Understanding the molecular underpinnings of cancer is of critical importance to developing targeted intervention strategies. Identification of such targets, however, is notoriously difficult and unpredictable. Malignant cell transformation requires the cooperation of a few oncogenic mutations that cause substantial reorganization of many cell features 1 and induce complex changes in gene expression patterns 2-6 . Genes critical to this multi-faceted cellular phenotype thus only have been identified following signaling pathway analysis 7-10 or on an ad hoc basis 4, 11-14 . Our observations that cell transformation by cooperating oncogenic lesions depends on synergistic modulation of downstream signaling circuitry 15-17 suggest that malignant transformation is a highly cooperative process, involving synergy at multiple levels of regulation, including gene expression. Here we show that a large proportion of genes controlled synergistically by loss-of-function p53 and Ras activation are critical to the malignant state. Remarkably, 14 among 24 such 'cooperation response genes' (CRGs) were found to contribute to tumor formation in gene perturbation experiments. In contrast, only one in 14 perturbations of genes responding in a non-synergistic manner had a similar effect. Synergistic control of gene expression by oncogenic mutations thus emerges as an underlying key to malignancy and provides an attractive rationale for identifying intervention targets in gene networks downstream of oncogenic gain and loss-of-function mutations.To identify genes regulated synergistically by cooperating oncogenic mutations at genomic scale, we compared mRNA expression profiles of young adult murine colon (YAMC) cells
Efficient construction of BAC-based human artificial chromosomes (HACs) requires optimization of each key functional unit as well as development of techniques for the rapid and reliable manipulation of high-molecular weight BAC vectors. Here, we have created synthetic chromosome 17-derived alpha-satellite arrays, based on the 16-monomer repeat length typical of natural D17Z1 arrays, in which the consensus CENP-B box elements are either completely absent (0/16 monomers) or increased in density (16/16 monomers) compared to D17Z1 alpha-satellite (5/16 monomers). Using these vectors, we show that the presence of CENP-B box elements is a requirement for efficient de novo centromere formation and that increasing the density of CENP-B box elements may enhance the efficiency of de novo centromere formation. Furthermore, we have developed a novel, high-throughput methodology that permits the rapid conversion of any genomic BAC target into a HAC vector by transposon-mediated modification with synthetic alpha-satellite arrays and other key functional units. Taken together, these approaches offer the potential to significantly advance the utility of BAC-based HACs for functional annotation of the genome and for applications in gene transfer.
In searching for small-molecule compounds that inhibit proliferation and survival of diffuse large B-cell lymphoma (DLBCL) cells and may, therefore, be exploited as potential therapeutic agents for this disease, we identified the commonly used and well-tolerated antibiotic doxycycline as a strong candidate. Here, we demonstrate that doxycycline inhibits the growth of DLBCL cells both in vitro and in mouse xenograft models. In addition, we show that doxycycline accumulates in DLBCL cells to high concentrations and affects multiple signaling pathways that are crucial for lymphomagenesis. Our data reveal the deneddylating activity of COP-9 signalosome (CSN) as a novel target of doxycycline and suggest that doxycycline may exert its effects in DLBCL cells in part through a CSN5-HSP90 pathway. Consistently, knockdown of CSN5 exhibited similar effects as doxycycline treatment on DLBCL cell survival and HSP90 chaperone function. In addition to DLBCL cells, doxycycline inhibited growth of several other types of non-Hodgkin lymphoma cells in vitro. Together, our results suggest that doxycycline may represent a promising therapeutic agent for DLBCL and other non-Hodgkin lymphomas subtypes.
BackgroundHuman Artificial Chromosomes (HACs) are potentially useful vectors for gene transfer studies and for functional annotation of the genome because of their suitability for cloning, manipulating and transferring large segments of the genome. However, development of HACs for the transfer of large genomic loci into mammalian cells has been limited by difficulties in manipulating high-molecular weight DNA, as well as by the low overall frequencies of de novo HAC formation. Indeed, to date, only a small number of large (>100 kb) genomic loci have been reported to be successfully packaged into de novo HACs.ResultsWe have developed novel methodologies to enable efficient assembly of HAC vectors containing any genomic locus of interest. We report here the creation of a novel, bimolecular system based on bacterial artificial chromosomes (BACs) for the construction of HACs incorporating any defined genomic region. We have utilized this vector system to rapidly design, construct and validate multiple de novo HACs containing large (100–200 kb) genomic loci including therapeutically significant genes for human growth hormone (HGH), polycystic kidney disease (PKD1) and ß-globin. We report significant differences in the ability of different genomic loci to support de novo HAC formation, suggesting possible effects of cis-acting genomic elements. Finally, as a proof of principle, we have observed sustained ß-globin gene expression from HACs incorporating the entire 200 kb ß-globin genomic locus for over 90 days in the absence of selection.ConclusionTaken together, these results are significant for the development of HAC vector technology, as they enable high-throughput assembly and functional validation of HACs containing any large genomic locus. We have evaluated the impact of different genomic loci on the frequency of HAC formation and identified segments of genomic DNA that appear to facilitate de novo HAC formation. These genomic loci may be useful for identifying discrete functional elements that may be incorporated into future generations of HAC vectors.
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