TY  - JOUR
A1  - Mitchell, Jonathan S.
A1  - Li, Ni
A1  - Weinhold, Niels
A1  - Försti, Asta
A1  - Ali, Mina
A1  - van Duin, Mark
A1  - Thorleifsson, Gudmar
A1  - Johnson, David C.
A1  - Chen, Bowang
A1  - Halvarsson, Britt-Marie
A1  - Gudbjartsson, Daniel F.
A1  - Kuiper, Rowan
A1  - Stephens, Owen W.
A1  - Bertsch, Uta
A1  - Broderick, Peter
A1  - Campo, Chiara
A1  - Einsele, Hermann
A1  - Gregory, Walter A.
A1  - Gullberg, Urban
A1  - Henrion, Marc
A1  - Hillengass, Jens
A1  - Hoffmann, Per
A1  - Jackson, Graham H.
A1  - Johnsson, Ellinor
A1  - Jöud, Magnus
A1  - Kristinsson, Sigurdur Y.
A1  - Lenhoff, Stig
A1  - Lenive, Oleg
A1  - Mellqvist, Ulf-Henrik
A1  - Migliorini, Gabriele
A1  - Nahi, Hareth
A1  - Nelander, Sven
A1  - Nickel, Jolanta
A1  - Nöthen, Markus M.
A1  - Rafnar, Thorunn
A1  - Ross, Fiona M.
A1  - da Silva Filho, Miguel Inacio
A1  - Swaminathan, Bhairavi
A1  - Thomsen, Hauke
A1  - Turesson, Ingemar
A1  - Vangsted, Annette
A1  - Vogel, Ulla
A1  - Waage, Anders
A1  - Walker, Brian A.
A1  - Wihlborg, Anna-Karin
A1  - Broyl, Annemiek
A1  - Davies, Faith E.
A1  - Thorsteinsdottir, Unnur
A1  - Langer, Christian
A1  - Hansson, Markus
A1  - Kaiser, Martin
A1  - Sonneveld, Pieter
A1  - Stefansson, Kari
A1  - Morgan, Gareth J.
A1  - Goldschmidt, Hartmut
A1  - Hemminki, Kari
A1  - Nilsson, Björn
A1  - Houlston, Richard S.
T1  - Genome-wide association study identifies multiple susceptibility loci for multiple myeloma
JF  - Nature Communications
N2  - 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.
KW  - Cancer genetics
KW  - Genome-wide association studies
KW  - Myeloma
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-165983
VL  - 7
ER  - 
TY  - JOUR
A1  - Ludwig, Heinz
A1  - Delforge, Michel
A1  - Facon, Thierry
A1  - Einsele, Hermann
A1  - Gay, Francesca
A1  - Moreau, Philippe
A1  - Avet-Loiseau, Hervé
A1  - Boccadoro, Mario
A1  - Hajek, Roman
A1  - Mohty, Mohamad
A1  - Cavo, Michele
A1  - Dimopoulos, Meletios A
A1  - San-Miguel, Jesús F
A1  - Terpos, Evangelos
A1  - Zweegman, Sonja
A1  - Garderet, Laurent
A1  - Mateos, María-Victoria
A1  - Cook, Gordon
A1  - Leleu, Xavier
A1  - Goldschmidt, Hartmut
A1  - Jackson, Graham
A1  - Kaiser, Martin
A1  - Weisel, Katja
A1  - van de Donk, Niels W. C. J.
A1  - Waage, Anders
A1  - Beksac, Meral
A1  - Mellqvist, Ulf H.
A1  - Engelhardt, Monika
A1  - Caers, Jo
A1  - Driessen, Christoph
A1  - Bladé, Joan
A1  - Sonneveld, Pieter
T1  - Prevention and management of adverse events of novel agents in multiple myeloma: a consensus of the European Myeloma Network
JF  - Leukemia
N2  - During the last few years, several new drugs have been introduced for treatment of patients with multiple myeloma, which have significantly improved the treatment outcome. All of these novel substances differ at least in part in their mode of action from similar drugs of the same drug class, or are representatives of new drug classes, and as such present with very specific side effect profiles. In this review, we summarize these adverse events, provide information on their prevention, and give practical guidance for monitoring of patients and for management of adverse events.
KW  - disease prevention
KW  - myeloma
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-237338
VL  - 32
ER  - 
TY  - JOUR
A1  - Went, Molly
A1  - Sud, Amit
A1  - Speedy, Helen
A1  - Sunter, Nicola J.
A1  - Försti, Asta
A1  - Law, Philip J.
A1  - Johnson, David C.
