Page 163 - 2019_05-HaematologicaMondo-web

miRNA in Richter syndrome
to our scarce understanding of the transformation of CLL to RS. We investigated the miRNA regulatory net- works composed of nodes and edges, where the nodes are miRNA genes, and the edges (links) are the molecu- lar interactions (a high statistical correlation between two miRNA nodes in a given set of patients). It is impor- tant to note that this method also recognizes miRNA that are not SDE as key elements. The network analysis provides a different perspective on the role of a miRNA than the commonly used expression profiling, and the results do not always overlap. By using the qRT-PCR expression data, we generated a 25-miRNA expression network for each of the four groups of patients of the extended UTMDACC cohort (Figure 5A). We observed that the number of edges increased significantly from 29 in the group 1a network to 55 in the group 1b network compared to the group 2a and group 2b networks, in which only one new extra-edge appeared, with the number of edges increasing from 53 to 54 (P<0.05, c2=3.913) (Figure 5B, left panel). When comparing the behavior of the miRNA nodes in patients who under- went Richter transformation, i.e., groups 1a and 1b, we observed an increase in the connectivity of nodes (P=0.0007), indicating a complete reprogramming of the
A
miRNA network during the transformation (Figure 5B, middle panel). When we performed the same compari- son for the miRNA networks of the “control” CLL patients who did not develop RS, i.e., groups 2a and 2b, we observed no significant change in the connectivity of the nodes (Figure 5B, right panel). The miRNA network of group 1a is a disjointed graph with many isolated nodes which, after Richter transformation (group 1b), becomes a highly-connected graph, with only two iso- lated miRNA (miR-23b and miR-155) (Figure 5A). The hubs (defined as the nodes with the highest connectivi- ty, i.e., the miRNA best connected in the network) spe- cific for Richter transformation (hubs in group 1b versus group 1a, but not in group 2a versus group 2b) were miR-191, miR-17 and miR-29c, which we named hub- specific (HUS) miRNA.
Additionally, these data were confirmed when we gen- erated an independent 40-miRNA network for the four groups of patients by using the Firefly assay expression data (Online Supplementary Figure S5). Therefore, both qRT- PCR-based and Firefly-based networks confirmed that Richter transformation leads to a complete rearrangement of the miRNA network, with a significant increase in the number of edges and the addition of new miRNA hubs.
BC
Figure 3. microRNA expression validation by quantitative reverse transcription polymerase chain reaction and gene expression profiling. (A) Quantitative reverse transcription polymerase chain reaction (qRT-PCR) expression analysis shows that miR-21 and miR-146b are significantly upregulated, and miR-150 is significantly downregulated at the time of Richter transformation (RT) when compared to their expression at the time of chronic lymphocytic leukemia (CLL) diagnosis (Dx) in the extended set of Richter syndrome (RS) samples, but not in the extended set of control CLL samples. (B) Gene expression profiling analysis in an independent set of RS/CLL samples from Ulm University shows significant upregulation of miR-21, miR-146b and miR-181b in RS when compared to CLL. (C) Heatmap showing the miRNA signature for CLL with subsequent transformation (“Richter”) and CLL without transformation (“CLL”) in the validation cohort (“Ulm University”) after hierar- chical clustering on genes (Pearson correlation, average linkage). *P<0.05; **P<0.01. For additional Information, see Online Supplementary Figure S3.
haematologica | 2019; 104(5)
1009