Person:

Brock, Amy Monique Lepre

With advances in screening, the incidence of detection of premalignant breast lesions has increased in recent decades; however, treatment options remain limited to surveillance or surgical removal by lumpectomy or mastectomy. We hypothesized that disease progression could be blocked by RNA interference (RNAi) therapy and set out to develop a targeted therapeutic delivery strategy. Using computational gene network modeling, we identified HoxA1 as a putative driver of early mammary cancer progression in transgenic C3(1)-SV40TAg mice. Silencing this gene in cultured mouse or human mammary tumor spheroids resulted in increased acinar lumen formation, reduced tumor cell proliferation, and restoration of normal epithelial polarization. When the HoxA1 gene was silenced in vivo via intraductal delivery of nanoparticle-formulated small interfering RNA (siRNA) through the nipple of transgenic mice with early-stage disease, mammary epithelial cell proliferation rates were suppressed, loss of estrogen and progesterone receptor expression was prevented, and tumor incidence was reduced by 75%. This approach that leverages new advances in systems biology and nanotechnology offers a novel noninvasive strategy to block breast cancer progression through targeted silencing of critical genes directly within the mammary epithelium.

Background: Interactions between mRNA and the cytoskeleton are critical for the localization of a number of transcripts in eukaryotic somatic cells. To characterize additional transcripts that may be subject to this form of regulation, we developed a two-step approach that utilizes biochemical fractionation of cells to isolate transcripts from different subcellular compartments followed by microarray analysis to examine and compare these subpopulations of transcripts in a massively-parallel manner. Results: Using this approach, mRNA was extracted from the cytoskeleton-rich and the cytosolic fractions of the promyelocytic HL-60 cell line. We identify a subset of 22 transcripts that are significantly enriched in the cytoskeleton-associated population. The majority of these encode structural proteins and/or proteins known to interact with elements of the cytoskeleton. Localization required an intact actin cytoskeleton and was largely conserved upon differentiation of precursor HL-60 cells to a macrophage-like phenotype. Conclusions: We conclude that the association of transcripts with the actin cytoskeleton in somatic cells may be a critical post-transcriptional regulatory event that controls a larger class of genes than has previously been recognized.

Structural features found in biomolecular networks that are absent in random networks produced by simple algorithms can provide insight into the function and evolution of cell regulatory networks. Here we analyze “betweenness” of network nodes, a graph theoretical centrality measure, in the yeast protein interaction network. Proteins that have high betweenness, but low connectivity (degree), were found to be abundant in the yeast proteome. This finding is not explained by algorithms proposed to explain the scale-free property of protein interaction networks, where low-connectivity proteins also have low betweenness. These data suggest the existence of some modular organization of the network, and that the high-betweenness, low-connectivity proteins may act as important links between these modules. We found that proteins with high betweenness are more likely to be essential and that evolutionary age of proteins is positively correlated with betweenness. By comparing different models of genome evolution that generate scale-free networks, we show that rewiring of interactions via mutation is an important factor in the production of such proteins. The evolutionary and functional significance of these observations are discussed.