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      The varied distribution and impact of RAS codon and other key DNA alterations across the translocation cyclin D subgroups in multiple myeloma

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          Abstract

          We examined a set of 805 cases that underwent DNA sequencing using the FoundationOne Heme (F1H) targeted sequencing panel and gene expression profiling. Known and likely variant calls from the mutational data were analyzed for significant associations with gene expression defined translocation cyclin D (TC) molecular subgroups. The spectrum of KRAS, NRAS, and BRAF codon mutations varied across subgroups with NRAS mutations at Q61 codon being common in hyperdiploid (HRD) and t(11;14) myeloma while being rare in MMSET and MAF. In addition, the presence of RAS-RAF mutations was inversely associated with NFκB pathway activation in all subgroups excluding MAF. In the MMSET subgroup, cases with low FGFR3 expression frequently had RAS-RAF mutations. Conditional inference tree analysis determined that mutation and homozygous deletion of TP53, CDKN2C, and RB1 were key prognostic factors associated with adverse outcome in a non-relapse clinical setting. In conclusion, this study highlights the heterogeneity in the distribution and clinical outcomes of RAS codon and other mutations in multiple myeloma dependent upon primary molecular subgroup.

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          Most cited references28

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          Modeling Survival Data: Extending the Cox Model

          This is a book for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Its goal is to extend the toolkit beyond the basic triad provided by most statistical packages: the Kaplan-Meier estimator, log-rank test, and Cox regression model. Building on recent developments motivated by counting process and martingale theory, it shows the reader how to extend the Cox model to analyse multiple/correlated event data using marginal and random effects (frailty) models. It covers the use of residuals and diagnostic plots to identify influential or outlying observations, assess proportional hazards and examine other aspects of goodness of fit. Other topics include time-dependent covariates and strata, discontinuous intervals of risk, multiple time scales, smoothing and regression splines, and the computation of expected survival curves. A knowledge of counting processes and martingales is not assumed as the early chapters provide an introduction to this area. The focus of the book is on actual data examples, the analysis and interpretation of the results, and computation. The methods are now readily available in SAS and S-Plus and this book gives a hands-on introduction, showing how to implement them in both packages, with worked examples for many data sets. The authors call on their extensive experience and give practical advice, including pitfalls to be avoided. Terry Therneau is Head of the Section of Biostatistics, Mayo Clinic, Rochester, Minnesota. He is actively involved in medical consulting, with emphasis in the areas of chronic liver disease, physical medicine, hematology, and laboratory medicine, and is an author on numerous papers in medical and statistical journals. He wrote two of the original SAS procedures for survival analysis (coxregr and survtest), as well as the majority of the S-Plus survival functions. Patricia Grambsch is Associate Professor in the Division of Biostatistics, School of Public Health, University of Minnesota. She has collaborated extensively with physicians and public health researchers in chronic liver disease, cancer prevention, hypertension clinical trials and psychiatric research. She is a fellow the American Statistical Association and the author of many papers in medical and statistical journals.
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            CDK inhibitors: positive and negative regulators of G1-phase progression.

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              The molecular classification of multiple myeloma.

              To better define the molecular basis of multiple myeloma (MM), we performed unsupervised hierarchic clustering of mRNA expression profiles in CD138-enriched plasma cells from 414 newly diagnosed patients who went on to receive high-dose therapy and tandem stem cell transplants. Seven disease subtypes were validated that were strongly influenced by known genetic lesions, such as c-MAF- and MAFB-, CCND1- and CCND3-, and MMSET-activating translocations and hyperdiploidy. Indicative of the deregulation of common pathways by gene orthologs, common gene signatures were observed in cases with c-MAF and MAFB activation and CCND1 and CCND3 activation, the latter consisting of 2 subgroups, one characterized by expression of the early B-cell markers CD20 and PAX5. A low incidence of focal bone disease distinguished one and increased expression of proliferation-associated genes of another novel subgroup. Comprising varying fractions of each of the other 6 subgroups, the proliferation subgroup dominated at relapse, suggesting that this signature is linked to disease progression. Proliferation and MMSET-spike groups were characterized by significant overexpression of genes mapping to chromosome 1q, and both exhibited a poor prognosis relative to the other groups. A subset of cases with a predominating myeloid gene expression signature, excluded from the profiling analyses, had more favorable baseline characteristics and superior prognosis to those lacking this signature.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                25 April 2017
                24 February 2017
                : 8
                : 17
                : 27854-27867
                Affiliations
                1 The Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
                2 The Institute of Cancer Research, London, UK
                3 Eramus University, Rotterdam, NL
                4 Department of Haematology, Newcastle University, Newcastle-upon-Tyne, UK
                5 Memorial Sloan Kettering Cancer Center, New York, New York, USA
                6 FoundationOne Medicine, Cambridge, Massachusetts, USA
                7 Tufts Medical Center, Boston, Massachusetts, USA
                8 Mayo Clinic, Scottsdale, Arizona, USA
                Author notes
                Correspondence to: Caleb K. Stein, CKStein@ 123456uams.edu
                Article
                15718
                10.18632/oncotarget.15718
                5438613
                28427158
                8818ed80-861c-4dbd-8a4e-b6cfc69ac68c
                Copyright: © 2017 Stein et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 January 2017
                : 15 February 2017
                Categories
                Research Paper

                Oncology & Radiotherapy
                multiple myeloma,gene expression profiling,mutational analysis,translocation cyclin d (tc)

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