SA: What about the molecular biology knowledge?
It's going to take a lot of biological knowledge. For example, let's suppose that every structural gene has at least one cis site that regulates it. Then there's 100,000 cis sites. Nobody knows if that's true, but let's pose that. Well, we have an awful lot of work to do to pull out all the cis sites. Now let's suppose that 5 percent of the structural genes that are around act as regulatory inputs to the structural genes. So there's on the order of 4,000 to 5,000 trans factors making up this vast network that we're talking about.
Well, we have to discover what those trans factors are; we have to discover what the cis sites are; we have to discover what the regulatory logic is. Then we have to make mathematical models of it. Then we have to integrate the behavior of those mathematical models. And then we're going to run into the same problems that people have looking at the gut ganglion in lobster -- that even though you know all the inputs, figuring out the behavior is going to be hard. Then we're going to run into the problem that people have looking at the gut ganglion in lobster -- that even though you know all the inputs, figuring out the behavior is going to be hard. Then we're going to run into the problem that you're looking at a circuitry with 40 genes in it, but there are impacts coming in from other genes in the 100,000-gene network that are going to screw up your models. So, this ain¿t going to be easy.
SA: In terms of a timeline, are we looking at one year or 200 years away?
I think 30 to 40 years from now we will have solved major chunks of this. The tools will mature in the next 10 to 12 years, and then we'll really start making progress.
SA: What do you define as progress?
That we will be getting the circuitry for big chunks of the genome and actually understanding how it works. Getting to the genomic sequences is wonderful, but what does it tell you about the circuitry? So far, nothing -- except who the players are.
SA: So we're at the beginning?
We're at the very beginning of postgenomic medicine. But the payoff is going to be enormous. There's going to be a day 30 years from now where somebody comes in with cancer and we diagnosis it with accuracy not just on the morphology of the cancer cell but by looking at the detailed patterns of gene expression and cis site binding activities in that cell. And we know the circuitry and the autocrine perturbations to try, or we know which gene activity perturbations to try that will cause that cell to differentiate into a normal cell type or cause that cell to commit hara-kiri.
SA: Will that be someone walking into their doctor's office, the doctor turning on the computer and just entering the data?
It will require being able to do the RNA sample. Biotech companies together with big pharma, which alone has the money to get things through clinical trials, will wind up proving that you can treat cancer this way -- or treating some degenerative disease of your joint, for example, where we regenerate the synovium. Why not? We can make an entire sheep -- why can't we regenerate the synovium?