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Dive into the research topics where Brian A. Walker is active.

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Featured researches published by Brian A. Walker.


Nature | 1999

The chicken B locus is a minimal essential major histocompatibility complex.

Jim Kaufman; Sarah Milne; Thomas W. Göbel; Brian A. Walker; Jansen P. Jacob; Charles Auffray; Rima Zoorob; Stephan Beck

Here we report the sequence of the region that determines rapid allograft rejection in chickens, the chicken major histocompatibility complex (MHC). This 92-kilobase region of the B locus contains only 19 genes, making the chicken MHC roughly 20-fold smaller than the human MHC. Virtually all the genes have counterparts in the human MHC, defining a minimal essential set of MHC genes conserved over 200 million years of divergence between birds and mammals. They are organized differently, with the class III region genes located outside the class II and class I region genes. The absence of proteasome genes is unexpected and might explain unusual peptide-binding specificities of chicken class I molecules. The presence of putative natural killer receptor gene(s) is unprecedented and might explain the importance of the B locus in the response to the herpes virus responsible for Mareks disease. The small size and simplicity of the chicken MHC allows co-evolution of genes as haplotypes over considerable periods of time, and makes it possible to study the striking MHC-determined pathogen-specific disease resistance at the molecular level.


Nature Reviews Cancer | 2012

The genetic architecture of multiple myeloma

Gareth J. Morgan; Brian A. Walker; Faith E. Davies

Based on the clinical features of myeloma and related malignancies of plasma cells, it has been possible to generate a model system of myeloma progression from a normal plasma cell through smouldering myeloma to myeloma and then plasma cell leukaemia. Using this model system we can study at which points the genetic alterations identified through whole-tumour molecular analyses function in the initiation and progression of myeloma. Further genetic complexity, such as intraclonal heterogeneity, and insights into the molecular evolution and intraclonal dynamics in this model system are crucial to our understandings of tumour progression, treatment resistance and the use of currently available and future treatments.


Blood | 2010

A compendium of myeloma-associated chromosomal copy number abnormalities and their prognostic value

Brian A. Walker; Paola Leone; Laura Chiecchio; Nicholas J. Dickens; Matthew W. Jenner; Kevin Boyd; David C. Johnson; David Gonzalez; Gian Paolo Dagrada; Rebecca K.M. Protheroe; Zoe J. Konn; David M. Stockley; Walter Gregory; Faith E. Davies; Fiona M. Ross; Gareth J. Morgan

To obtain a comprehensive genomic profile of presenting multiple myeloma cases we performed high-resolution single nucleotide polymorphism mapping array analysis in 114 samples alongside 258 samples analyzed by U133 Plus 2.0 expression array (Affymetrix). We examined DNA copy number alterations and loss of heterozygosity (LOH) to define the spectrum of minimally deleted regions in which relevant genes of interest can be found. The most frequent deletions are located at 1p (30%), 6q (33%), 8p (25%), 12p (15%), 13q (59%), 14q (39%), 16q (35%), 17p (7%), 20 (12%), and 22 (18%). In addition, copy number-neutral LOH, or uniparental disomy, was also prevalent on 1q (8%), 16q (9%), and X (20%), and was associated with regions of gain and loss. Based on fluorescence in situ hybridization and expression quartile analysis, genes of prognostic importance were found to be located at 1p (FAF1, CDKN2C), 1q (ANP32E), and 17p (TP53). In addition, we identified common homozygously deleted genes that have functions relevant to myeloma biology. Taken together, these analyses indicate that the crucial pathways in myeloma pathogenesis include the nuclear factor-κB pathway, apoptosis, cell-cycle regulation, Wnt signaling, and histone modifications. This study was registered at http://isrctn.org as ISRCTN68454111.


Blood | 2012

Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4;14) and t(11;14) myeloma.

Brian A. Walker; Christopher P. Wardell; Lorenzo Melchor; Sanna Hulkki; Nicola E. Potter; David C. Johnson; Kerry Fenwick; Iwanka Kozarewa; David Gonzalez; Christopher J. Lord; Alan Ashworth; Faith E. Davies; Gareth J. Morgan

