Genome-wide association study identifies variation at 6q25.1 associated with survival in multiple myeloma

Multiple myeloma

Multiple myeloma (MM) is a haematological lymphoid malignancy involving tumoural plasma cells and is usually characterized by the presence of a monoclonal immunoglobulin protein. MM is the second most common haematological malignancy, with an increasing global incidence. It remains incurable because most patients relapse or become refractory to treatments. MM is a genetically complex disease with high heterogeneity that develops as a multistep process, involving acquisition of genetic alterations in the tumour cells and changes in the bone marrow microenvironment. Symptomatic MM is diagnosed using the International Myeloma Working Group criteria as a bone marrow infiltration of ≥10% clonal plasma cells, and the presence of at least one myeloma-defining event, either standard CRAB features (hypercalcaemia, renal failure, anaemia and/or lytic bone lesions) or biomarkers of imminent organ damage. Younger and fit patients are considered eligible for transplant. They receive an induction, followed by consolidation with high-dose melphalan and autologous haematopoietic cell transplantation, and maintenance therapy. In older adults (ineligible for transplant), the combination of daratumumab, lenalidomide and dexamethasone is the preferred option. If relapse occurs and requires further therapy, the choice of therapy will be based on previous treatment and response and now includes immunotherapies, such as bi-specific monoclonal antibodies and chimeric antigen receptor T cell therapy.

CoNet: Efficient Network Regression for Survival Analysis in Transcriptome-Wide Association Studies—With Applications to Studies of Breast Cancer

Transcriptome-wide association studies (TWASs) aim to detect associations between genetically predicted gene expression and complex diseases or traits through integrating genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) mapping studies. Most current TWAS methods analyze one gene at a time, ignoring the correlations between multiple genes. Few of the existing TWAS methods focus on survival outcomes. Here, we propose a novel method, namely a COx proportional hazards model for NEtwork regression in TWAS (CoNet), that is applicable for identifying the association between one given network and the survival time. CoNet considers the general relationship among the predicted gene expression as edges of the network and quantifies it through pointwise mutual information (PMI), which is under a two-stage TWAS. Extensive simulation studies illustrate that CoNet can not only achieve type I error calibration control in testing both the node effect and edge effect, but it can also gain more power compared with currently available methods. In addition, it demonstrates superior performance in real data application, namely utilizing the breast cancer survival data of UK Biobank. CoNet effectively accounts for network structure and can simultaneously identify the potential effecting nodes and edges that are related to survival outcomes in TWAS.

Efficient and accurate frailty model approach for genome-wide survival association analysis in large-scale biobanks

With decades of electronic health records linked to genetic data, large biobanks provide unprecedented opportunities for systematically understanding the genetics of the natural history of complex diseases. Genome-wide survival association analysis can identify genetic variants associated with ages of onset, disease progression and lifespan. We propose an efficient and accurate frailty model approach for genome-wide survival association analysis of censored time-to-event (TTE) phenotypes by accounting for both population structure and relatedness. Our method utilizes state-of-the-art optimization strategies to reduce the computational cost. The saddlepoint approximation is used to allow for analysis of heavily censored phenotypes (>90%) and low frequency variants (down to minor allele count 20). We demonstrate the performance of our method through extensive simulation studies and analysis of five TTE phenotypes, including lifespan, with heavy censoring rates (90.9% to 99.8%) on ~400,000 UK Biobank participants with white British ancestry and ~180,000 individuals in FinnGen. We further analyzed 871 TTE phenotypes in the UK Biobank and presented the genome-wide scale phenome-wide association results with the PheWeb browser.

Functional dissection of inherited non-coding variation influencing multiple myeloma risk

Thousands of non-coding variants have been associated with increased risk of human diseases, yet the causal variants and their mechanisms-of-action remain obscure. In an integrative study combining massively parallel reporter assays (MPRA), expression analyses (eQTL, meQTL, PCHiC) and chromatin accessibility analyses in primary cells (caQTL), we investigate 1,039 variants associated with multiple myeloma (MM). We demonstrate that MM susceptibility is mediated by gene-regulatory changes in plasma cells and B-cells, and identify putative causal variants at six risk loci (SMARCD3, WAC, ELL2, CDCA7L, CEP120, and PREX1). Notably, three of these variants co-localize with significant plasma cell caQTLs, signaling the presence of causal activity at these precise genomic positions in an endogenous chromosomal context in vivo. Our results provide a systematic functional dissection of risk loci for a hematologic malignancy.

