At A Glance
- Ramaswamy Narayanan
- Professor, Department of Biological Sciences, Florida Atlantic University; President and CEO, Forseti Biosciences.
- PhD, National University of Ireland, Dublin.
Ramaswamy Narayanan spent 10 years as a researcher at Roche before joining the Florida Atlantic University faculty in 1998. Four and a half years later, he has no doubts about his decision. Other than living in snow-free south Flor- ida, Narayanan is making research discoveries using microarrays, establishing a new academic curriculum and helping create a biotechnology industry that he hopes will stand alongside tourism as a pillar of Florida’s economy — as well as creating a company that will benefit his employer.
In December, Florida Atlantic announced that Narayanan’s research team had isolated two genes, CCRG and C15, involved in early stages of cancer of the colon, pancreas, and prostate. The finding was reported in the December issue of Anticancer Research.
Narayanan will also head the company that is licensing the genes, Forseti Biosciences (http://forsetibiosciences.com), the university’s first biotechnology spinoff. He also maintains one of three Affymetrix GeneChip systems in the state of Florida.
What made you decide to leave private industry?
After 10 years, I felt that I could better serve ind-ustry needs in academia than by being part of a major pharmaceutical [company]. I saw many academics coming through our facilities at Roche and I thought I could help bridge the gap by coming back to academia, putting in a corporate-type infrastructure, educating people about intellectual property and the ethical and moral aspects. I want to try to bring the university closer to an industrial structure. I followed Herbert Weissbach, who was director of Roche Institute, here when he established the Center for Molecular Biology and Biotechnology. Florida Atlantic had been a teaching type institution and they wanted to see some concrete work in genomics and biotechnology.
Did you have a research project in mind when you moved there?
I have always been a cancer researcher and my focus is on solid tumors. My operating philosophy is genes to drugs. My research efforts here revolved on bioinformatics, using whatever is publicly available on databases, to discover cancer genes. Also, from day one, we established a large patient tissue repository from local hospitals, and [enabled] access to well-characterized tissue material with clinical type information on therapy, stages, and treatment. We have a tissue repository with 800 samples from breast colon, lung, pancreatic, and prostate cancers and a large collection of matched normal tissue that goes with it, as well as clinical information and treatment. Some of the patients are still alive, so we can monitor expression in response to treatment. We also have 2,000 paraffin sections of some of these tumors for immunohistochemical (IHC) analysis.
We have discovered one gene, with a high degree of specificity to colon cancer, that is not present in many organs. The university has applied for a patent on it. And, we have found another gene, connected with Down syndrome and we have been able to show an association of this gene with three major solid tumors and with validated expression specificity. We have developed an antisense drug to establish functionality. The drug shows efficacy in pre clinical models and provides a proof-of-concept for the drug therapy use of the gene.
How are you using microarrays?
We have established Affymetrix GeneChip instrumentation in my laboratory. It got funded through federal money that was created to bring biotechnology to southeast Florida. We are using it to create a core facility for internal and external people. My laboratory uses Affymetrix in understanding pathways for drugs, how they work, [as well as] other targets they affect in cell culture in preclinical type models. We are creating a pharmacogenomics database from cancer patients being treated, looking at different stages of cancer. The microarrays [have] a potential to come up with additional targets, other than these two targets. But the most important use is in the understanding the mechanism of the drugs, the biological effects of the drug, and establishing a drug fingerprint.
We want to ask a question: What does the gene activate, the mechanism and pathways, why does this gene have the potential to be a therapeutic? We can also eliminate a lot of other genes, which are non-specifically affected by the drug. We have used 350 chips in a year and a half.
We were using GeneChip because it was whatever we had on hand. I’m not getting into comparisons of one technology against another. The instrumentation was here as part of a special grant from a federal appro priation from the Human Resources Administration.
What are you using for data analysis?
We are using basically Affymetrix software with their statistical information and replication. It’s an evol ving process, we are still learning how to handle the information. I spend a lot more time in designing the experiment. Having listened to a lot of people, there is one thing that is clear: You just don’t stick in an RNA sample and come out with information at the other end. We have a large number of outputs; there have to be multiple appropriate filters with an extensive understanding of biological questions that have to be asked, as well as chip replication and biological replication. We are learning the nitty gritty aspects. Any of us can come up with lots of data. What to do with that — To say: that this is our target of interest from thousands of genes — that is an uncharted territory.
How many people do you have working for you?
We have one PhD student, two master’s students and several temporary students and post docs and guest workers. Funding at this point is internal. Because of the potential intellectual property issues, we didn’t apply for Federal grants: We are funded by the FAU Foundation, Florida Atlantic University Research Corporation and philanthropic organizations, and from people who have seen my work, but mainly, it’s internal. We are now moving the discoveries to commercialization, creating the first company from the university. The university is an equity holder in the company. We are going to try to raise funds through private placement. We will move outside the university, but right now, we are using the university infrastructure to continue. We are going to try to raise $12 million to make one antisense drug.
How are your financing efforts going?
We are writing the private placement memorandum as of today. We will start the offering on Monday, talking to local investors, accredited investors — angels and individuals of high net worth. We have considerable interest, but I will believe it when I see it. We want funding that will enable us to move to clinical trial[s]. We think that by focusing on pancreatic cancer, the project can go for accelerated approval, since there is no treatment for something with [a] 100 percent mortality rate [like this cancer].
How do you feel about your progress?
I am very excited at the finds, the technology. But, better ask me a year from now. What I feel good about is that I’m helping the next generation of students get into biotechnology. Florida doesn’t have [a lot of] biotechnology offerings. We have set up an online class that anyone can take once they have registered. Maybe in 10 years, Florida will not just be a tourist attraction. Biotechnology is the future and the state government feels that is the way to go. I didn’t come from Roche to start a company, but I think we can set this up as a model of how to do all of these things while being a faculty member: How one can maintain a professorial position and also wear an entrepreneurial type of hat.
What do you see in the future for microarrays?
Proteomics is the next dimension. The ultimate molecule is the protein. The next dimension has to revolve around proteomics. The gene chip must be brought closer to the patient. We are not trying to do research for the fun of it. We have to give back to the patient.
We need to learn how to interpret microarray results. I try to train my my students and I find that there is not a hell of a lot of information available, and what you find, well, one thing is opposite to another.
This technology is very expensive to many people and the question comes up whether it is better to do 15 experiments or just two. I think I would rather do two really good experiments, rather than 15. The proof of the pudding is that the targets really mean something.
What do you do with your databases?
For us, by defining a lot of filters and understanding the biological system, the chip output gets reduced tremendously. By using bioinformatics and statistical interpretation as controls, and using cell culture and patient-derived materials, understanding the targets, and introducing filters to eliminate noise, we deal with tens of genes as an output instead of hundreds and thousands of genes as an output. That’s where we need more help and that’s where I focus on the biology. It may be possible to totally rely on the computation, but we don’t have enough software to accomplish [that]. Until that happens, I want to understand the biology. Maybe in a few years, someone, without knowing anything about the biology, will be doing clustering and make gene-to-gene links.