RNAi Therapeutics: Qiagen High-Throughput RNAi User Meeting San Francisco (Part 1 of 2)

An army of RNAi enthusiasts descended today onto the UCSF Mission Bay Campus in San Francisco, just across the street from Sirna Therapeutics/Merck, to discuss the latest in the use of RNAi for high-throughput screening. Illustrating the ever increasing popularity of RNAi, 175 scientists registered for this year’s one-day meeting, some from as far as Japan, compared to 75 when it was held for the first time two years ago in Boston. It was therefore fitting that a number of presenters noted as an aside that the discovery of RNAi and microRNAs not only transformed molecular biology, but also a number of lab personnel from bench-weary scientists to those that live and breathe RNAi every day. In the next two posts, I will try and highlight a few points from the meeting seen through my RNAi Therapeutics filter.

Carl Novina (Harvard and scientific advisor to mdRNA/Nastech) gave the keynote address with an introduction to microRNAs and their molecular mechanism of action. In a paper earlier this year, his lab had developed a biochemical model system to study microRNA repression that led them to conclude that microRNAs repress translation through the inhibition of the joining of the large 60S ribosomal subunit to the mRNA-bound 40S subunit of the protein translation apparatus. In today’s presentation, he expanded on that work by describing an RNAi-based screen for the discovery of genes involved in microRNA function. For this, his lab created luciferase cell lines in which one of the reporters contained a target site for an endogenously expressed microRNA and was therefore repressed. Knocking down a gene contributing to microRNA-mediated repression should therefore lead to an increase in the signal intensity from that reporter gene.

Encouragingly and attesting to the high specificity of RNAi, the screen uncovered many of the known microRNA pathway components such as Drosha, Dicer, and Argonautes 1 and 2. In addition, the screen making use of an siRNA library targeting the “druggable genome”, that is the ~7000 genes in our genome encoding for kinases, cell surface receptors etc. that are amenable to small molecule and/or monoclonal antibody inhibition, uncovered a number of proteasomal components. This raises the intriguing question whether an old hypothesis, namely that microRNAs may induce co-translational protein degradation may indeed be part of the complicated reality of the molecular microRNA repression process.

As an aside, Carl Novina noted that one problem with working on RNAi-related aspects in Boston is the considerable demand for talent there by the many RNAi companies located there. A nice problem to have for the many hungry post-docs at a time when public funding for basic research has stalled to pay for apparently more important projects overseas.

One recurrent theme of the conference was the role of small RNAs in the new era of personalized medicine, particularly for cancer, which not coincidentally also was the loud message heard from last week’s ASCO mega meeting. The case was made by Lynne Bemis (University of Colorado) as she compared the costs of today’s monoclonal antibody cancer therapeutics that run at about $30k per annum with clinical responses in only a subset of patients. To avoid patients wasting precious time on ineffective therapies and also to reduce healthcare costs, it is therefore important that these treatments are accompanied by diagnostics that can predict the response of a patient to the therapy, by the way an area first pioneered by the local Genentech.

The striking conclusion from her research was that microRNAs were by far emerged the best biomarkers for this purpose, far better than single protein or mRNA diagnostics. When compared to proteins this is likely due to the fact that microRNAs function as master regulators, often with direct and critical functions in cancer itself, while a single protein may only reflect a much smaller aspect of a much larger picture. When compared to mRNAs, it is the relatively high stability in most tissue preservation methods and their compatibility with formalin fixation that adds to the competitive advantage of microRNA diagnostics.

As an example, EGFR tyrosine kinase inhibitors (TKI) are now widely used for cancer therapy, yet only 10% respond to treatment. Lynne’s team therefore looked at whether EGFR protein levels, EGFR mutations, or genomic amplification levels of the EGFR gene would be good predictors of drug response. Unfortunately, all of them either failed to do so (EGFR levels) or were not practical (EGFR mutations). Running out of options, they then turned to microRNAs. First they made use of microRNA target prediction software to discover two microRNAs that might target the EGF receptor mRNA. They then hypothesized that in cancers where EGFR had been aberrantly activated one of these microRNAs was lost. As an interesting technical aspect, unlike most other microRNA diagnostics currently being developed by Asuragen, Rosetta Genomics, Exiqon and others, they did not make use of qRT-PCR or microRNA microarray for the detection of microRNA expression levels, but the even simpler pPCR from DNA isolated from tumor tissue microdissected from formalin-fixed samples.

Amazingly, from a sample of 60 tumors of the lung, the miR-128b gene dosage was able to nicely segregate those patients that responded to TKI treatment versus those that did not. None of the other methods tested came anywhere close. As, if not even more spectacularly, it turns out that miR-128b is located on a region of the short arm of chromosome 3 that had been previously implicated and was frequently deleted in lung cancer (around 90% of late-stage lung cancers), but of which the identity of the underlying gene had long been a mystery.

In another elegant study, her group employed mRNA microarray analysis to look for genes either over- or under-expressed in a panel of cancer cell lines. Once identified, microRNA target prediction was used to come up with potential clusters of genes being targeted by the same microRNA. Demonstrating yet another promising method of discovering microRNA diagnostic candidates, 5 out of the top 7 overexpressed genes shared a common microRNA signature, and sure enough, this microRNA alone was more predictive of drug responsiveness than any of the proteins alone.

Eric Lader from the host Qiagen rounded up the session on microRNAs with an overview of products for the quantitation and inhibition of microRNAs sold by Qiagen. Qiagen’s qRT-PCR quantitation method allows for the one-step conversion of all microRNAs into cDNA so that many individual microRNAs can be measured from this one cDNA sample thereby reducing the use of precious clinical material. As to the microRNA inhibition technology, a number of nucleotide modifications were tested in the antagomirs and it was interesting that while a number of them were able to inhibit microRNA function, depending on the modification, they probably did so at various steps of microRNA biogenesis and function and included both microRNA degradation and competitive binding. LNAs and other chemistries with high melting temperature generally worked best while RNase H-dependent antisense did not appear to be an effective microRNA inhibition technology.

In my next post, I will summarize the rest of the meeting including more RNAi screens, cancer, and systems biology. Stay tuned…