Identification of Differentially Expressed miRNAs in Peripheral t-Cell Lymphomas.

Peripheral T-cell lymphomas (PTCLs) are rare and heterogeneous tumors whose biology is largely unknown. Interestingly, the commonest subtypes (i.e. PTCL not otherwise specified, NOS; angioimmunoblastic T-cell lymphoma, AITL; and anaplastic large cell lymphoma, ALCL) present on one hand few disease-specific molecular features and, on the other hand, several apparently common abnormalities. So far, no data are available regarding miRNA expression in these tumors. In order to identify miRNA deregulated in PTCLs, we performed an extensive miRNA profiling (by studying 379 targets on the TaqMan Array MicroRNA Cards) of 44 PTCLs (including 23 PTCLs/NOS, 12 ALCLs, and 9 AITLs) and 13 sample representative of normal T-cell sub-populations (CD4+ and CD8+, both resting and activated). In addition, for all these cases, gene expression profiles (GEPs) were generated by the Ilumina whole genome DASL-assay. TaqMan Quantitative-PCR (qPCR) was then used for validation. First, we found that PTCLs and normal T-cells could be easily distinguished based on their miRNA profile, by both unsupervised and supervised analysis. Specifically, the latter identified 91 miRNA differentially expressed in PTCLs vs. T-cells with a fold change ≥2 and a pvalue<0.01. Interestingly, the predicted target genes of such miRNA were involved in relevant cellular functions (such as cell proliferation, apoptosis, signal transduction etc.) and were found to be differentially expressed in tumor vs. controls, indicating a functional impact of miRNA deregulation in the molecular phenotype of neoplastic T-cells. Intriguingly, several drugs were estimated in silico to be able to interfere with pathways controlled by the de-regulated miRNA, including flavopiridol, everolimus/ temsirolimus, and forodesine. Secondly, by supervised analysis (ANOVA), we identified miRNA differentially expressed among PTCL/NOS, AITL and ALCL. Indeed, basing on such miRNA it was possible to roughly separate the different entities by hierarchical clustering (HC) (chi-square, p=0.0005). Specifically, we found 7 miRNA differentially expressed in PTCL/NOS vs. AITL, 26 in PTCL/NOS vs. ALK- ALCL, and 16 in ALK- vs. ALK+ ALCL. Selected miRNA were then studied by qPCR in an independent set of PTCLs (including 10 PTCL/NOS, 5 AITL, 5 ALK- ALCL, and 5 ALK+ ALCL) as for validation. Subsequently, in order to assess the impact of miRNA on the GEP, we picked up the miRNA most efficient in differentiating the diverse tumors (miR-431, miR-887, miR-889, and miR-155), and we studied the expression of their predicted target genes. Indeed, we found that miR-431 target genes were differentially expressed in PTCL/NOS vs. AITL (GSEA, q-value=0.45), and basing on their expression, HC could efficiently divide the two diseases (chi-square, p=0.004). Similarly, miR-889 targets were differentially expressed in PTCL/NOS vs. ALK- ALCL (GSEA, q-value=0; chi-square for HC, p=0.01), while miR-155 targets were differentially expressed in ALK+ vs. ALK- ALCL (GSEA, q-value=0; chi-square for HC, p<0.001). In conclusion, we performed for the first time an extensive miRNA profiling of PTCLs and combined it with global GEP. Importantly we identified miRNAs deregulated in PTCLs with possible pathogenetic implications. In addition, we found miRNAs, whose detection might be relevant for the differential diagnosis of PTCL subtypes. Finally, we provided in silico evidences that the cellular pathway controlled by de-regulated miRNA in PTCLs might serve as potential therapeutic targets, thus warranting further functional investigation