The Relationship of ABCB1/MDR1 and CYP1A1 Variants with the Risk of Disease Development and Shortening of Overall Survival in Patients with Multiple Myeloma

(1) Background: The aim of our study was to analyze the possible relationship of ABCB1 and CYP1A1 gene variants with susceptibility and outcome of multiple myeloma (MM); (2) Methods: Genomic DNA samples from 110 newly-diagnosed MM patients and 100 healthy blood donors were analyzed by methods-PCR-RFLP (for ABCB1 3435C > T, CYP1A1 6235T > C-m1), automated DNA sequencing (for ABCB1 1236C > T, 2677G > T/A) and allele-specific PCR (for CYP1A1 4889A > G-m2); (3) Results: The genotypic frequencies of CYP1A1 4889A > G variant were not in Hardy-Weinberg equilibrium for MM patients. The presence of m1 and m2 CYP1A1 alleles decreased the risk of MM-OR = 0.49 (p = 0.011) and OR = 0.27 (p = 0.0003), respectively. In turn, TT genotype (ABCB1 2677G > T/A) increased the risk of this disease (p = 0.007). In the multivariate Cox analysis CT + TT genotypes (ABCB1 3435C > T) were associated with decreased risk of death (HR = 0.29, p = 0.04). In log-rank test in patients with CT genotype (ABCB1 3435C > T) was observed association of overall survival with the type of treatment; (4) Conclusions: Our findings suggest that T-alleles of ABCB1 2677G > T/A and m1/m2 alleles of CYP1A1 affected the susceptibility of MM. Moreover, T-allele of ABCB1 3435C > T might be independent positive prognostic factor in MM.

Common gene variants within 3'-untranslated regions as modulators of multiple myeloma risk and survival

We evaluated the association between germline genetic variants located within the 3'-untranlsated region (polymorphic 3'UTR, ie, p3UTR) of candidate genes involved in multiple myeloma (MM). We performed a case-control study within the International Multiple Myeloma rESEarch (IMMEnSE) consortium, consisting of 3056 MM patients and 1960 controls recruited from eight countries. We selected p3UTR of six genes known to act in different pathways relevant in MM pathogenesis, namely KRAS (rs12587 and rs7973623), VEGFA (rs10434), SPP1 (rs1126772), IRF4 (rs12211228) and IL10 (rs3024496). We found that IL10-rs3024496 was associated with increased risk of developing MM and with a worse overall survival of MM patients. The variant allele was assayed in a vector expressing eGFP chimerized with the IL10 3'-UTR and it was found functionally active following transfection in human myeloma cells. In this experiment, the A-allele caused a lower expression of the reporter gene and this was also in agreement with the in vivo expression of mRNA measured in whole blood as reported in the GTEx portal. Overall, these data are suggestive of an effect of the IL10-rs3024496 SNP on the regulation of IL10 mRNA expression and it could have clinical implications for better characterization of MM patients in terms of prognosis.

Genetically determined telomere length and multiple myeloma risk and outcome

Telomeres are involved in processes like cellular growth, chromosomal stability, and proper segregation to daughter cells. Telomere length measured in leukocytes (LTL) has been investigated in different cancer types, including multiple myeloma (MM). However, LTL measurement is prone to heterogeneity due to sample handling and study design (retrospective vs. prospective). LTL is genetically determined; genome-wide association studies identified 11 SNPs that, combined in a score, can be used as a genetic instrument to measure LTL and evaluate its association with MM risk. This approach has been already successfully attempted in various cancer types but never in MM. We tested the "teloscore" in 2407 MM patients and 1741 controls from the International Multiple Myeloma rESEarch (IMMeNSE) consortium. We observed an increased risk for longer genetically determined telomere length (gdTL) (OR = 1.69; 95% CI 1.36-2.11; P = 2.97 × 10^-6 for highest vs. lowest quintile of the score). Furthermore, in a subset of 1376 MM patients we tested the relationship between the teloscore and MM patients survival, observing a better prognosis for longer gdTL compared with shorter gdTL (HR = 0.93; 95% CI 0.86-0.99; P = 0.049). In conclusion, we report convincing evidence that longer gdTL is a risk marker for MM risk, and that it is potentially involved in increasing MM survival.

Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients

Gene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype-tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10^-7 either in EBV-transformed B-lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression-free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4-rs1992292, TBRG4-rs2287535 and ENTPD1-rs2153913) showed associations with OS at P < .05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta-analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4-rs1992292 is associated with OS (hazard ratio = 1.14, 95% confidence interval 1.04-1.26, P = .007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.

Upregulation of ATIC in multiple myeloma tissues based on tissue microarray and gene microarrays

PURPOSE

Multiple myeloma (MM) is characterized by the malignant proliferation of plasma cells, which produce a monoclonal immunoglobulin protein. The role of 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase (ATIC) has not yet been well studied in the area of MM. Thus, in the current study, we sought to examine the expression levels, including mRNA and protein levels of ATIC in MM.

METHODS

Multiple myeloma microarray and RNA-seq data were screened from the SRA, GEO, ArrayExpress, and Oncomine databases. The mRNA level of ATIC was extracted from the high throughput data, and the prognostic value was studied. The protein level of ATIC was also detected by in-house immunohistochemistry on a tissue microarray. Potential signaling pathways were enriched with ATIC-related genes in MM.

RESULTS

Both the mRNA and protein levels of ATIC were significantly upregulated in MM samples as compared to normal samples. Furthermore, the summarized Standardized Mean Difference was 1.66 with 674 cases of MM based on 10 independent studies including the in-house tissue microarray. The overall hazard ratio of ATIC in MM was 1.7 with 1631 cases of MM based on five microarrays. In the KEGG pathway analysis, the ATIC-related genes were mainly enriched in the pathway of complement and coagulation cascades.

CONCLUSION

We provided the first evidence supporting the upregulation of ATIC may play an essential part in the tumorigenesis and development of MM. The promoting cancer capacity may be related to the pathway of complement and coagulation cascades.

Identification and Validation of a Biomarker Signature in Patients With Resectable Pancreatic Cancer via Genome-Wide Screening for Functional Genetic Variants

Importance

Surgery currently offers the only chance for a cure in pancreatic ductal adenocarcinoma (PDAC), but it carries a significant morbidity and mortality risk and results in varying oncologic outcomes. At present, to our knowledge, there are no tests available before surgical resection to identify tumors with an aggressive biological phenotype that could guide personalized treatment strategies.

Objective

Identification of noninvasive genetic biomarkers that could direct therapy in patients whose cases are amenable to pancreatic cancer resection.

Design, Setting, and Participants

This multicenter study combined a prospective European cohort of patients with PDAC who underwent pancreatic resection (from University Hospital of Zurich, Zurich, Switzerland; Cantonal Hospital of Winterthur, Winterthur, Switzerland; and University Clinic of Ulm, Ulm, Germany) with data from the Cancer Genome Atlas database in the United States, which includes prospectively registered patients with PDAC. A genome-wide screening for functional single-nucleotide polymorphisms (SNPs) that affect PDAC survival was conducted using the European cohort for identification and the Cancer Genome Atlas cohort for validation. We used Cox proportional hazards models to screen for high-frequency polymorphic variants that are associated with allelic differences in tumor-associated survival and either result in an altered protein structure and function or reside in known regulatory noncoding genomic regions. The false-discovery rate method was applied for multiple hypothesis-testing corrections. Data analysis occurred from November 2017 to May 2018.

Exposures

Pancreatic resection.

Main Outcomes and Measures

Tumor-associated survival.

Results

A total of 195 patients in the European cohort were included, as well as 136 patients in the Cancer Genome Atlas cohort (overall median [range] age, 66 [19-87] years; 156 [47.1%] were women, and 175 [52.9%] were men). Two SNPs in noncoding, functional regions of genes that regulate cancer progression, invasion, and metastasis were identified (CHI3L2 SNP rs684559 and CD44 SNP rs353630). These were associated with survival after PDAC resection; patients who carry the risk alleles at 1 of both SNP loci had a 2.63-fold increased risk for tumor-associated death compared with those with protective genotypes (hazard ratio for survival, 0.38 [95% CI, 0.27-0.53]; P = 1.0 × 10-8).