A1  - Mirabella, Fabio
A1  - Holroyd, Amy
A1  - Li, Ni
A1  - Orlando, Giulia
A1  - Weinhold, Niels
A1  - van Duin, Mark
A1  - Chen, Bowang
A1  - Mitchell, Jonathan S.
A1  - Mansouri, Larry
A1  - Juliusson, Gunnar
A1  - Smedby, Karin E
A1  - Jayne, Sandrine
A1  - Majid, Aneela
A1  - Dearden, Claire
A1  - Allsup, David J.
A1  - Bailey, James R.
A1  - Pratt, Guy
A1  - Pepper, Chris
A1  - Fegan, Chris
A1  - Rosenquist, Richard
A1  - Kuiper, Rowan
A1  - Stephens, Owen W.
A1  - Bertsch, Uta
A1  - Broderick, Peter
A1  - Einsele, Hermann
A1  - Gregory, Walter M.
A1  - Hillengass, Jens
A1  - Hoffmann, Per
A1  - Jackson, Graham H.
A1  - Jöckel, Karl-Heinz
A1  - Nickel, Jolanta
A1  - Nöthen, Markus M.
A1  - da Silva Filho, Miguel Inacio
A1  - Thomsen, Hauke
A1  - Walker, Brian A.
A1  - Broyl, Annemiek
A1  - Davies, Faith E.
A1  - Hansson, Markus
A1  - Goldschmidt, Hartmut
A1  - Dyer, Martin J. S.
A1  - Kaiser, Martin
A1  - Sonneveld, Pieter
A1  - Morgan, Gareth J.
A1  - Hemminki, Kari
A1  - Nilsson, Björn
A1  - Catovsky, Daniel
A1  - Allan, James M.
A1  - Houlston, Richard S.
T1  - Genetic correlation between multiple myeloma and chronic lymphocytic leukaemia provides evidence for shared aetiology
JF  - Blood Cancer Journal
N2  - The clustering of different types of B-cell malignancies in families raises the possibility of shared aetiology. To examine this, we performed cross-trait linkage disequilibrium (LD)-score regression of multiple myeloma (MM) and chronic lymphocytic leukaemia (CLL) genome-wide association study (GWAS) data sets, totalling 11,734 cases and 29,468 controls. A significant genetic correlation between these two B-cell malignancies was shown (Rg = 0.4, P = 0.0046). Furthermore, four of the 45 known CLL risk loci were shown to associate with MM risk and five of the 23 known MM risk loci associate with CLL risk. By integrating eQTL, Hi-C and ChIP-seq data, we show that these pleiotropic risk loci are enriched for B-cell regulatory elements and implicate B-cell developmental genes. These data identify shared biological pathways influencing the development of CLL and, MM and further our understanding of the aetiological basis of these B-cell malignancies.
KW  - cancer genetics
KW  - myeloma
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-233627
VL  - 9
ER  - 
TY  - JOUR
A1  - Walker, Brian A.
A1  - Mavrommatis, Konstantinos
A1  - Wardell, Christopher P.
A1  - Ashby, T. Cody
A1  - Bauer, Michael
A1  - Davies, Faith
A1  - Rosenthal, Adam
A1  - Wang, Hongwei
A1  - Qu, Pingping
A1  - Hoering, Antje
A1  - Samur, Mehmet
A1  - Towfic, Fadi
A1  - Ortiz, Maria
A1  - Flynt, Erin
A1  - Yu, Zhinuan
A1  - Yang, Zhihong
A1  - Rozelle, Dan
A1  - Obenauer, John
A1  - Trotter, Matthew
A1  - Auclair, Daniel
A1  - Keats, Jonathan
A1  - Bolli, Niccolo
A1  - Fulciniti, Mariateresa
A1  - Szalat, Raphael
A1  - Moreau, Phillipe
A1  - Durie, Brian
A1  - Stewart, A. Keith
A1  - Goldschmidt, Hartmut
A1  - Raab, Marc S.
A1  - Einsele, Hermann
A1  - Sonneveld, Pieter
A1  - San Miguel, Jesus
A1  - Lonial, Sagar
A1  - Jackson, Graham H.
A1  - Anderson, Kenneth C.
A1  - Avet-Loiseau, Herve
A1  - Munshi, Nikhil
A1  - Thakurta, Anjan
A1  - Morgan, Gareth
T1  - A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis
JF  - Leukemia
N2  - Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4% and 25.2%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3% for PFS and 46.5% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches.
KW  - cancer genomics
KW  - risk factors
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-233299
VL  - 33
ER  -