Next generation sequencing is here to stay. Now how do we use it?
Next generation sequencing (NGS) is now a ‘must have’ for anyone looking to get funding. But this was not always the case. David Smith was one of the technology’s early adopters and greatest advocates. Now that the technology is opening up new possibilities, David considers what it means for institutions like the Mayo Clinic and healthcare in general.
The genomic revolution is one driven by technology. Although next generation sequencing technology is almost common place now, that was not always the case. Its spread would not have happened without early adopters and advocates. David Smith is one of those early adaptors and advocates of NGS technology, and currently chairs the Technology Assessment Committee for the Center for Individualized Medicine at the Mayo Clinic. He uses genomic technologies in his research to understand the molecular alterations that underlie cancer development.
David kindly took some time during his last trip to London to discuss where he feels some of the biggest challenges for genomics, as a growing field, are today.
FLG: What do we need to be talking about, when we speak about the future of genomics?
DS: Think about the time in the not too distant future, where everyone has their genome in their pocket and how that’s going to change healthcare. Who’s going to be in charge of the information, and how will it change medicine when it’s not just diagnostic tests but can I just ‘scan your iPhone’? The problem is, that the area is so broad and ill-defined, that no one really knows how we’re going to get from here to there. It’s kind of scary for a doctor. The sort of testing that they’re doing now, in 5 years it will be gone. If you’re a patient, you’re not going to need to go to a doctor for the sorts of tests that are currently being used in clinical practice. You’re going to have to go to a bioinformatician, to make sense of your sequence in the context of your symptoms.
FLG: Where does Mayo Clinic fit in?
DS: Our motto is “the needs of the patient come first”. But no one really has a good vision on where genomics will go. I don’t think anybody does. Genomics is going to change every aspect of medicine. You can see it on a small scale already. In the past there was considerable need for cytogeneticists to analyse chromosomes. Already that is being replaced by array comparative
genomic hybridization and very quickly that will be replaced by some type of whole genome sequencing. What we really need are bioinformaticians and data storage. Two of the biggest problems in this whole field right now are analysis and storage. Right now no-one really has a clue.
FLG: How do we get from where we are now, to genomics on a nationwide scale?
DS: There are two different issues: what happens in the large centres and then what happens in the regional hospitals? The large centres aren’t so problematic. However, a regional hospital can’t have the infrastructure that say somewhere like the Mayo Clinic has. So we have to look at the model that works best for the populous rather than the bigger centres. Most places can’t afford the infrastructure, so they need a model which gives them the best provider so that they can send stuff out to get analysed and get it back in a form that’s digestible. You can’t get back an encyclopaedia of alterations; you just want something that tells you which drug to give the patient.
FLG: Is there a negative pressure on healthcare?
DS: I don’t know if it’s negative, but if you can’t predict the future it’s kind of scary. Medicine was much more comfortable when whatever you learned at medical school worked for your whole career. This is going to change everything. Mayo’s still going to be around, because we have the best doctors and diagnosticians and infrastructure for excellent clinical practice, but they’re going to have to evolve practically because they’re going to have a new set of tools. People are still going to travel to get the best treatment. Big centres are still going to do what they’re going to do. But it’s the smaller centres that treat the majority of the patients that are going to need help.
FLG: Where is a good place to start making an impact?
DS: Education. Make more people aware of the revolution that’s occurring. And out of that comes contacts, people getting to meet each other. Getting people together that normally wouldn’t meet each other at all. Most academics tend not to interact with the business world, but if you can get these people understanding each other, just think of some of the potential for innovation and spin-offs. It’s all about finding a sweet spot! But it’s really broad right now. A lot of people are trying to focus in. However, even just looking at NGS for cancer, or drug development, or companion diagnostics, are still really broad.
FLG: Where is your focus on at the moment?
DS: I’ve focused on next gen sequencing. It’s going to be a diagnostic for the cancers I research, and most cancers actually. So now we need to figure out how we get it across to doctors so they know that it’s cheaper and more informative. But of course it has a lot of challenges, which are again, analysis and storage. You get comprehensive information, but how much are you supposed to tell the patient? That’s a huge problem. But it does also change the paradigm. There are now discussions now across the board in genetics to train a whole new group of people. Because even genetic counsellors now don’t have the tools to deal with this. So what will this new group look like? Bioinformaticians don’t understand the biology or the clinic; so do we need a new type of person with both types of expertise, or a new system where they all work together somehow?
FLG: Where do you think the big breakthrough is going to come from?
DS: I see a lot of meetings in the United States. But it’s interesting to see Europe. There’s a dramatic difference between the United States and Europe. The UK may not have as much money, but you’re smaller and more nimble. I’ve seen a lot of efforts from small places in Europe where they’ve been able to turn on a dime. But I don’t think anyone is really prepared. It’s going to shock a lot of people. But the good news is, these tools are extremely powerful and are going to start being used. The key is to look for the low hanging fruit. The lowest hanging fruit is Cancer. We waste hundreds of thousands of dollars on treatments and cures that only work on 10% of the people. So if we can work on that and optimise that, it’s a great place to start.
FLG: How have you seen the field change over the past few years?
DS: Next Gen Sequencing isn’t just in cancer, it’s everywhere. 5-10 years ago, when i was talking about this, people didn’t believe me. So it’s nice to be proved right about something! But there are still problems, and no one has any clue how to integrate data. It’s not just whole genome sequencing. It’s RNA seq, methylation sequencing, and how do you put all of that information together? I haven’t seen anybody in the whole world who knows how to do that. Integrating data is a key topic right now. At the moment, we’re definitely in the educational stage. When I went to the first Illumina User’s meeting 4 or 5 years ago it was Washington University and the big sequencing units that were doing it, and attending those types of meetings. Now everyone from everywhere is starting to get involved in this technology and attend these meetings. In basic research, for example, if you write a grant and you don’t have next gen sequencing in there, you’re not competitive.
FLG: Is increased involvement from a major player in the data business, like Google, an encouraging sign?
DS: We need more investment in data analysis, so having Google and IBM starting to think about it is a good thing. We need more help. A lot more help. The current NIH funding model is abysmal. If we can get Bill Gates or some of those guys’ interests it’d help a lot. So having Google involved is a big plus.
FLG: How far can you go with that level of mathematics and computer science without the domain science to support it? That’s one of the criticisms around Bioinformatics at the moment.
DS: It’s one of the biggest problems. They’re so obsessed with mathematical models that they can’t fathom the biological question. We need to start training people who understand computers and bioinformatics, but within the context of a disease. I see some of the best places in the world with some of the best bioinformaticians, but they don’t understand the biology of the disease.
FLG: So with the field changing so rapidly, how does your working life change?
DS: Firstly, I have to struggle with funding like everybody else! The other important thing is, I’m just wondering if it’s getting out of my grasp. I liked next gen sequencing a few years ago when you could just do one cancer, analyse it and you had a really big paper. But now, I’m having to rely on the amazing people and bioinformaticians at Mayo to add that extra layer. I wish I could go back and learn it all, but it’s those guys who have that understanding which are going to be in the driving seat. So we might just retire here to London!