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Ofer Margalit

Publications and source records attributed to Ofer Margalit.

2 recordsLinked to original sources

BCL6 is regulated by p53 through a response element frequently disrupted in B-cell non-Hodgkin lymphoma.

The BCL6 transcriptional repressor mediates survival, proliferation, and differentiation blockade of B cells during the germinal-center reaction and is frequently misregulated in B-cell non-Hodgkin lymphoma (BNHL). The p53 tumor-suppressor gene is central to tumorigenesis. Microarray analysis identified BCL6 as a primary target of p53. The BCL6 intron 1 contains a region in which 3 types of genetic alterations are frequent in BNHL: chromosomal translocations, point mutations, and internal deletions. We therefore defined it as TMDR (translocations, mutations, and deletions region). The BCL6 gene contains a p53 response element (p53RE) residing within the TMDR. This p53RE contains a motif known to be preferentially targeted by somatic hypermutation. This p53RE is evolutionarily conserved only in primates. The p53 protein binds to this RE in vitro and in vivo. Reporter assays revealed that the BCL6 p53RE can confer p53-dependent transcriptional activation. BCL6 mRNA and protein levels increased after chemotherapy/radiotherapy in human but not in murine tissues. The increase in BCL6 mRNA levels was attenuated by the p53 inhibitor PFT-alpha. Thus, we define the BCL6 gene as a new p53 target, regulated through a RE frequently disrupted in BNHL.

Animals↗

Microarray-based gene expression profiling of hematologic malignancies: basic concepts and clinical applications.

Each cell in our body contains a set of tens of thousands of genes, out of which a set of several thousands determines the cell's characteristics. The deciphering of the sequence of the human genome combined with the technical feasibility to simultaneously measure the gene expression levels of thousands of genes had revolutionized our understanding of cellular processes. This ability has great significance in our comprehension of the mechanisms that bring about diseases in general and hematologic malignancies in particular. Several new high-throughput technologies, commonly referred as microarrays, enable us to perform such measurements and concurrently, bioinformatic and statistical tools were developed to analyze the data obtained by using microarrays. In this review we present examples of analyses of hematologic malignancies using microarrays which contribute to refinement of diagnosis, identification of novel disease subtypes and of relationships between diseases that were previously considered to be unrelated, prediction of response to treatment and identification of genes and pathways linked to pathogenesis, thus defining targets to rational therapy.

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