FRET-Based Probe for High-Throughput DNA Intercalator Drug Discovery and In Vivo Imaging.

Molecules that bind DNA by intercalating its bases remain among the most potent cancer therapies and antimicrobials due to their interference with DNA-processing proteins. To accelerate the discovery of novel intercalating drugs, we designed a fluorescence resonance energy transfer (FRET)-based probe that reports on DNA intercalation, allowing rapid and sensitive screening of chemical libraries in a high-throughput format. We demonstrate that the method correctly identifies known DNA intercalators in approved drug libraries and discover previously unreported intercalating compounds. When introduced in cells, the oligonucleotide-based probe rapidly distributes in the nucleus, allowing direct imaging of the dynamics of drug entry and its interaction with DNA in its native environment. This enabled us to directly correlate the potency of intercalators in killing cultured cancer cells with the ability of the drug to penetrate the cell membrane. The combined capability of the single probe to identify intercalators in vitro and follow their function in vivo can play a valuable role in accelerating the discovery of novel DNA-intercalating drugs or repurposing approved ones.

Benzo[a]pyrene diol epoxide stimulates an inflammatory response in normal human lung fibroblasts through a p53 and JNK mediated pathway.

Cellular responses to carcinogens are typically studied in transformed cell lines, which do not reflect the physiological status of normal tissues. To address this question, we have characterized the transcriptional program and cellular responses of human lung WI-38 fibroblasts upon exposure to the ultimate carcinogen benzo[a]pyrene diol epoxide (BPDE). In contrast to observations in cell lines, we find that BPDE treatment induces a strong inflammatory response in these normal fibroblasts. Whole-genome microarrays show induction of numerous inflammatory factors, including genes that encode interleukins (ILs), growth factors and enzymes related to prostaglandin synthesis and signaling. Real-time reverse transcription-polymerase chain reaction and enzyme-linked immunosorbent assay (ELISA) revealed a time- and dose-dependent-induced expression and production of cyclooxygenase 2, prostglandin E2 and IL1B, IL6 and IL8. In parallel, cell cycle progression and DNA repair processes were repressed, but DNA damage signaling was increased via p53-Ser15 phosphorylation and induced expression levels of GADD45A, CDKN1A, BTG2 and SESN1. Network analysis suggested that activator protein 1 transcription factors may link the cell cycle response and DNA damage signaling with the inflammatory stress-response in these cells. We confirmed this hypothesis by showing that p53-dependent signaling through c-jun N-terminal kinase (JNK) led to increased cJun-Ser63 phosphorylation and that inhibition of JNK-mediated cJun activation using p53- or JNK-specific inhibitors significantly reduced IL gene expression and subsequent production of IL8. This is the first demonstration that a strong inflammatory response is triggered in normal fibroblasts by BPDE and that this occurs through coordinated regulation with other cellular processes.

Network modeling links breast cancer susceptibility and centrosome dysfunction.

Many cancer-associated genes remain to be identified to clarify the underlying molecular mechanisms of cancer susceptibility and progression. Better understanding is also required of how mutations in cancer genes affect their products in the context of complex cellular networks. Here we have used a network modeling strategy to identify genes potentially associated with higher risk of breast cancer. Starting with four known genes encoding tumor suppressors of breast cancer, we combined gene expression profiling with functional genomic and proteomic (or 'omic') data from various species to generate a network containing 118 genes linked by 866 potential functional associations. This network shows higher connectivity than expected by chance, suggesting that its components function in biologically related pathways. One of the components of the network is HMMR, encoding a centrosome subunit, for which we demonstrate previously unknown functional associations with the breast cancer-associated gene BRCA1. Two case-control studies of incident breast cancer indicate that the HMMR locus is associated with higher risk of breast cancer in humans. Our network modeling strategy should be useful for the discovery of additional cancer-associated genes.