Identification of miRSNPs associated with the risk of multiple myeloma

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 Léon”. 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

Genetically determined telomere length and multiple myeloma risk and outcome

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

Inherited variation in the xenobiotic transporter pathway and survival of multiple myeloma patients

Over the past four decades, remarkable progress has been made in the treatment and prognosis of multiple myeloma (MM), although it remains an incurable disease. Chemotherapy resistance is a major hurdle for treatment efficacy. Drug resistance can be innate and so driven by genes involved in the drug metabolism pathways. We performed an association study of 71 germline variants within the major genes in those pathways (ABCB1, ABCC2, ABCG2, and their regulators NR1I2/PXR and NR1I3/CAR) in the International Multiple Myeloma rESEarch (IMMEnSE) consortium, consisting of 1365 MM cases with survival information recruited in 5 European countries. Two of the SNPs showed a significant association with the survival of MM patients, namely rs2235013, located in ABCB1 [Hazard ratio (HR) = 1·52, 95% confidence interval (CI) = 1·18-1·95, P = 0·00087], and rs4148388, located in ABCC2 (HR = 2·15, 95% CI = 1·44-3·22, P = 0·0001). ABCC2 plays an essential role in transporting various anticancer drugs, including several used against MM, out of the cell. In silico analyses predict that the variant alleles of four SNPs in linkage disequilibrium with ABCC2-rs4148388 are associated with increased gene expression. Overexpression of ABCC2 increases drug clearance and therefore may induce drug resistance mechanisms. In conclusion, we found a promising association between ABCC2-rs4148388 and MM outcome that is supported by a plausible biological explanation.This work was partially supported by intramural funds of DKFZ and University of Pisa. This work was also partially supported by grant from FIBAO foundation and from the Instituto de Salud Carlos III (Madrid, Spain; PI17/02276).info:eu-repo/semantics/publishedVersio

Common gene variants within 3′‐untranslated regions as modulators of multiple myeloma risk and survival

International audienc

Does a multiple myeloma polygenic risk score predict overall survival of myeloma patients?

Background: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) iden-tified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival Methods: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consor-tium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associa-tions were meta-analyzed. Results: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P &lt; 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09-1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01-1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Conclusions: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. Impact: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma

A pleiotropic variant in <I>DNAJB4</I> is associated with multiple myeloma risk

Pleiotropy, which consists of a single gene or allelic variant affecting multiple unrelated traits, is common across cancers, with evidence for genome-wide significant loci shared across cancer and noncancer traits. This feature is particularly relevant in multiple myeloma (MM) because several susceptibility loci that have been identified to date are pleiotropic. Therefore, the aim of this study was to identify novel pleiotropic variants involved in MM risk using 28 684 independent single nucleotide polymorphisms (SNPs) from GWAS Catalog that reached a significant association (P