January 15, 2012 (Vol. 32, No. 2)

In 2011, several big pharma companies dealt serious blows to RNA interference (RNAi) technology by abandoning or reducing their programs. But while RNAi may be down, it is far from out.

The discovery of RNAi electrified the field of biology and earned scientists the 2006 Nobel Prize in Medicine. Though the initial fever pitch excitement for RNAi therapeutics has dimmed in some circles, academic and biotech scientists continue to doggedly pursue the challenges that vex the field. Despite setbacks, many clinical trials are under way with more planned.

Keystone Symposia’s “Nucleic Acid Therapeutics” and CHI’s “High Content Analysis” meetings featured new technical approaches and disease-relevant applications for RNAi. Presentations described an allele-specific inhibition treatment for Huntington disease, optimizing high-content RNAi screens, deciphering mechanisms of biothreat pathogens, and use of improved lipid nanoparticles to deliver the RNAi payload.

Genetic illnesses, such as Huntington disease, often affect only one allele. The challenge for RNAi therapeutics is to specifically knock down only the mutant, but not the wild-type, allele.

“We are pursuing an allele-selective approach for inhibition that uses specially constructed single-stranded RNAs that act through the RNAi pathway,” said Dongbo Yu, M.D./Ph.D. student in the laboratory of David R. Corey, Ph.D., professor, pharmacology and biochemistry, University of Texas Southwestern Medical Center.

“Huntington disease is a devastating neurodegenerative disorder that presents in mid-life, and symptoms worsen until death. It is caused by extended runs of a trinucleotide repeating unit (CAG) within the first exon of the huntingtin gene. Normal alleles have 10–17 copies, but mutant alleles have ~35–100 CAG repeats,” Yu explained.

“Our lab previously identified several different classes of oligonucleotides that can specifically inhibit expression of the mutant huntingtin gene. These were either single- or double-stranded designs. However, each type had its own specific drawbacks such as low specificity, limited stability, and biodistribution and/or nuclease sensitivity.”

According to Yu, Isis Pharmaceuticals developed the novel single-stranded RNA (ssRNA) design and provided compounds to the Corey Lab.

“The hybrid chemistry developed by Isis combines the desired properties of antisense oligonucleotides and duplex RNAs into a single novel type of small RNA. We applied this new tool to selective inhibition of huntingtin expression.”

Yu and colleagues provided proof of concept in experiments that used patient-derived heterozygous fibroblast cell lines treated with these strategically mismatched ssRNAs.

“We found that the huntingtin gene was potently knocked down across a broad range of concentrations without significantly affecting the wild-type allele. These results represent the most potent and allele-selective inhibitors identified to date. They also suggest that there are unexplored RNAi pathways that remain to be characterized.”

Dr. Corey predicted that ssRNAs have the potential to be a major breakthrough.

“They combine the advantages of antisense oligonucleotides (e.g., simplicity of using one strand and the potential for good biodistribution) with the potency of duplex RNAs that function through the RNAi complex. Over the next five years we may see ssRNAs emerge as a competing strategy for clinical gene silencing that will challenge antisense oligonucleotides and duplex RNAs.”

The Corey Lab will continue collaborating with partners at Isis and the laboratory of Donald Cleveland, Ph.D., at the University of California, San Diego. “We hope these studies will lead to new RNAi-based therapeutic treatments for Huntington disease,” Dr. Corey said.

High-Content RNAi Screens

High-content screening for RNAi can provide a rich source of high-dimensional phenotypic data to explore the effects of knockdown in a variety of ways that move beyond simple threshold-based selection methods.

The process, however, is not without its challenges, such as the need for a scalable and robust data-management infrastructure and the problem of identifying a subset of biologically meaningful features from the raw, high-dimensional data.

“Extracting functional relationships from high-content RNAi screens definitely is a challenge,” noted Rajarshi Guha, Ph.D., informatics scientist, NIH Center for Translational Therapeutics.

“In the high-content environment, microscopy images of individual cells from each well treated with siRNAs must be evaluated. We use commercial siRNA libraries containing four different siRNAs per gene.

“The use of robotics integrated with image-analysis tools allows for the automated evaluation of various parameters. But manual inspection of the automated analysis is vital, to ensure that the results make sense in the context of the biology being studied.

Dr. Guha and colleagues have developed a framework for hit selection that employs a random forest classification model that can identify phenotypic changes such as cell number, size of their nuclei, cellular shape, and characterization of intracellular changes.

“The random forest method is a machine-learning algorithm, and is an extension of the decision tree method that asks a series of yes/no questions to label observations. The nice thing about decision trees and random forests is that they are somewhat interpretable, compared to many other methods that are black boxes.”

Dr. Guha explained that once phenotypic classifications are made, which are usually coarse-grained, the next step is fine tuning.

“We developed a series of tiered models in order to refine groups into finer populations, allowing us to apply gene ontology (GO) enrichment analysis methods to provide functional annotations and hence prioritize genes for follow-up analysis.”

The take-home message Dr. Guha delivered is that high-content RNAi screening provides datasets that are much richer compared to those obtained from reporter systems.

“It is also becoming increasingly important to characterize multiple phenotypic parameters rather than to focus only on one. Using machine-learning tools and high-content generated functional screens can lead to a much better understanding of the biology and associated phenotypic features produced by RNAi.”

