32 research outputs found

    Bortezomib with Thalidomide plus Dexamethasone Compared with Thalidomide plus Doxorubicin and Dexamethasone as Induction Therapy in Previously Untreated Multiple Myeloma Patients

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    We conducted a retrospective study to compare thalidomide, bortezomib and dexamethasone (VTD) with thalidomide plus doxorubicin and dexamethasone (TAD). Until now, first-line treatment with these combinations has not been reported in any comparative study. The principal objective of this study was to determine whether VTD would improve the complete response (CR) and CR plus very good partial response rates compared with TAD. Second, using additional methods, such as flow cytometric assays and polymerase chain reaction technology, we evaluated the molecular residual disease in the subgroup of patients that obtained CR. Our study shows that VTD is a superior induction regimen compared with TAD, with a higher response rate after induction, translating into greater CR plus very good partial response

    Arsenic Trioxide with Ascorbic Acid and High-Dose Melphalan: Results of a Phase II Randomized Trial

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    AbstractArsenic trioxide (ATO) is synergistic with ascorbic acid (AA) and melphalan against myeloma both in vitro and in vivo. The aim of this randomized phase II trial was to determine the safety and efficacy of a combination of ATO, melphalan, and AA as preparative regimen in 48 patients undergoing autologous hematopoietic stem cell transplantation (ASCT) for multiple myeloma (MM). Forty-eight patients received melphalan 200 mg/m2 i.v. over 2 days and AA 1000 mg i.v. over 7 days in 3 treatment arms: no ATO (arm 1), ATO 0.15 mg/kg i.v. × 7 days (arm 2), and ATO 0.25 mg/kg i.v. × 7 days (arm 3). No dose-limiting toxicity, engraftment failure, or nonrelapse mortality (NRM) was seen in the first 100 days post-ASCT. Complete responses (CR) were seen in 12 of 48 patients (25%), with an overall response rate (ORR = CR + PR) of 85%. Median progression-free survival (PFS) was 25 months; median overall survival (OS) has not yet been reached. There was no significant difference in CR, PFS, or OS among the 3 treatment arms, and no adverse effect of ATO on melphalan pharmacokinetics. Addition of ATO + AA to high-dose melphalan is safe and well tolerated as a preparative regimen for MM

    Genetically determined telomere length and multiple myeloma risk and outcome

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    This work was partially supported by intramural funds of Univerity of Pisa and DKFZ; by Fondo de Investigaciones Sanitarias (Madrid, Spain) [PI12/02688 to J. S., PI17/02276 to J.S.]; by Instituto de Salud Carlos III, co-funded by FEDER funds —a way to build Europe—[PI14-00613 to V.M.] and by Agency for Management of University and Research Grants (AGAUR) of the Catalan Government (Barcelona, Spain) [2017SGR723 to V.M.]. Open Access funding enabled and organized by Projekt DEAL.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 x 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.Univerity of PisaHelmholtz AssociationInstituto de Salud Carlos III PI12/02688 PI17/02276Instituto de Salud Carlos IIIEuropean CommissionFEDER funds-a way to build Europe PI14-00613Agency for Management of University and Research Grants (AGAUR) of the Catalan Government (Barcelona, Spain) 2017SGR723Projekt DEA

    A polygenic risk score for multiple myeloma risk prediction

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    This work was partially supported by intramural funds of the University of Pisa, DKFZ, and University Hospital of Southern Jutland, Denmark, and by a grant of the French National Cancer Institute (INCA). The authors wish to thank Dr. Dominic Edelmann (Division of Biostatistics, DKFZ) for helpful advice about data analysis.There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53-4.69, p = 3.55 x 10(-15) for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34-4.33, p = 1.62 x 10(-13) for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.University of Pisa, DKFZUniversity Hospital of Southern Jutland, DenmarkInstitut National du Cancer (INCA) Franc