We have used whole exome sequencing to compare a group of presentation t(4;14) with t(11;14) cases of myeloma to define the mutational landscape. Each case was characterized by a median of 24.5 exonic nonsynonymous single-nucleotide variations, and there was a consistently higher number of mutations in the t(4;14) group, but this number did not reach statistical significance. We show that the transition and transversion rates in the 2 subgroups are similar, suggesting that there was no specific mechanism leading to mutation differentiating the 2 groups. Only 3% of mutations were seen in both groups, and recurrently mutated genes include NRAS, KRAS, BRAF, and DIS3 as well as DNAH5, a member of the axonemal dynein family. The pattern of mutation in each group was distinct, with the t(4;14) group being characterized by deregulation of chromatin organization, actin filament, and microfilament movement. Recurrent RAS pathway mutations identified subclonal heterogeneity at a mutational level in both groups, with mutations being present as either dominant or minor subclones. The presence of subclonal diversity was confirmed at a single-cell level using other tumor-acquired mutations. These results are consistent with a distinct molecular pathogenesis underlying each subgroup and have important impacts on targeted treatment strategies. The Medical Research Council Myeloma IX trial is registered under ISRCTN68454111.


Leukemia | 2012

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.

Kevin Boyd; Fiona M. Ross; Laura Chiecchio; Gianpaolo Dagrada; Zoe J. Konn; William Tapper; Brian A. Walker; Christopher P. Wardell; Walter Gregory; Alexander J. Szubert; Se Bell; J. A. Child; Graham Jackson; Faith E. Davies; Gareth J. Morgan

The association of genetic lesions detected by fluorescence in situ hybridization (FISH) with survival was analyzed in 1069 patients with newly presenting myeloma treated in the Medical Research Council Myeloma IX trial, with the aim of identifying patients associated with the worst prognosis. A comprehensive FISH panel was performed, and the lesions associated with short progression-free survival and overall survival (OS) in multivariate analysis were +1q21, del(17p13) and an adverse immunoglobulin heavy chain gene (IGH) translocation group incorporating t(4;14), t(14;16) and t(14;20). These lesions frequently co-segregated, and there was an association between the accumulation of these adverse FISH lesions and a progressive impairment of survival. This observation was used to define a series of risk groups based on number of adverse lesions. Taking this approach, we defined a favorable risk group by the absence of adverse genetic lesions, an intermediate group with one adverse lesion and a high-risk group defined by the co-segregation of >1 adverse lesion. This genetic grouping was independent of the International Staging System (ISS) and so was integrated with the ISS to identify an ultra-high-risk group defined by ISS II or III and >1 adverse lesion. This group constituted 13.8% of patients and was associated with a median OS of 19.4 months.


Blood | 2011

Aberrant global methylation patterns affect the molecular pathogenesis and prognosis of multiple myeloma

Brian A. Walker; Christopher P. Wardell; Laura Chiecchio; Emma M. Smith; Kevin Boyd; Antonino Neri; Faith E. Davies; Fiona M. Ross; Gareth J. Morgan

We used genome-wide methylation microarrays to analyze differences in CpG methylation patterns in cells relevant to the pathogenesis of myeloma plasma cells (B cells, normal plasma cells, monoclonal gammopathy of undetermined significance [MGUS], presentation myeloma, and plasma cell leukemia). We show that methylation patterns in these cell types are capable of distinguishing nonmalignant from malignant cells and the main reason for this difference is hypomethylation of the genome at the transition from MGUS to presentation myeloma. In addition, gene-specific hypermethylation was evident at the myeloma stage. Differential methylation was also evident at the transition from myeloma to plasma cell leukemia with remethylation of the genome, particularly of genes involved in cell-cell signaling and cell adhesion, which may contribute to independence from the bone marrow microenvironment. There was a high degree of methylation variability within presentation myeloma samples, which was associated with cytogenetic differences between samples. More specifically, we found methylation subgroups were defined by translocations and hyperdiploidy, with t(4;14) myeloma having the greatest impact on DNA methylation. Two groups of hyperdiploid samples were identified, on the basis of unsupervised clustering, which had an impact on overall survival. Overall, DNA methylation changes significantly during disease progression and between cytogenetic subgroups.


Journal of Clinical Oncology | 2015

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

Brian A. Walker; Eileen Boyle; Christopher P. Wardell; Alex Murison; Dil Begum; Nasrin M. Dahir; Paula Proszek; David C. Johnson; Martin Kaiser; Lorenzo Melchor; Lauren I. Aronson; Matthew Scales; Charlotte Pawlyn; Fabio Mirabella; John R Jones; Annamaria Brioli; Aneta Mikulášová; David A. Cairns; Walter Gregory; Ana Quartilho; Mark T. Drayson; Nigel H. Russell; Gordon Cook; Graham Jackson; Xavier Leleu; Faith E. Davies; Gareth J. Morgan

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.


