, we conducted a genome-wide association study with validation in additional series totaling 4,692 individuals with multiple myeloma (cases) and 10,990 controls. We identified four risk loci at 3q26.2 (rs10936599, P = 8.70 × 10−14), 6p21.33 (rs2285803, PSORS1C2, P = 9.67 × 10−11), 17p11.2 (rs4273077, TNFRSF13B, P = 7.67 × 10−9) and 22q13.1 (rs877529, CBX7, P = 7.63 × 10−16). These data provide further evidence for genetic susceptibility to this B-cell hematological malignancy, as well as insight into the biological basis of predisposition.

The CCND1 c.870G>A polymorphism is a risk factor for t(11;14)(q13;q32) multiple myeloma

A number of specific chromosomal abnormalities define the subgroups of multiple myeloma. In a meta-analysis of two genome-wide association studies of multiple myeloma including a total of 1,661 affected individuals, we investigated risk for developing a specific tumor karyotype. The t(11;14)(q13;q32) translocation in which CCND1 is placed under the control of the immunoglobulin heavy chain enhancer was strongly associated with the CCND1 c.870G>A polymorphism (P = 7.96 × 10−11). These results provide a model in which a constitutive genetic factor is associated with risk of a specific chromosomal translocation.

Inherited genetic susceptibility to multiple myeloma

Although the familial clustering of multiple myeloma (MM) supports the role of inherited susceptibility, only recently has direct evidence for genetic predisposition been demonstrated. A meta-analysis of two genome-wide association (GWA) studies has identified single-nucleotide polymorphisms (SNPs) localising to a number of genomic regions that are robustly associated with MM risk. In this review, we provide an overview of the evidence supporting a genetic contribution to the predisposition to MM and MGUS (monoclonal gammopathy of unknown significance), and the insight this gives into the biological basis of disease aetiology. We also highlight the promise of future approaches to identify further specific risk factors and their potential clinical utility.

Genome-wide association study identifies multiple susceptibility loci for multiple myeloma

Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P=1.31 × 10−8), 6q21 (rs9372120, P=9.09 × 10−15), 7q36.1 (rs7781265, P=9.71 × 10−9), 8q24.21 (rs1948915, P=4.20 × 10−11), 9p21.3 (rs2811710, P=1.72 × 10−13), 10p12.1 (rs2790457, P=1.77 × 10−8), 16q23.1 (rs7193541, P=5.00 × 10−12) and 20q13.13 (rs6066835, P=1.36 × 10−13), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.

Clonal selection and double-hit events involving tumor suppressor genes underlie relapse in myeloma.

To elucidate the mechanisms underlying relapse from chemotherapy in multiple myeloma, we performed a longitudinal study of 33 patients entered into Total Therapy protocols investigating them using gene expression profiling, high-resolution copy number arrays, and whole-exome sequencing. The study illustrates the mechanistic importance of acquired mutations in known myeloma driver genes and the critical nature of biallelic inactivation events affecting tumor suppressor genes, especially TP53, the end result being resistance to apoptosis and increased proliferation rates, which drive relapse by Darwinian-type clonal evolution. The number of copy number aberration changes and biallelic inactivation of tumor suppressor genes was increased in GEP70 high risk, consistent with genomic instability being a key feature of high risk. In conclusion, the study highlights the impact of acquired genetic events, which enhance the evolutionary fitness level of myeloma-propagating cells to survive multiagent chemotherapy and to result in relapse.

Spatial genomic heterogeneity in multiple myeloma revealed by multi-region sequencing

In multiple myeloma malignant plasma cells expand within the bone marrow. Since this site is well-perfused, a rapid dissemination of “fitter” clones may be anticipated. However, an imbalanced distribution of multiple myeloma is frequently observed in medical imaging. Here, we perform multi-region sequencing, including iliac crest and radiology-guided focal lesion specimens from 51 patients to gain insight into the spatial clonal architecture. We demonstrate spatial genomic heterogeneity in more than 75% of patients, including inactivation of CDKN2C and TP53, and mutations affecting mitogen-activated protein kinase genes. We show that the extent of spatial heterogeneity is positively associated with the size of biopsied focal lesions consistent with regional outgrowth of advanced clones. The results support a model for multiple myeloma progression with clonal sweeps in the early phase and regional evolution in advanced disease. We suggest that multi-region investigations are critical to understanding intra-patient heterogeneity and the evolutionary processes in multiple myeloma.In multiple myeloma, malignant cells expand within bone marrow. Here, the authors use multi-region sequencing in patient samples to analyse spatial clonal architecture and heterogeneity, providing novel insight into multiple myeloma progression and evolution.

Clinical value of molecular subtyping multiple myeloma using gene expression profiling

Using a data set of 1217 patients with multiple myeloma enrolled in Total Therapies, we have examined the impact of novel therapies on molecular and risk subgroups and the clinical value of molecular classification. Bortezomib significantly improved the progression-free survival (PFS) and overall survival (OS) of the MMSET (MS) subgroup. Thalidomide and bortezomib positively impacted the PFS of low-risk (LoR) cases defined by the GEP70 signature, whereas high-risk (HiR) cases showed no significant changes in outcome. We show that molecular classification is important if response rates are to be used to predict outcomes. The t(11;14)-containing CD-1 and CD-2 subgroups showed clear differences in time to response and cumulative response rates but similar PFS and OS. Furthermore, complete remission was not significantly associated with the outcome of the MAF/MAFB (MF) subgroup or HiR cases. HiR cases were enriched in the MF, MS and proliferation subgroups, but the poor outcome of these groups was not linked to subgroup-specific characteristics such as MAF overexpression per se. It is especially important to define risk status if HiR cases are to be managed appropriately because of their aggressive clinical course, high rates of early relapse and the need to maintain therapeutic pressure on the clone.

Inherited genetic susceptibility to monoclonal gammopathy of unknown significance

Monoclonal gammopathy of undetermined significance (MGUS) is present in ∼2% of individuals age >50 years. The increased risk of multiple myeloma (MM) in relatives of individuals with MGUS is consistent with MGUS being a marker of inherited genetic susceptibility to MM. Common single-nucleotide polymorphisms (SNPs) at 2p23.3 (rs6746082), 3p22.1 (rs1052501), 3q26.2 (rs10936599), 6p21.33 (rs2285803), 7p15.3 (rs4487645), 17p11.2 (rs4273077), and 22q13.1 (rs877529) have recently been shown to influence MM risk. To examine the impact of these 7 SNPs on MGUS, we analyzed two case-control series totaling 492 cases and 7306 controls. Each SNP independently influenced MGUS risk with statistically significant associations (P < .02) for rs1052501, rs2285803, rs4487645, and rs4273077. SNP associations were independent, with risk increasing with a larger number of risk alleles carried (per allele odds ratio, 1.18; P < 10(-7)). Collectively these data are consistent with a polygenic model of disease susceptibility to MGUS.

Concomitant gain of 1q21 and MYC translocation define a poor prognostic subgroup of hyperdiploid multiple myeloma

The impact of MYC locus aberrations on the outcome of multiple myeloma (MM) patients is still a matter of debate. The aim of this study was to further investigate their influence on the survival of MM patients treated with high-dose chemotherapy. Our data suggest that the favorable prognosis factor