Conclusions and Relevance

The identified polymorphisms may serve as a noninvasive biomarker signature of prospective survival after pancreatic resection that is readily available at the time of PDAC diagnosis. This signature can be used to identify a subset of high-risk patients with PDAC with very low survival probability who might be eligible for inclusion in clinical trials of new therapeutic strategies, including neoadjuvant chemotherapy protocols. In addition, the biological knowledge about these SNPs could help guide the development of individualized genomic strategies for PDAC therapies.

Gene Co-expression Network and Copy Number Variation Analyses Identify Transcription Factors Associated With Multiple Myeloma Progression

Multiple myeloma (MM) has two clinical precursor stages of disease: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). However, the mechanism of progression is not well understood. Because gene co-expression network analysis is a well-known method for discovering new gene functions and regulatory relationships, we utilized this framework to conduct differential co-expression analysis to identify interesting transcription factors (TFs) in two publicly available datasets. We then used copy number variation (CNV) data from a third public dataset to validate these TFs. First, we identified co-expressed gene modules in two publicly available datasets each containing three conditions: normal, MGUS, and SMM. These modules were assessed for condition-specific gene expression, and then enrichment analysis was conducted on condition-specific modules to identify their biological function and upstream TFs. TFs were assessed for differential gene expression between normal and MM precursors, then validated with CNV analysis to identify candidate genes. Functional enrichment analysis reaffirmed known functional categories in MM pathology, the main one relating to immune function. Enrichment analysis revealed a handful of differentially expressed TFs between normal and either MGUS or SMM in gene expression and/or CNV. Overall, we identified four genes of interest (MAX, TCF4, ZNF148, and ZNF281) that aid in our understanding of MM initiation and progression.

Correlation of MicroRNA 17-92 Cluster Host Gene (MIR17HG) Polymorphisms With Susceptibility and Prognosis for Multiple Myeloma

PURPOSE

To explore the correlation of MIR17HG polymorphism with susceptibility and prognosis of multiple myeloma (MM).

PATIENTS AND METHODS

A total of 217 MM patients treated with high-dose melphalan combined with autologous peripheral blood stem-cell transplantation at our hospital were enrolled as the case group, and 220 healthy people were included as the control group. Sequenom MassARRAY iPLEX Gold single nucleotide polymorphism genotyping was used to detect polymorphisms of MIR17HG, including rs7336610, rs17735387, rs4284505, and rs1428.

RESULTS

An increased risk of MM was found in patients who carried the rs7336610 T allele and rs4284505 G allele, and the higher the Durie-Salmon and International Staging System stages were, the more MM patients carrying rs7336610 CT + TT genotype and rs4284505 AG + GG genotype (all P < .05). Haplotype AC (rs4284505-rs1428) and CA (rs7336610-rs4284505) evidently reduce MM risk, whereas haplotype GC (rs4284505-rs1428) significantly elevated MM risk (all P < .05). Kaplan-Meier curve analysis demonstrated that rs7336610 CC genotype carriers had higher 5-year survival rate than CT + TT genotype carriers (P = .034), and the AA genotype carriers of rs4284505 had higher 5-year survival rate than AG + GG genotype carriers (P < .001).

CONCLUSION

Polymorphisms of MIR17HG rs7336610 and rs1428 were correlated with MM risk and prognosis.

Genetic polymorphisms in genes of class switch recombination and multiple myeloma risk and survival: an IMMEnSE study

Genetic variants in genes acting during the maturation process of immature B-cell to differentiated plasma cell could influence the risk of developing multiple myeloma (MM). During B-cell maturation, several programmed genetic rearrangements occur to increase the variation of the immunoglobulin chains. Class switch recombination (CSR) is one of the most important among these mechanisms. Germline polymorphisms altering even subtly this process could play a role in the etiology and outcome of MM. We performed an association study of 30 genetic variants in the key CSR genes, using 2632 MM patients and 2848 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the Heidelberg MM Group and the ESTHER cohort. We found an association between LIG4-rs1555902 and decreased MM risk, which approached statistical significance, as well as significant associations between AICDA-rs3794318 and better outcome. Our results add to our knowledge on the genetic component of MM risk and survival.

