Although high-throughput RNAi screens are widely used to identify novel drug targets, few hits turn out to be robust enough in follow-on preclinical validation, in part because of the differences between the behavior and response of cells grown in 2D monolayers compared with those grown in vivo following gene perturbation.
This issue is especially problematic when it comes to cancer research, as tumor cells in vivo are embedded in an interactive 3D microenvironment influenced by, among other things, non-cancerous cells, tumor stroma, and systemic and local regulators, according to researchers from ETH Zurich and biosciences firm InSphero.
To address this, the scientists have developed a high-throughput-compatible method to perform target identification and validation using RNAi in a 3D co-culture tumor microtissue model produced with the hanging drop technology, they wrote in the Journal of Biomolecular Screening.
To demonstrate the technology, the colon cancer cell line DLD1, which was engineered to express enhanced green fluorescence protein as a fluorescent reporter, was grown in combination with mouse NIH3T3 fibroblasts.
"DLD1 cells in this model failed to expand upon siRNA-mediated depletion of Kif11/Eg5, a member of the mitotic kinesin-like motor protein family," according to the team. "In contrast, these cancer cells proved to be more resistant to Kif11/Eg5 depletion when grown as a 2D monolayer."
The results provide a "striking example of the phenotypic differences produced in 2D versus 3D tissue culture models," and point to the potential of 3D cell culture models in discovering novel target genes or lead compounds for drug development.
Looking for a way to take advantage of exosomes' inherent transport properties, a group from Northwestern University has developed an approach to use these naturally occurring nanomaterials to carry microRNA-regulating agents.
The researchers specifically focused on spherical nucleic acids — a new class of potential therapeutics often consisting of gold nanoparticles cores with a dense shell of highly oriented oligonucleotides.
SNAs, they noted in a paper appearing in Small, exhibit "unique properties that make them good candidates for exosomal loading such as enhanced serum stability, rapid cell uptake without transfection agents, low immunogenicity, and the ability to control gene regulation."
These properties, they added, are "mediated by the dense shell of oligonucleotides around the gold nanoparticle, where oligonucleotides also could serve as signaling molecules for SNAs to be taken up by endogenous exosomes. Taken together, these unique properties allow SNAs to overcome many biological barriers ranging from resisting serum nucleases to crossing the cell membrane in order to be internalized within exosomes by utilizing the natural exosomal sorting process of cytoplasmic biomolecules."
To test their theory, the investigators constructed SNAs consisting of a DNA/locked nucleic acid gapmer recognition sequence targeting miR-21, an miRNA that has been associated with cancer. Using transmission electron microscopy, they showed that the SNAs are secreted into the extracellular environment from which they can be isolated and selectively reintroduced into the cell type from which they were derived. Further, exosome-encased SNAs were shown to knock down their miRNA target in prostate cancer cell lines by approximately 50 percent.
The Northwestern team noted that the approach used to encase SNAs is "impractical in its current state" due to inefficiency of SNA loading and the scale at which it can be done, but stated that the findings indicate the potential of synthetic exosome mimics that can be loaded with SNAs and gene-silencing cargo.
Given the need for effective tools to visualize high-throughput RNAi screening data in a dynamic fashion, researchers from the Institute of Molecular and Cell Biology in Singapore have developed an open-source desktop application to help store, analyze, and rapidly mine information from RNAi screening datasets.
Called ScreenSifter, the tool facilitates meta-data acquisition and long-term safe-storage, while the graphical user interface helps the definition of a hit list and the visualization of biological modules among the hits, through Gene Ontology and protein-protein interaction analyses, according to a paper in BMC Bioinformatics describing the application.
"Biologists with no extensive bioinformatics knowledge can upload their screen data in a simple .csv format, and have access to multiple screen analysis tools, including quality control, normalization and hit selection, as well as the ability to visualize the distribution of hit genes and graphically compare replicates," the scientists wrote.
ScreenSifter also allows for comparisons between different screens and includes visualization tools to poly subsets of screen data, such as specific genes or gene groups, while providing gene set enrichment analysis and protein-protein interaction information directly from or on hyperlinked plots.
Noting a lack of attention to the use of helper lipids in the development of lipid nanoparticles for siRNA and miRNA therapeutics, a team from Ohio State University has reported data showing the enhancement of LNPs through the addition of oleic acid.
Using the cationic lipid, N-[1-(2,3-dioleoyloxy)propyl]-N,N,N-trimethylammonium chloride, or DOTMA, as the foundation of their LNP, the scientists formulated a series of nanoparticles incorporating different helper lipids, then studied their particle size, surface charge, cellular uptake, and transfection activity in vitro.
Selecting oleic acid as the optimal helper lipid, the team then tested their LNP's ability to deliver the liver-specific miRNA miR-122 both in tumor cells and in animals.
Compared to the commercial transfection reagent Lipofectamine 2000, oleic acid-containing LNPs delivered microRNA-122 in a "more efficient manner," with a 1.8-fold increase in mature miR-122 expression and a 20 percent decrease in the miR-122 target Bcl-w, they wrote in the Journal of Controlled Release.
When they tested against Invivofectamine, which is specifically designed for hepatic delivery, they found their LNP formulation offered comparable liver accumulation and in vivo delivery efficacy.
Together, the data point to the importance of helper lipids in LNP delivery to the liver, they concluded.