Targeting Pathogens

Opportunistic bacterial and viral pathogens have evolved sophisticated mechanisms to subvert the human immune system. The majority of host proteins targeted by such pathogens remains poorly understood. RNAi represents a potent molecular tool for identifying host genes manipulated by such microbes.

Elizabeth Hong-Geller, Ph.D., staff scientist, bioscience division, Los Alamos National Laboratory, is performing studies to systematically identify host signaling pathways affected by Yersinia and other organisms.

“The Yersinia genus encodes three human pathogens, the worst of which is Y. pestis, the causative agent of bubonic plague. All members of this bacterial family attack the lymphoid system by injecting Yersinia outer proteins (Yop) into the cell cytoplasm. These proteins target multiple host signaling pathways and induce cell death. Mechanisms for this are not well characterized.”

Dr. Hong-Geller is working to decipher such mechanisms by utilizing RNAi. “In the last couple years, RNAi screens have begun to identify which of the host’s proteins are affected after infection. Our studies utilize a less virulent but related form of Yersinia called Y. enterocolitica.

“We initially infect mammalian cells with Yersinia and then use a commercial shRNA library to screen for NF-κB activity rescue. Yersinia infection normally downregulates NF-κB activity, which controls gene transcription involved in inflammation and is important to help clear the bacteria,” she continued.

“We monitor NF-κB expression using a high-throughput luminescent reporter assay system. After individual knock-down of ~750 kinases or kinase-related genes, we identified 19 genes needed to suppress NF-κB activity. We also identified two genes that restored the viability of infected cells.”

Dr. Hong-Geller also validated her results by taking the hits and double-checking them with siRNA constructs and stable shRNA cell lines. Additionally, they decided to assess available small molecule kinase inhibitors.

“We wanted to know which, if any, of these inhibitors might rescue NF-κB activation in infected cells. We were pleased to determine that in a subset of targeted genes, we could effectively rescue this activity.

“Our goals now are to extend these findings by delving into the basic mechanistic biology represented by this data. We will determine if the RNAi screen hits represent direct or indirect interactions between the pathogen and host.”

These studies may help elucidate the pathogenic mechanisms of Yersinia and related pathogens. “Our hope is that this information may serve as the basis for the design of new inhibitors for broad-spectrum host-derived therapeutics.”

RNA interference methodology was used to identify host genes that are targeted by Yersinia enterocolitica during infection. Researchers screen for hits that induce derepression of Yersinia-mediated inhibition of NF-kB gene expression in 96-well plate format. Candidate hits are potential targets for novel host-derived therapies against infectious disease.

Lipid Nanoparticles Delivery

Successful delivery of the payload is a key aspect for the successful use of RNAi therapeutics. Tekmira Pharmaceuticals utilizes lipid nanoparticles (LNPs) as a delivery technology platform. The uniformly constructed LNPs encapsulate their target-specific double-stranded siRNA molecules or other nucleic acids.

“Nucleic acids are relatively large in size and unstable in the blood compartment,” explained Ian MacLachlan, Ph.D., evp and CSO. “They do not readily diffuse across the membranes of target cells, and thus need an effective delivery vehicle.

“Our LNP technology protects the nucleic acid payload and allows us to control the circulation time in blood. Since it is a modular platform technology, there are literally thousands of lipid combinations and lipid or lipid:nucleic acid ratios that can be customized for specific delivery applications.”

According to Dr. MacLachlan, the field is tackling these challenges and making headway.

“As we continue developing formulations that are increasingly clinically validated for increased potency and reduced toxicity, we are acquiring new understandings of how to improve the therapeutic index of these drugs.

“Recent research has provided important information about the structural basis for the chemical toxicities associated with high doses of lipid excipients and the nucleic acids themselves. Further, we are beginning to unravel how immune toxicities can manifest through unwanted engagement of either the innate or adaptive immune systems, and how these can be avoided.”

Tekmira’s LNP siRNA delivery platform (known as SNALP) has confirmed RNAi-mediated efficacy in several preclinical models including oncology and infectious and metabolic diseases. Aside from systemic delivery, the company also has made progress in nebulization-mediated delivery of siRNA into the respiratory tract.

“One recent example of progress is that we have received approval from the FDA to initiate Phase I clinical trials with our Ebola therapeutic, TKM-Ebola. This disease and those caused by other hemorrhagic fever viruses have no approved treatments.

“Our preclinical studies demonstrated that the Ebola therapeutic provided 100% protection from an otherwise fatal infection with Zaire Ebola virus in nonhuman primates.”

Dr. MacLachlan said he is pleased with how the field is progressing. “This is an incredibly exciting time. Tekmira expects that six or seven of our and partner Alnylam’s LNP-based products will have entered the clinic by the end of 2012. A few years ago, we would have said that we couldn’t be sure if RNAi would ever translate into therapeutics. But now, especially with the use of siRNAs, we are close to achieving that goal.

“The last few years have seen us improve our understanding on a number of fronts such as development of more potent siRNA and lipid chemistries, advantageous sequence design, and controlling responses of the immune system. At the same time we are seeing the LNP approach validated in the clinic. All of this has increased my confidence that RNAi therapeutics are on the horizon.”

Tekmira utilizes lipid nanoparticles (LNPs) in its delivery platform known as SNALP. The LNPs encapsulate their target-specific double-stranded siRNA molecules or other nucleic acids.

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