LRP1B Polymorphisms Are Associated with Multiple Myeloma Risk in a Chinese Han Population

Multiple myeloma (MM) is an extremely complex plasma cell malignancy that is genetically heterogeneous. A recent Genome-wide association study (GWAS) indicated that variation at 2q22 (rs61070260) influences MM risk. This association has not been validated to date in a Chinese Han population. In this study, we evaluated the association between rs61070260 in LRP1B and MM risk in a Chinese Han population involving 739 MM patients and 592 healthy controls. Our results indicated that rs61070260 in LRP1B was significantly associated with MM susceptibility (P=3.937×10-37). Furthermore, the linkage disequilibrium (LD) analysis of rs61070260 revealed an LD block encompassing exons 26, 27 and 28 of the LRP1B gene, and a subsequent sequencing analysis identified three SNPs (rs762074421, rs756168629, rs113600691) in exons 26 and 28 of LRP1B. For the SNP rs756168629 in exon 26, a missense mutation which results in a transition from arginine to histidine at position 1661 of the LRP1B protein, has not been found in Chinese populations according to the Chinese Millionome Database and Genome Aggregation Database (EAS), and this mutation was predicted to be deleterious or damaging by SIFT and PolyPhen. These findings firmly establish the role of LRP1B in contributing to MM susceptibility. In addition, the identification of a rare coding mutation (p.R1661H) in LRP1B detected in MM individuals was suggested to be harmful to the encoded protein, which was characterized as a candidate tumour suppressor; thus, LRP1B is likely to be a disease-associated gene that is implicated in the development and progression of MM.

European Myeloma Network recommendations on tools for the diagnosis and monitoring of multiple myeloma: what to use and when

The diagnosis of multiple myeloma can be challenging, even for experienced physicians, and requires close collaboration between numerous disciplines (orthopedics, radiology, nuclear medicine, radiation therapy, hematology and oncology) before the final diagnosis of myeloma is made. The definition of multiple myeloma is based on the presence of clinical, biochemical, histopathological, and radiological markers of disease. Specific tests are needed both at presentation and during follow-up in order to reach the correct diagnosis and characterize the disease precisely. These tests can also serve prognostic purposes and are useful for follow-up of myeloma patients. Molecular analyses remain pivotal for defining high-risk myeloma and are used in updated patient stratifications, while minimal residual disease assessment via flow cytometry, molecular techniques and radiological approaches provides additional prognostic information on patients' long-term outcome. This pivotal information will guide our future treatment decisions in forthcoming clinical trials. The European Myeloma Network group updated their guidelines on different diagnostic recommendations, which should be of value to enable appropriate use of the recommendations both at diagnosis and during follow-up.

Inherited variation in the xenobiotic transporter pathway and survival of multiple myeloma patients

Over the past four decades, remarkable progress has been made in the treatment and prognosis of multiple myeloma (MM), although it remains an incurable disease. Chemotherapy resistance is a major hurdle for treatment efficacy. Drug resistance can be innate and so driven by genes involved in the drug metabolism pathways. We performed an association study of 71 germline variants within the major genes in those pathways (ABCB1, ABCC2, ABCG2, and their regulators NR1I2/PXR and NR1I3/CAR) in the International Multiple Myeloma rESEarch (IMMEnSE) consortium, consisting of 1365 MM cases with survival information recruited in 5 European countries. Two of the SNPs showed a significant association with the survival of MM patients, namely rs2235013, located in ABCB1 [Hazard ratio (HR) = 1·52, 95% confidence interval (CI) = 1·18-1·95, P = 0·00087], and rs4148388, located in ABCC2 (HR = 2·15, 95% CI = 1·44-3·22, P = 0·0001). ABCC2 plays an essential role in transporting various anticancer drugs, including several used against MM, out of the cell. In silico analyses predict that the variant alleles of four SNPs in linkage disequilibrium with ABCC2-rs4148388 are associated with increased gene expression. Overexpression of ABCC2 increases drug clearance and therefore may induce drug resistance mechanisms. In conclusion, we found a promising association between ABCC2-rs4148388 and MM outcome that is supported by a plausible biological explanation.

