Next-generation sequencing machines introduced this year promise to read a genome in about a day for $1,000. Although the technologies may have their biggest impact in the clinic, their speed may be helpful in the lab—and open new avenues of research.
Next-generation sequencing could revolutionize cancer research, once scientists develop the tools and knowledge to harness the deluge of data
In January 2012, 2 sequencing companies, Illumina (San Diego, CA) and Life Technologies (Carlsbad, CA), each announced a next-generation sequencing machine capable of reading a genome in a day. Life Technologies' machine will do so for just $1,000, the company announced—faster and cheaper than ever before. A month later, Oxford Nanopore Technologies (Oxford, UK) entered the competition with a range of systems stretching down to the MinION, a 1-time-use device about the size of a cell phone to analyze DNA on the go.
The $149,000 Life Technologies Ion Proton Sequencer will sequence a single 3-Gb human genome with 20 to 30 times coverage—repeated sequencing to ensure high-quality data—in a day for $1,000. The $740,000 Illumina HiSeq 2500 will sequence a genome with 40 times coverage in 27 hours. The company has not yet disclosed a price per genome for the HiSeq 2500. The disposable MinION will run under $900, Oxford Nanopore announced, and is designed for inexpensive, universally accessible DNA sequencing rather than high-quality genome reads.
These rapid, relatively inexpensive sequencing technologies are likely to make the biggest impact in the clinic, experts agree. “As a general trend, the less expensive and less time-consuming sequencing becomes, the more feasible it will be to implement sequencing as part of a diagnostic workup,” says Bert Vogelstein, MD, director of the Ludwig Center for Cancer Genetics and Therapeutics at the Johns Hopkins University School of Medicine in Baltimore. “Eventually every tumor will be evaluated to determine what genetic alterations are there.”
Once that happens, the whole process of diagnosing cancer could change, says Andrew Simpson, PhD, scientific director of the Ludwig Institute for Cancer Research, New York. “In the clinic, we'll begin to approach the concept of diagnosing cancer as a function of its mutations rather than its anatomic site or stage,” he says.
The value of having complete genomic information for a tumor, however, still remains to be demonstrated. Although certain known mutations have clear therapeutic indications—such as EGFR mutations in lung cancer and BRAF in melanoma—“what's not clear yet is if we'll get a lot more knowledge by sequencing every gene in the genome” instead of just individual genes, says Vogelstein.
Even if sequencing tumors leads to the identification of additional therapeutic targets, “the whole premise of this is that you need to have drugs suitable for patients with specific mutations, and right now, we simply don't have all the drugs we need,” says Simpson. Cancer research should therefore remain focused on drug development, he argues.
As in the clinic, there are both benefits and limitations to using the technology in the lab. “In cancer research, there's not much that you need right now. If it takes a few days, it's not going to make that much of a difference,” says Soheil Meshinchi, MD, PhD, a pediatric oncologist at the Fred Hutchinson Cancer Research Center in Seattle.
Yet in some cases, that speed might be helpful. In cohort studies, for example, the machines will make it possible to sequence hundreds of exomes in just a few months, says Nicholas Navin, PhD, a tumor geneticist at MD Anderson Cancer Center in Houston. “If it were to take a week to sequence each patient, that study is going to take many years to complete,” he says.
The inexpensive machines will also democratize next-generation sequencing, says Navin, so that small labs, and not just large institutions and companies, will possess the technology. This shift will open up new avenues of research, he believes, as individual investigators apply whole-genome sequencing to a myriad of research areas. For example, Navin, who studies tumor heterogeneity of human cancers, would be able to sequence 10 to 20 samples from a single tumor, instead of 4 to 5 as he currently does. “That would be very exciting,” he says.
The technology could also encourage cancer researchers to take a closer look at animal models of cancer, says Charles Perou, PhD, of the University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center. “Now we can easily sequence a genome from our favorite mouse tumor to identify the differences,” he says. “It's really opening up a whole new world of experiments.”
But there are still roadblocks to overcome before whole-genome sequencing takes off in labs around the country. “The real bottlenecks are in analysis and interpretation,” says Keith Stewart, MB ChB, dean for research at the Mayo Clinic in Arizona. The field needs bioinformatics tools and trained personnel to harness all the data that will result from rapid whole-genome sequencing, agrees Meshinchi. “The ability to sift through a massive amount of data to identify disease-associated mutations is the limiting factor right now,” he says.
No matter what, sequencing machines and bioinformatics tools will continue to pervade cancer clinics and laboratories. “It's been absolutely dizzying how rapidly whole-genome sequencing has become available,” says Meshinchi. “It is immensely useful.”—Megan Scudellari