Leukemia | 2014

Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms

Brian A. Walker; Christopher P. Wardell; Lorenzo Melchor; Annamaria Brioli; David C. Johnson; Martin Kaiser; Fabio Mirabella; Lucía López-Corral; Sean Humphray; Lisa Murray; Mark T. Ross; David R. Bentley; Norma C. Gutiérrez; Ramón García-Sanz; J. F. San Miguel; Faith E. Davies; D. González; Gareth J. Morgan

The mechanisms involved in the progression from monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM) to malignant multiple myeloma (MM) and plasma cell leukemia (PCL) are poorly understood but believed to involve the sequential acquisition of genetic hits. We performed exome and whole-genome sequencing on a series of MGUS (n=4), high-risk (HR)SMM (n=4), MM (n=26) and PCL (n=2) samples, including four cases who transformed from HR-SMM to MM, to determine the genetic factors that drive progression of disease. The pattern and number of non-synonymous mutations show that the MGUS disease stage is less genetically complex than MM, and HR-SMM is similar to presenting MM. Intraclonal heterogeneity is present at all stages and using cases of HR-SMM, which transformed to MM, we show that intraclonal heterogeneity is a typical feature of the disease. At the HR-SMM stage of disease, the majority of the genetic changes necessary to give rise to MM are already present. These data suggest that clonal progression is the key feature of transformation of HR-SMM to MM and as such the invasive clinically predominant clone typical of MM is already present at the SMM stage and would be amenable to therapeutic intervention at that stage.


Leukemia | 2014

Single-cell genetic analysis reveals the composition of initiating clones and phylogenetic patterns of branching and parallel evolution in myeloma

Lorenzo Melchor; Annamaria Brioli; Christopher P. Wardell; Alexander Murison; N E Potter; Martin Kaiser; Rosemary A Fryer; David C. Johnson; Dil Begum; S Hulkki Wilson; Gowri Vijayaraghavan; Ian Titley; Michele Cavo; Faith E. Davies; Brian A. Walker; Gareth J. Morgan

Although intratumor heterogeneity has been inferred in multiple myeloma (MM), little is known about its subclonal phylogeny. To describe such phylogenetic trees in a series of patients with MM, we perform whole-exome sequencing and single-cell genetic analysis. Our results demonstrate that at presentation myeloma is composed of two to six different major clones, which are related by linear and branching phylogenies. Remarkably, the earliest myeloma-initiating clones, some of which only had the initiating t(11;14), were still present at low frequencies at the time of diagnosis. For the first time in myeloma, we demonstrate parallel evolution whereby two independent clones activate the RAS/MAPK pathway through RAS mutations and give rise subsequently to distinct subclonal lineages. We also report the co-occurrence of RAS and interferon regulatory factor 4 (IRF4) p.K123R mutations in 4% of myeloma patients. Lastly, we describe the fluctuations of myeloma subclonal architecture in a patient analyzed at presentation and relapse and in NOD/SCID-IL2Rγnull xenografts, revealing clonal extinction and the emergence of new clones that acquire additional mutations. This study confirms that myeloma subclones exhibit different survival properties during treatment or mouse engraftment. We conclude that clonal diversity combined with varying selective pressures is the essential foundation for tumor progression and treatment resistance in myeloma.


Nature Genetics | 2012

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

Peter Broderick; Daniel Chubb; David C. Johnson; Niels Weinhold; Asta Försti; Amy Lloyd; Bianca Olver; Yussanne Ma; Sara E. Dobbins; Brian A. Walker; Faith E. Davies; Walter A. Gregory; J. Anthony Child; Fiona M. Ross; Graham Jackson; Kai Neben; Anna Jauch; Per Hoffmann; Thomas W. Mühleisen; Markus M. Nöthen; Susanne Moebus; Ian Tomlinson; Hartmut Goldschmidt; Kari Hemminki; Gareth J. Morgan; Richard S. Houlston

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.

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Gareth J. Morgan

University of Arkansas for Medical Sciences

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Faith E. Davies

University of Arkansas for Medical Sciences

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Christopher P. Wardell

University of Arkansas for Medical Sciences

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Martin Kaiser

Institute of Cancer Research

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Fiona M. Ross

University of Southampton

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Charlotte Pawlyn

Institute of Cancer Research

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David Gonzalez

The Royal Marsden NHS Foundation Trust

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Dil Begum

Institute of Cancer Research

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