Search for rare protein altering variants influencing susceptibility to multiple myeloma.

The genetic basis underlying the inherited risk of developing multiple myeloma (MM) is largely unknown. To examine the impact of rare protein altering variants on the risk of developing MM we analyzed high-coverage exome sequencing data on 513 MM cases and 1,569 healthy controls, performing both single variant and gene burden tests. We did not identify any recurrent coding low-frequency alleles (1-5%) with moderate effect that were statistically associated with MM. In a gene burden analysis we did however identify a promising relationship between variation in the marrow kinetochore microtubule stromal gene KIF18A, which plays a role in control mitotic chromosome positioning dynamics, and risk of MM (P =3.6x10-6). Further analysis showed KIF18A displays a distinct pattern of expression across molecular subgroups of MM as well as being associated with patient survival. Our results inform future study design and provide a resource for contextualizing the impact of candidate MM susceptibility genes.

Genetic Predisposition to Multiple Myeloma at 5q15 Is Mediated by an ELL2 Enhancer Polymorphism.

Multiple myeloma (MM) is a malignancy of plasma cells. Genome-wide association studies have shown that variation at 5q15 influences MM risk. Here, we have sought to decipher the causal variant at 5q15 and the mechanism by which it influences tumorigenesis. We show that rs6877329 G > C resides in a predicted enhancer element that physically interacts with the transcription start site of ELL2. The rs6877329-C risk allele is associated with reduced enhancer activity and lowered ELL2 expression. Since ELL2 is critical to the B cell differentiation process, reduced ELL2 expression is consistent with inherited genetic variation contributing to arrest of plasma cell development, facilitating MM clonal expansion. These data provide evidence for a biological mechanism underlying a hereditary risk of MM at 5q15.

Mutational Spectrum, Copy Number Changes, and Outcome: Results of a Sequencing Study of Patients With Newly Diagnosed Myeloma.

PURPOSE: At the molecular level, myeloma is characterized by copy number abnormalities and recurrent translocations into the immunoglobulin heavy chain locus. Novel methods, such as massively parallel sequencing, have begun to describe the pattern of tumor-acquired mutations, but their clinical relevance has yet to be established. METHODS: We performed whole-exome sequencing for 463 patients who presented with myeloma and were enrolled onto the National Cancer Research Institute Myeloma XI trial, for whom complete molecular cytogenetic and clinical outcome data were available. RESULTS: We identified 15 significantly mutated genes: IRF4, KRAS, NRAS, MAX, HIST1H1E, RB1, EGR1, TP53, TRAF3, FAM46C, DIS3, BRAF, LTB, CYLD, and FGFR3. The mutational spectrum is dominated by mutations in the RAS (43%) and nuclear factor-κB (17%) pathways, but although they are prognostically neutral, they could be targeted therapeutically. Mutations in CCND1 and DNA repair pathway alterations (TP53, ATM, ATR, and ZNFHX4 mutations) are associated with a negative impact on survival. In contrast, those in IRF4 and EGR1 are associated with a favorable overall survival. We combined these novel mutation risk factors with the recurrent molecular adverse features and international staging system to generate an international staging system mutation score that can identify a high-risk population of patients who experience relapse and die prematurely. CONCLUSION: We have refined our understanding of genetic events in myeloma and identified clinically relevant mutations that may be used to better stratify patients at presentation.

visPIG--a web tool for producing multi-region, multi-track, multi-scale plots of genetic data.

We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk), a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R, Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser or the WashU Epigenome Browser allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV). Other locally run data visualisation software such as Circos require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…). It also allows annotation of genes and other custom features in the plotted region(s). Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3).