No abstract

No abstract

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.

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 × 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.

Multiple 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 3'UTR 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.