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TGen s Spyro Mousses on Using RNAi to Advance Cancer Drug Research

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At A Glance

Name: Spyro Mousses

Position: Director, Cancer Drug Development Laboratory, Translational Genomics Research Institute

Background: Staff scientist, National Human Genome Research Institute — 2002; Senior research fellow, NHGRI — 2001-2002; Postdoc, NHGRI — 1998-2001; PhD, cancer genetics, University of Toronto — 1998; MS, cancer genetics, University of Toronto — 1994; BS, pharmacology/toxicology, University of Toronto — 1991

Having worked closely with Natasha Caplen at the National Institutes of Health, Spyro Mousses’ involvement with RNA interference is not surprising. Now at TGen, he has continued to incorporate the gene-silencing technology into his work, and recently took time to speak with RNAi News about it.

Could you give an overview of what you do at TGen?

TGen is a biomedical research institute. We’re a not-for-profit organization based in Phoenix, Arizona. [I work at] a satellite operation of TGen’s in Gaithersburg, Maryland, that is focused on cancer-drugs — in fact, it’s called the Cancer Drug Development Lab. Our goal is to develop and apply high-throughput biology to both discover new drug targets for oncology as well as perform pharmacogenomics and other basic research that will accelerate the discovery of new drugs and improve the development of existing cancer treatments.

How did you start getting involved with RNA interference?

We started working with RNA interference very early, when siRNAs were discovered. It began with a collaboration with Natasha Caplen, who published one of the two seminal papers on siRNAs when they were discovered. We began by making siRNA against known therapeutic targets in cancer but quickly started to think about using the power of this technology for high-throughput screening. Towards this end, we started to develop miniaturized platforms — one of the first things we collaborated on was the high-throughput RNAi microarray platform, which was published awhile back in Genome Research. This work was largely started when I was working as a staff scientist at the Olli Kallioniemi’s section at the NIH.

[Another RNAi project] we started working on was an entire library of siRNA targeting genes. That was when Natasha and I were both at the National Human Genome Research Institute at the NIH. Two years ago, Jeffrey Trent, president of TGEN, and I decided to set up a multidisciplinary team at TGen armed with a completely new strategy to integrate global RNAi phenotype profiling into a comprehensive cancer drug-discovery and -development program. So over the last few years we’ve put much effort in the development of RNAi expertise, the design and generation of large siRNA library resources, high-throughput screening infrastructure, and assay development — to support high-throughput RNAi based strategies for evaluating vulnerable drug targets and discovery of genes that are functionally and causally involved in drug response.

Can you talk about the work on therapeutic siRNAs? Is that something you’re still working on?

Although our focus will be on integration of global RNAi profiling into a different kind of drug-discovery and -development strategy, many of the siRNAs with anticancer properties that come out of the high-throughput screening are also considered as candidate therapeutic agents. We are now forming a collaboration with Intradigm to validate some our potentially therapeutic siRNAs in vivo. We’re are also working with a very experienced clinical development group in Phoenix, headed by Dan Von Hoff and others, who have an interest in bringing the most promising siRNAs agents to the clinic.

Although we are excited about our ability to bring siRNA discoveries from bench to bedside, we feel that our greatest strength right now is our ability to effectively integrate high-throughput RNAi into multiple aspects of cancer drug discovery and development.

Can you talk a little bit about that?

There’re a variety of projects going on in the lab; the underlying theme is multi-dimensional RNAi phenotype analysis across multiple cell systems, under different treatments and conditions, and using various endpoints — cellular, phenotypic, and molecular endpoints — focusing largely on things that have anti-cancer properties or regulate drug response. For example, we use an MPT-type assay to define genes that are essential for the growth of cancer cells. We screen multiple cell lines in parallel and then ask questions about selectivity — what would be an essential gene for one cell line and not another? Then, [we] integrate that [information] with gene-expression and gene-copy number to gain some understanding as to where the source of vulnerability comes from by integration of the -omics data.

The other approach that we’re taking is a synthetic lethal-type one, where we have isogenic cell-line pairs; these screens typically utilize cell lines that are identical in every way except they would vary, for example, in the status of a tumor-suppressor gene. We have through a collaboration with Haiyong Han and Dan Von Hoff, a cell line pair that is isogenic and differs only in smad4/DPC4 expression — so we have a natural deletion of smad4/DPC4 versus a cell line where smad4/DPC4 expression has been restored, we screen both cell lines in parallel with 10,000 siRNAs, and ask the question: Is there a knockdown that will selectively and preferentially kill the cell with the natural deletion? We’re starting with a pancreatic cancer cell line, where we know that half of pancreatic cancer patients will have the deletion of smad4/DPC4, and therefore we aim to identify new targets that are going to be effective at killing cancer cells with deletions in their tumor but not normal cells that have normal smad4/DPC4 function.

The third thing that we do is chemotherapy-sensitization screening, where we screen a particular cell line and then add a very low concentration of a drug and measure the resulting phenotype. By comparing a vehicle control versus a very low concentration [of chemotherapy], we’re looking for knockdown events that will increase the sensitivity of cancer cells to a particular drug.

There’re three utilities that come out of that type of screening: The genes we identify are functionally modulating the cellular response to the drug, so they’re important because they can give insights into mechanism of action.