A common variant within the HNF1B gene is associated with overall survival of multiple myeloma patients: results from the IMMEnSE consortium and meta-analysis

Diabetogenic single nucleotide polymorphisms (SNPs) have recently been associated with multiple myeloma (MM) risk but their impact on overall survival (OS) of MM patients has not been analysed yet. In order to investigate the impact of 58 GWAS-identified variants for type 2 diabetes (T2D) on OS of patients with MM, we analysed genotyping data of 936 MM patients collected by the International Multiple Myeloma rESEarch (IMMENSE) consortium and an independent set of 700 MM patients recruited by the University Clinic of Heidelberg. A meta-analysis of the cox regression results of the two sets showed that rs7501939 located in the HNF1B gene negatively impacted OS (HRRec= 1.44, 95% CI = 1.18-1.76, P = 0.0001). The meta-analysis also showed a noteworthy gender-specific association of the SLC30A8rs13266634 SNP with OS. The presence of each additional copy of the minor allele at rs13266634 was associated with poor OS in men whereas no association was seen in women (HRMen-Add = 1.32, 95% CI 1.13-1.54, P = 0.0003). In conclusion, these data suggest that the HNF1Brs7501939 SNP confers poor OS in patients with MM and that a SNP in SLC30A8 affect OS in men.

Constitutional mutation in CDKN2A is associated with long term survivorship in multiple myeloma: a case report

Background

Multiple Myeloma is a cancer of plasma cells associated with significantly reduced survival. Long term survivorship from myeloma is very rare and despite advances in its treatment the disease is generally considered incurable. We report a patient diagnosed with myeloma carrying a germline mutation of a tumour suppressor gene who has effectively been cured.

Case presentation

A 36-year-old woman was diagnosed with IgG lambda myeloma in 1985. She was treated with melphalan chemotherapy followed by high-dose melphalan and autologous stem cell rescue and since remained in complete remission despite not having received any additional therapy. After eliciting a prior history of multiple primary melanomas and breast cancer, she was tested for and shown to be a carrier for a germline mutation in CDKN2A.

Conclusions

This is the second case report of germline mutation of CDKN2A being associated with myeloma. CDKN2A is a stabiliser of p53. Long term survivorship after high dose DNA damaging chemotherapy with melphalan in this patient is compatible with an increased chemo-sensitivity due to impairment of the DNA repair pathway.

Genome-wide association studies of cancer: current insights and future perspectives

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS.

Evolutionary biology of high-risk multiple myeloma

The outcomes for the majority of patients with myeloma have improved over recent decades, driven by treatment advances. However, there is a subset of patients considered to have high-risk disease who have not benefited. Understanding how high-risk disease evolves from more therapeutically tractable stages is crucial if we are to improve outcomes. This can be accomplished by identifying the genetic mechanisms and mutations driving the transition of a normal plasma cell to one with the features of the following disease stages: monoclonal gammopathy of undetermined significance, smouldering myeloma, myeloma and plasma cell leukaemia. Although myeloma initiating events are clonal, subsequent driver lesions often occur in a subclone of cells, facilitating progression by Darwinian selection processes. Understanding the co-evolution of the clones within their microenvironment will be crucial for therapeutically manipulating the process. The end stage of progression is the generation of a state associated with treatment resistance, increased proliferation, evasion of apoptosis and an ability to grow independently of the bone marrow microenvironment. In this Review, we discuss these end-stage high-risk disease states and how new information is improving our understanding of their evolutionary trajectories, how they may be diagnosed and the biological behaviour that must be addressed if they are to be treated effectively.

Multiple myeloma

Multiple myeloma is a malignancy of terminally differentiated plasma cells, and patients typically present with bone marrow infiltration of clonal plasma cells and monoclonal protein in the serum and/or urine. The diagnosis of multiple myeloma is made when clear end-organ damage attributable to the plasma cell proliferative disorder or when findings that suggest a high likelihood of their development are present. Distinguishing symptomatic multiple myeloma that requires treatment from the precursor stages of monoclonal gammopathy of undetermined significance and smouldering multiple myeloma is important, as observation is the standard for those conditions. Much progress has been made over the past decade in the understanding of disease biology and individualized treatment approaches. Several new classes of drugs, such as proteasome inhibitors and immunomodulatory drugs, have joined the traditional armamentarium (corticosteroids, alkylating agents and anthracyclines) and, along with high-dose therapy and autologous haemopoietic stem cell transplantation, have led to deeper and durable clinical responses. Indeed, an increasing proportion of patients are achieving lasting remissions, raising the possibility of cure for this disease. Success will probably depend on using combinations of effective agents and treating patients in the early stages of disease, such as patients with smouldering multiple myeloma.