    Identification of miRSNPs associated with the risk of multiple myeloma

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    Accepted articleMultiple myeloma (MM) is a malignancy of plasma cells usually infiltrating the bone marrow, associated with the production of a monoclonal immunoglobulin (M protein) which can be detected in the blood and/or urine. Multiple lines of evidence suggest that genetic factors are involved in MM pathogenesis, and several studies have identified single nucleotide polymorphisms (SNPs) associated with the susceptibility to the disease. SNPs within miRNA-binding sites in target genes (miRSNPs) may alter the strength of miRNA-mRNA interactions, thus deregulating protein expression. MiRSNPs are known to be associated with risk of various types of cancer, but they have never been investigated in MM. We performed an in silico genome-wide search for miRSNPs predicted to alter binding of miRNAs to their target sequences. We selected 12 miRSNPs and tested their association with MM risk. Our study population consisted of 1,832 controls and 2,894 MM cases recruited from seven European countries and Israel in the context of the IMMEnSE (International Multiple Myeloma rESEarch) consortium. In this population two SNPs showed an association with p<0.05: rs286595 (located in gene MRLP22) and rs14191881 (located in gene TCF19). Results from IMMEnSE were meta-analyzed with data from a previously published genome-wide association study (GWAS). The SNPs rs13409 (located in the 3UTR of the POU5F1 gene), rs1419881 (TCF19), rs1049633, rs1049623 (both in DDR1) showed significant associations with MM risk. In conclusion, we sought to identify genetic polymorphisms associated with MM risk starting from genome-wide prediction of miRSNPs. For some mirSNPs, we have shown promising associations with MM risk. What's new? Even though deregulation of miRNA expression has been associated with human cancers little information is available regarding their relation with MM susceptibility. We performed an in silico genome-wide search for miRSNPs and selected the most promising ones for an association study. The SNPs with the strongest associations with MM risk are localized in genes which have never been related with MM.This work was partially funded by: intramural funds of German Cancer Research Center (DKFZ), Grant ref. HUS412A1271 from the “Gerencia Regional de Salud de la Junta de Castilla y LĂ©on”. This work was supported by grants from the Instituto de Salud Carlos III (Madrid, Spain; PI12/02688). Catalan Government DURSI grant 2014SGR647 and Instituto de Salud Carlos III, co7funded by FEDER funds –a way to build Europe– grants PI11701439 and PIE13/00022info:eu-repo/semantics/publishedVersio

    Polymorphisms within autophagy-related genes as susceptibility biomarkers for multiple myeloma: a meta-analysis of three large cohorts and functional characterization

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    Functional data used in this project have been meticulously catalogued and archived in the BBMRI-NL data infrastructure (https://hfgp.bbmri.nl/, accessed on 12 February 2020) using the MOLGENIS open-source platform for scientific data.Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10−9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10−4−5.79 × 10−14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10−4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10−4) and circulating serum concentrations of Monocyte hemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 SNP corre lated with numbers of CD19+ B cells, CD19+CD3− B cells, CD5+ IgD− cells, IgM− cells, IgD−IgM− cells, and CD4−CD8− PBMCs (p = 4.9 × 10−4−8.6 × 10−4 ) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27− cells (p = 9.3 × 10−4 ). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3−, MCP-2−, and IL20-dependent pathways.This work was supported by the European Union’s Horizon 2020 research and innovation program, N° 856620 and by grants from the Instituto de Salud Carlos III and FEDER (Madrid, Spain; PI17/02256 and PI20/01845), Consejería de Transformación Económica, Industria, Conocimiento y Universidades and FEDER (PY20/01282), from the CRIS foundation against cancer, from the Cancer Network of Excellence (RD12/10 Red de Cáncer), from the Dietmar Hopp Foundation and the German Ministry of Education and Science (BMBF: CLIOMMICS [01ZX1309]), and from National Cancer Institute of the National Institutes of Health under award numbers: R01CA186646, U01CA249955 (EEB).This work was also funded d by Portuguese National funds, through the Foundation for Science and Technology (FCT)—project UIDB/50026/2020 and UIDP/50026/2020 and by the project NORTE-01-0145-FEDER-000055, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF)

    Exome sequencing identifies germline variants in DIS3 in familial multiple myeloma

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    [Excerpt] Multiple myeloma (MM) is the third most common hematological malignancy, after Non-Hodgkin Lymphoma and Leukemia. MM is generally preceded by Monoclonal Gammopathy of Undetermined Significance (MGUS) [1], and epidemiological studies have identified older age, male gender, family history, and MGUS as risk factors for developing MM [2]. The somatic mutational landscape of sporadic MM has been increasingly investigated, aiming to identify recurrent genetic events involved in myelomagenesis. Whole exome and whole genome sequencing studies have shown that MM is a genetically heterogeneous disease that evolves through accumulation of both clonal and subclonal driver mutations [3] and identified recurrently somatically mutated genes, including KRAS, NRAS, FAM46C, TP53, DIS3, BRAF, TRAF3, CYLD, RB1 and PRDM1 [3,4,5]. Despite the fact that family-based studies have provided data consistent with an inherited genetic susceptibility to MM compatible with Mendelian transmission [6], the molecular basis of inherited MM predisposition is only partly understood. Genome-Wide Association (GWAS) studies have identified and validated 23 loci significantly associated with an increased risk of developing MM that explain ~16% of heritability [7] and only a subset of familial cases are thought to have a polygenic background [8]. Recent studies have identified rare germline variants predisposing to MM in KDM1A [9], ARID1A and USP45 [10], and the implementation of next-generation sequencing technology will allow the characterization of more such rare variants. [...]French National Cancer Institute (INCA) and the Fondation Française pour la Recherche contre le Myélome et les Gammapathies (FFMRG), the Intergroupe Francophone du Myélome (IFM), NCI R01 NCI CA167824 and a generous donation from Matthew Bell. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors thank the Association des Malades du Myélome Multiple (AF3M) for their continued support and participation. Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organizatio
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