Dr. Peter Laird discusses the changing face of cancer and how epigenetics is playing a role.
So we used to think cancer was primarily a genetic based disease, and in the past few years, and even the past decade we’ve learned that epigenetics also plays a really important role.
When I started my career the biologist and the experimentalist was really the person who was in complete control of the experiment. They designed the experiment and they preformed the experiments, interpreted the data, analyzed it and wrote it up, and were first author. And what I’ve seen over the course of my career with these high-throughput technologies now being responsible for or able to generate huge volumes of data at reasonable cost. The experimentalist is less important on many large scale studies then they used to be and the person that has the skill sets in data analysis, computation, and programming are becoming really key to a lot of these large scale studies.
So we’ve made tremendous technical advances in the past decade in epigenetics we were nowhere near a decade ago. And now we’re full-fledged partners in genomic characterizations and the human epigenome project, the cancer genome atlas, and a variety of different consortium; the International Human Epigenome Consortium. So we’ve made tremendous technical advances, but we’re not finished.
We need to be able to process for large numbers of samples; if you look at the various technologies that are available right now on the commercial landscape and in private protocols, you can see that some techniques really excel at large numbers of samples, others really excel at covering the entire epigenome; whether it’s the methylome or histone modifications or other aspects of the epigenome, but we don’t have technologies that allow us to do thousands of samples at the very highest resolution.
The other area that we really need increased technological investment and development is to go smaller, to go to single cells. And the reason for that is, if you look at a human body… 10 to 13, 14 cells, something like that, for the most part they all have exactly the same genome. So it doesn’t really matter which one you grab, you can look at the genome and understand it and you know the genetic composition of that person. Everyone of those cells though has its own unique epigenome, and when we take a tissue sample, a tumor sample for example, and grind it up and analyze it for DNA methylation profiles we are really looking at a mixture of millions of cells, some of which have vastly diverse epigenome; so what we really need is the ability to go in and look at individual single cells and characterize the whole epigenome.
So epigenetics offers a tremendous opportunity for clinical diagnostics in several different respects, one is the subtype classification, and designing panels that identify specific subtypes of disease. Another is to do a more supervised approach where you have a drug in mind and you look specifically at whether particular epigenetic profiles respond better to a certain drug or not; and that work is ongoing. And the third is in diagnostics is really sensitive detection, so detecting disease in biopsies, in blood samples, or urine samples; the presence of disease in the body by looking at abnormal DNA methylation in bodily fluids or biopsies. And that is also very much an active area of research there are clinical products on the market that are designed to detect cancer and it doesn’t just have to be for population based screening, you can also imagine that this would be useful for monitoring disease after the surgeon has resected the tumor. To see whether or not you can catch recurrence at an earlier time-point and then switch drugs that the patient may be on or provide an additional surgical, other or radiation or chemotherapeutic intervention.
So as I said, there is really a wealth of opportunity there for epigenomics and epigenomic profiling and we’re just really in the infancy of whole scale profiling of epigenomic changes both DNA methylation, as well as histone modifications, nucleosome positioning, non-coding RNAs; and the next few years promise to be very exciting.