The adverse effect of FOPNL genomic variant is reversed by bortezomib-based treatment protocols in multiple myeloma

Fibroblast growth factor receptor 1 oncogene partner N-terminal like gene (FOPNL) rs72773978 polymorphism was identified as an adverse prognostic factor in multiple myeloma (MM). We aimed to investigate the associations of rs72773978 with clinical characteristics and treatment outcome in 373 Hungarian MM patients. In our cohort, FOPNL polymorphism showed differential prognostic effect that depended on the treatment applied. Among patients treated with non-proteasome inhibitor (PI)-based therapy, carriership of the minor allele was significantly associated with adverse overall survival (p=.022). In contrast, the adverse effect was overcome by the application of PI-containing treatment (p=.048). Multivariate analyses revealed the independent adverse effect of rs72773978 on survival in the non-PI-treated group (p=.045), but not in PI treatment (OS: p=.093). We confirmed the adverse prognostic effect of rs72773978 associated with non-PI-based treatment regimens. Our results point to the importance of genotypic prognostic information associated with complex clinical background MM.

Improved survival in multiple myeloma, with a diminishing racial gap and a widening socioeconomic status gap over three decades

Multiple myeloma (MM) is estimated to have 30,280 new cases and be associated with 12,590 deaths in 2017. However, quantitative analysis for survival, based on a large population, is lacking. Data were extracted from a total of 33,170 cases from nine registry sites in the Surveillance, Epidemiology, and End Results database. The current study shows that the incidence for MM remained relatively stable between 1981 and 2010, with 4.6, 4.7, and 4.7 per 100,000 persons in each decade. In addition, survival for MM improved each decade with a larger increment in the last two decades, with a narrowing survival gap among races and a widening gap among socioeconomic status (SES) groups. The survival gap changes in races and SES groups may guide clinicians to design better treatment protocols and call for the pressing need for health-care policy to fill the gap among SES groups.

SurvivalGWAS_SV: software for the analysis of genome-wide association studies of imputed genotypes with "time-to-event" outcomes

BACKGROUND

Analysis of genome-wide association studies (GWAS) with "time to event" outcomes have become increasingly popular, predominantly in the context of pharmacogenetics, where the survival endpoint could be death, disease remission or the occurrence of an adverse drug reaction. However, methodology and software that can efficiently handle the scale and complexity of genetic data from GWAS with time to event outcomes has not been extensively developed.

RESULTS

SurvivalGWAS_SV is an easy to use software implemented using C# and run on Linux, Mac OS X & Windows operating systems. SurvivalGWAS_SV is able to handle large scale genome-wide data, allowing for imputed genotypes by modelling time to event outcomes under a dosage model. Either a Cox proportional hazards or Weibull regression model is used for analysis. The software can adjust for multiple covariates and incorporate SNP-covariate interaction effects.

CONCLUSIONS

We introduce a new console application analysis tool for the analysis of GWAS with time to event outcomes. SurvivalGWAS_SV is compatible with high performance parallel computing clusters, thereby allowing efficient and effective analysis of large scale GWAS datasets, without incurring memory issues. With its particular relevance to pharmacogenetic GWAS, SurvivalGWAS_SV will aid in the identification of genetic biomarkers of patient response to treatment, with the ultimate goal of personalising therapeutic intervention for an array of diseases.

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.

Management of high-risk Myeloma: an evidence-based review of treatment strategies

INTRODUCTION

Despite the progress made in the treatment of patients with multiple myeloma over recent decades, a significant cohort with high-risk disease as defined by specific clinical and genetic criteria continue to respond poorly to standard treatment. These patients represent a particular challenge to the treating physician and require early identification as well as personalized treatment strategies.

AREAS COVERED

In this review, we discuss the prognostic impact of adverse clinical, radiological and genetic factors, evaluate available scoring systems and highlight key aspects of the therapeutic management of high-risk myeloma. MEDLINE and recent scientific meetings' databases were searched for the keywords 'high-risk' and 'multiple myeloma' and relevant studies relating to both diagnostic and therapeutic approaches were identified. Expert commentary: A case is made for intensive induction using combinations of novel agents, early high-dose therapy supported by autologous stem cell transplantation and the widespread use of maintenance therapies. Novel therapeutic options, especially in the field of immunotherapy, are currently explored in clinical trials and have the potential to further improve outcomes for patients with high-risk multiple myeloma.