• Multiple Myeloma
• mirSNP
• miRNA

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. About 63 000 subjects are reported to die from the disease each year, accounting for 0.9% of all cancer deaths and nearly 10% of all haematological neoplastic diseases.
Prognosis is usually unfavourable, with a mean overall survival ranging between 20 and 60 months. It has been shown that MM usually evolves from an asymptomatic premalignant condition termed monoclonal gammopathy of undetermined significance (MGUS). In some patients, an intermediate asymptomatic, but more advanced premalignant stage, defined as smouldering multiple myeloma (SMM) could be clinically recognized.
Converging evidence of MM in monozygotic twins and familial aggregation of MM strongly suggest that MM aetiology has a robust genetic component. Single Nucleotide Polymorphisms (SNPs) are the major source of genetic variation in humans and thought to be responsible, at least in part, for the individual differences in genetic susceptibility to complex diseases as tumors. In the last ten years several studies have identified SNPs associated with the disease susceptibility.
Genetic polymorphisms in miRNA-binding sites in target genes may alter the strength of miRNA– mRNA interactions, thus deregulating protein levels. This category of SNPs are called miR-SNPs. I analyzed 12 SNPs located in the 3' UTR region of miRNAs target genes, with the aim of testing whether they are associated with MM risk. Those MiR-SNP were previously selected from an in silico genome-wide search for their potential ability to alter binding of miRNAs to their target sequences.
My study population consisted of 1935 controls and 2457 cases recruited from 7 European countries and from Israel and Japan in the context of the IMMEnSE (International Multiple Myeloma rESEarch) consortium. I performed the genotyping with TaqMan technology.
Association between SNPs and multiple myeloma risk was assessed with unconditional logistic regression using allelic, codominant, dominant and recessive inheritance models, adjusting by age, gender, and region of origin. Afterwords I performed a meta-analysis between my data and the data from a previously published genome-wide association study (GWAS). The SNPs rs13409 (located in the 3’UTR of the PUOF5 gene), rs1419881 (CCHCR1), rs1049633, rs1049623 (both in DDR1) have shown significant associations with MM risk, with no heterogeneity between IMMEnSE and the GWAS in most of inheritance models tested.