Identification of MicroRNA Expression Patterns and Definition of a MicroRNAs/mRNA Regulatory Network in Distinct Molecular Groups of Multiple Myeloma.
Authors: Lionetti Marta , Biasiolo Marta , Agnelli Luca , Todoerti Katia , Mosca Laura , Fabris Sonia , Sales Gabriele , Deliliers Giorgio Lambertenghi , Bicciato Silvio , Lombardi Luigia , Bortoluzzi Stefania , Neri Antonino 
Published: October 2019

Abstract 2824

Poster Board II-800

Multiple myeloma (MM) is a malignant proliferation of bone marrow (BM) plasma cells (PCs), characterized by a profound genomic instability involving both numerical and structural chromosomal aberrations of potential prognostic relevance. The discovery of microRNA (miRNA) genes, encoding for a class of small non-coding RNAs involved in the regulation of cell cycle, survival and differentiation programs, has added a further level of complexity to normal and cancer cell biology; it has been suggested that chromosomal abnormalities and other types of genetic or epigenetic alterations might contribute to miRNA deregulation in cancer. To date, only little evidence of miRNA expression/deregulation in multiple myeloma (MM) has been reported. To characterize miRNA expression profiling of MM plasma cells (PCs) and integrate miRNA expression data with other molecular features of MM patients, global miRNA expression profiles of PCs isolated from BM biopsies of 38 newly diagnosed MM, 2 plasma cell leukemia patients, and 3 healthy donors were generated using the Agilent Human miRNA microarray V2 (representing 723 human mature miRNAs from the Sanger miRBase v10.1). All of the patients had previously been characterized by FISH for the main IGH translocations and other genetic abnormalities; they were also profiled for global gene expression by means of Affymetrix U133A arrays; nineteen of the patients profiled for miRNA expression underwent genome-wide DNA analysis using Affymetrix GeneChip® Human Mapping 50K XbaI microarrays. An unsupervised analysis of the samples, using conventional hierarchical clustering algorithm and based on the most variably expressed miRNAs across the dataset, grouped the PCs from healthy donors separately from MM PCs; among the pathological samples, the most striking finding was that the seven patients with t(4;14) (TC4) were tightly clustered, as were four out of the five samples with translocated MAF genes (TC5). A partial grouping of the TC2 cases (mostly hyperdiploid) was also observed, whereas the TC1, showing t(11;14), and TC3 (mostly expressing Cyclin D2), samples were dispersed along the dendrogram. A multiclass supervised analysis of the miRNA expression between the members of the 5 TC groups highlighted specific miRNA signatures, in particular characterizing the TC4 and TC5 groups. A slight miRNA signature was observed in t(11;14) cases and TC2 group, whereas we could not identify any TC3-specific miRNA signature. None of the differentially expressed miRNAs in patients with specific IGH translocations maps to the rearranged chromosomal regions. The levels of some differentially expressed miRNAs were quantified by means of Q-RT-PCR in all of the 43 samples, using specific TaqMan® microRNA assays (Applied Biosystems); a linear correlation analysis indicated very good correspondence between microarrays and Q-RT-PCR data. Furthermore, the expression of specific miRNAs was also evaluated in 14 additional cases, four carrying t(11;14), seven t(4;14), and three t(14;16) or t(14;20): as well, in this broaden panel the selected miRNAs confirmed their TC-specific over-expression. The occurrence of other lesions, such as 1q gain, 13q and 17p deletions, and hyperdiploidy, was slightly characterized by specific miRNA signatures. Furthermore, the integrated analysis with the genomic profiles revealed the occurrence of several allelic imbalances significantly associated with the altered expression of miRNAs located in the involved regions, such as let-7b at 22q13.31 (loss) and miR-142-3p at 17q22 (gain), or miR-140-3p at 16q22 (loss-of-heterozygosity). Finally, in an attempt to define the consequences of deregulated miRNA expression, we performed an integrative analysis based on computational target prediction, miRNA and mRNA profiling. Specifically, we searched for putative functional targeting relationships in MM cells supported by expression data, i.e. anti-correlations between miRNA and target mRNA expression profiles, and thus defined a global miRNAs/mRNAs regulatory network. Our data provide the first evidence of miRNA deregulation in the context of the molecular subtypes of MM, and represent the first attempt to define the complex of miRNAs/mRNAs regulatory relationships, aimed at deepening our understanding of the involvement of specific miRNAs and target genes in the pathology of the disease.

Disclosures:

No relevant conflicts of interest to declare.