EBV-miR-BHRF1-2 targets PRDM1/Blimp1: potential role in EBV lymphomagenesis.

PRDM1/Blimp1, a master regulator of B-cell terminal differentiation, has been identified as a tumor suppressor gene in aggressive lymphomas, including diffuse large B-cell lymphoma (DLBCL). It has been shown in DLBCL and Hodgkin lymphoma that PRDM1 is downregulated by cellular microRNAs. In this study, we identify the Epstein-Barr virus (EBV) microRNA (miRNA), EBV-miR-BHRF1-2, as a viral miRNA regulator of PRDM1. EBV-miR-BHRF1-2 repressed luciferase reporter activity by specific interaction with the seed region within the PRDM1 3' untranslated region. EBV-miR-BHRF1-2 inhibition upregulated PRDM1 protein expression in lymphoblastoid cell lines (LCL), supporting a role of miR-BHRF1-2 in PRDM1 downregulation in vivo. Discordance of PRDM1 messenger RNA and protein expressions is associated with high EBV-miR-BHRF1-2 levels in LCLs and primary post-transplant EBV-positive DLBCL. Enforced expression of PRDM1-induced apoptosis and cell cycle arrest in LCL cells. Inhibition of EBV-miR-BHRF1-2 negatively regulates cell cycle and decreases expression of SCARNA20, a small nucleolar RNA that is also downregulated by PRDM1 overexpression. The interaction between EBV-miR-BHRF1-2 and PRDM1 may be one of the mechanisms by which EBV-miR-BHRF1-2 promotes EBV lymphomagenesis. Our results support the potential of EBV-miR-BHRF1-2 as a therapeutic target in EBV-associated lymphoma.

The transcriptional modulator BCL6 as a molecular target for breast cancer therapy.

Inappropriate expression or activation of transcription factors can drive patterns of gene expression, leading to the malignant behavior of breast cancer cells. We have found that the transcriptional repressor BCL6 is highly expressed in breast cancer cell lines, and its locus is amplified in about half of primary breast cancers. To understand how BCL6 regulates gene expression in breast cancer cells, we used chromatin immunoprecipitation followed by deep sequencing to identify the BCL6 binding sites on a genomic scale. This revealed that BCL6 regulates a unique cohort of genes in breast cancer cell lines compared with B-cell lymphomas. Furthermore, BCL6 expression promotes the survival of breast cancer cells, and targeting BCL6 with a peptidomimetic inhibitor leads to apoptosis of these cells. Finally, combining a BCL6 inhibitor and a signal transducer and activator of transcription3 inhibitor provided enhanced cell killing in triple-negative breast cancer cell lines, suggesting that combination therapy may be particularly useful. Thus, targeting BCL6 alone or in conjunction with other signaling pathways may be a useful therapeutic strategy for treating breast cancer.

Cancer systems biology: embracing complexity to develop better anticancer therapeutic strategies.

The transformation of normal cells into cancer cells and maintenance of the malignant state and phenotypes are associated with genetic and epigenetic deregulations, altered cellular signaling responses and aberrant interactions with the microenvironment. These alterations are constantly evolving as tumor cells face changing selective pressures induced by the cells themselves, the microenvironment and drug treatments. Tumors are also complex ecosystems where different, sometime heterogeneous, subclonal tumor populations and a variety of nontumor cells coexist in a constantly evolving manner. The interactions between molecules and between cells that arise as a result of these alterations and ecosystems are even more complex. The cancer research community is increasingly embracing this complexity and adopting a combination of systems biology methods and integrated analyses to understand and predictively model the activity of cancer cells. Systems biology approaches are helping to understand the mechanisms of tumor progression and design more effective cancer therapies. These approaches work in tandem with rapid technological advancements that enable data acquisition on a broader scale, with finer accuracy, higher dimensionality and higher throughput than ever. Using such data, computational and mathematical models help identify key deregulated functions and processes, establish predictive biomarkers and optimize therapeutic strategies. Moving forward, implementing patient-specific computational and mathematical models of cancer will significantly improve the specificity and efficacy of targeted therapy, and will accelerate the adoption of personalized and precision cancer medicine.

Characterization of the human cumulus cell transcriptome during final follicular maturation and ovulation.

Cumulus expansion and oocyte maturation are central processes in ovulation. Knowledge gained from rodent and other mammalian models has revealed some of the molecular pathways associated with these processes. However, the equivalent pathways in humans have not been thoroughly studied and remain unidentified. Compact cumulus cells (CCs) from germinal vesicle cumulus oocyte complexes (COCs) were obtained from patients undergoing in vitro maturation (IVM) procedures. Expanded CCs from metaphase 2 COC were obtained from patients undergoing IVF/ICSI. Global transcriptome profiles of the samples were obtained using state-of-the-art RNA sequencing techniques. We identified 1746 differentially expressed (DE) genes between compact and expanded CCs. Most of these genes were involved in cellular growth and proliferation, cellular movement, cell cycle, cell-to-cell signaling and interaction, extracellular matrix and steroidogenesis. Out of the DE genes, we found 89 long noncoding RNAs, of which 12 are encoded within introns of genes known to be involved in granulosa cell processes. This suggests that unique noncoding RNA transcripts may contribute to the regulation of cumulus expansion and oocyte maturation. Using global transcriptome sequencing, we were able to generate a library of genes regulated during cumulus expansion and oocyte maturation processes. Analysis of these genes allowed us to identify important new genes and noncoding RNAs potentially involved in COC maturation and cumulus expansion. These results may increase our understanding of the process of oocyte maturation and could ultimately improve the efficacy of IVM treatment.