[The genes] can also give us a starting point for combination chemotherapy — for example, we have an NIH-funded study [to investigate] sensitizers to doxorubicin in breast cancer. We’ve identified a number of targets that, when knocked down, sensitize breast cancer cells to doxorubicin. Those would be a great starting point for combination chemotherapy to boost the effect of doxorubicin in patients that are not responding well to doxorubicin chemotherapy.

The third utility for these knockdowns that modulate drug responses is that they are functionally relevant candidates for predictors of drug response. For example, if an RNAi knockdown of expression increases sensitivity to a particular chemotherapeutic, then we want to also test the hypothesis that the state of that gene (low expression, inactivating mutations/deletions) may be a predictor for positive response in the clinic. We have found gene silencing events that are very chemo selective in the drugs that they will sensitize cells to. That, of course, is very useful when you’re designing clinical trials and you want to identify patients that are going to fail to respond to one drug, but benefit from another drug.

Both the combination chemotherapy plus the predictive markers are tools that result from this type of analysis that can be used to help in the development of emerging and existing chemotherapeutic agents.

When you think about these targets … do you envision these resulting in an RNAi drug?

I think it depends. For the most part, our screens focus on druggable-tractable gene products. If I could take a step back, I didn’t mention the libraries we have for screening. Our biggest library right now is the druggable genome from Qiagen. It represents 5,000 druggable targets. We have two siRNAs for each of those 5,000 targets, 10,000 siRNA, so we’re really starting with genes that are tractable targets [for small-molecule drugs].

Our preference is, of course, small molecule agents. In some cases where we have discovered new vulnerable gene targets, there are already known inhibitors against those targets. In some cases, we focus on receptors where we can make monoclonal antibodies or other biologicals. If there are no possibilities for the development of a small molecule or biological, we also would consider siRNAs as a therapeutic in their own right.

Again, our priority is fastest route to the clinic, and that means putting priority on more established types of agents. SiRNAs as therapeutic agents is something that many groups, including ours, consider the new frontier for future therapeutic agents.

Where are these programs in development? How far along are you?

We have products at various stages of discovery and development. Most of the work so far in the program was in establishing the resources, expertise and infrastructure for high-throughput RNAi screening. We see this as a long-term effort where we plan to do this multi-dimensionally and compare hundreds of screens at the 10,000 siRNA level [in order to] create a knowledge base of multi-dimensional phenotype data — the more data we put into it the more valuable and useful it is.

But we also have programs to advance individual biomarkers, as well as individual drug targets and inhibitors with anticancer properties, individually. We’re at the stage now where we’ve validated several genes that can sensitize to chemotherapy, as well as identified several synthetic-lethal targets that we’re going to be publishing soon. Those are going to be advanced into preclinical development.

Are you guys doing this in collaboration with any pharmaceutical company?

We’re working very closely with industry. There’re a large number of pharmaceutical companies that have come to us for contract research to apply high-throughput RNAi to help in the development of their drugs by identifying functionally relevant genes that modulate the response of their particular drugs.

I can’t mention any [companies] by name, but we have contracts already to do that type of service.

I should mention that we do contract research not only for pharmaceutical companies but for academia and the federal government, [and] we do offer services utilizing our RNAi expertise to make focused siRNA libraries. There is already a press release on that [kind of work] with the NIH — we’re doing that [as a subcontract managed by Icoria] for the NIEHS (see RNAi News, 11/192004).

We were commissioned to design and validate siRNA library of [toxicology] genes. These are genes that are relevant to toxicology or are otherwise relevant to environmental response. Then NIEHS has an interest in developing information about effective siRNAs, and validating them to support and enable the research community to fully utilize the power of RNAi to investigate environmental genes and the role they play in disease.

How long does it take to put together this kind of library?

It varies. The library we’re putting together for the NIEHS is going to be validated and we’re designing four siRNAs per gene. We’re going to functionally test each one to see if it’s effective or not. We also design libraries that are non-validated with fewer siRNA that are faster to make.

We’re working very closely with Qiagen, and Qiagen has a number of unique algorithms for selecting siRNAs that are going to be maximally effective and have minimal off-target effects.

Is there anything we may have missed on the RNAi front? You’re doing a lot.

The only other thing is that I mentioned the libraries, and we have several collaborations — one with Qiagen, of course, with the 10,000 siRNAs, plus a cancer set of 139 genes. We also have a collaboration with Open Biosystems for shRNA libraries, and Origene for libraries of full length genes in expression vectors.

There are many company collaborations that make our work possible: For example, [GE Healthcare] is collaborating with us in applying their In-Cell Analyzer, to high-throughput RNAi, and we’re doing a lot of things with their instrument; In addition to looking at the MPT-type assays that I mentioned, we looking at more sophisticated high-content analysis endpoints. So we’re using the In-Cell Analyzer 1000 to read out, in a high-content way, the effective siRNA knockdowns at a cellular level. That takes the endpoints to another level.

The other thing is [with] the platforms for screening we’re doing things in a 384-well format using robotics. David Evans who is the head of drug discovery in our group has built a fully automated robotic system for high-throughout transfection. It integrates the In-Cell Analyzer plus a lot of the other plate readers and automated incubators and liquid handling stations, etc, so we’ve been able to automate high-throughput siRNA transfection.

The other thing we’re doing is developing new technologies to do this on a glass slide — these are RNAi microarrays. We think this is really the future of high-throughout RNAi screening, but the technology is still in its infancy. We’re developing it further — it’s probably another year or so away from being a standardized technology that can be used for high-throughput RNAi screening, but it will seriously accelerate the whole process.

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