microRNA analysis in normal and neoplastic human B cell phenotypes


Riccardo Dalla-Favera and Andrea Califano




The short endogenous RNAs known as microRNAs (miRNAs) have been shown to play a key role in oncogenesis by post-transcriptional regulation of genes involved in regulatory and signaling pathways. We have characterized the expression profiles of various miRNAs to identify which ones are differentially expressed during normal differentiation of B cells and in malignancies. We developed a tool to find the downstream targets of these differentially-expressed miRNAs, and adapted existing network inference tools to find their upstream regulators. Finally, we explored the use of miRNA expression signatures to identify different normal and cancerous cell types.


Researchers are increasingly recognizing the important role of miRNA and other regulatory RNAs in a variety of biological processes, including oncogenesis. By post-transcriptionally regulating the amount of protein produced by genes, these ubiquitous molecules add an extra layer to the complex molecular networks, but their detailed role is not well understood in specific cellular contexts.

We are exploiting our detailed understand of B-cell biology, both in normal and cancerous cells, to explore the role of miRNA in oncogenesis. The first step was to survey the miRNAs, both in normal human B cells at different stages of development (naive, germinal center, and memory cell) and from a Burkitt lymphoma cell line. (Basso 2009). We identified 178 miRNAs, 75 of which had not been previously reported. Differential expression of numerous known and newly identified miRNAs was evident during B-cell differentiation and germinal-center transit. The results showed that naive and memory B cells share a large fraction of the most abundant miRNAs, while the centroblasts have a more distinct miRNA profile. Many of the abundant miRNAs are specifically expressed.

To identify downstream targets of miRNAs, we applied several existing methods. In addition, we developed an algorithm for the Prediction of MiRNA-targets by Enrichment of Regulons (PreMiER), which flags transcription factors whose activity is affected by changes in miRNA overexpression or silencing of a particular miRNA. This algorithm specifically identifies miRNA target genes that are themselves transcription factors, which are in turn expected to regulate many other genes.

To identify upstream regulators of miRNA active in normal or malignant B cells, we have adapted the established ARACNe network-inference algorithm to analyze expression data from chronic lymphocytic leukemia and follicular lymphoma samples. We are currently experimentally validating the predicted regulatory interactions.

Finally, we explored the power of miRNA expression signatures to distinguish various normal and malignant cells in the B cell family. The results suggest that miRNA expression profiles are informative enough to discriminate among different cancer types and normal samples. However, these expression profiles had a large proportion of samples with no detectable expression of most miRNA probes, so new strategies will be required to reliably interpret this kind of data.

This ongoing research will exploit our detailed knowledge of the B-cell system and the molecular networks that control both its normal and malignant state to illuminate the role of miRNAs in the early stages of cancer.

Project Publications

Klein U, Lia M, Crespo M, Siegel R, Shen Q, Mo T, Ambesi-Impiombato A, Califano A, Migliazza A, Bhagat G, Dalla-Favera R.  The DLEU2/miR-15a/16-1 cluster controls B-cell proliferation and its deletion leads to chronic lymphocytic leukemia.  Cancer Cell. 2010;17(1):28-40.


Basso K, Sumazin P, Morozov P, Schneider C, Maute RL, Kitagawa Y, Mandelbaum J, Haddad J Jr, Chen CZ, Califano A, Dalla-Favera R. Identification of the human mature B cell miRNome. Immunity. 2009;30(5):744-52.

Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ. miRBase: tools for microRNA genomics . Nucleic Acids Res. 2008;36(Database issue):D154-8.

Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, Pfeffer S, Rice A, Kamphorst AO, Landthaler M, Lin C, Socci ND, Hermida L, Fulci V, Chiaretti S, Foà R, Schliwka J, Fuchs U, Novosel A, Müller RU, Schermer B, Bissels U, Inman J, Phan Q, Chien M, Weir DB, Choksi R, De Vita G, Frezzetti D, Trompeter HI, Hornung V, Teng G, Hartmann G, Palkovits M, Di Lauro R, Wernet P, Macino G, Rogler CE, Nagle JW, Ju J, Papavasiliou FN, Benzing T, Lichter P, Tam W, Brownstein MJ, Bosio A, Borkhardt A, Russo JJ, Sander C, Zavolan M, Tuschl T. A mammalian microRNA expression atlas based on small RNA library sequencing. Cell. 2007;129(7):1401-14.

Mani KM, Lefebvre C, Wang K, Lim WK, Basso K, Dalla-Favera R, et al. A systems biology approach to prediction of oncogenes and molecular perturbation targets in B-cell lymphomas. Mol Syst Biol. 2008;4:169.