Probing Mutations in Cancer
At the Broad Institute, researchers are looking for genetic causes of glioblastoma. Stacey Gabriel, Ph.D., director of the genome sequence and analysis program, will be presenting the results of their search using next-generation sequencing methods. The goal is to identify different kinds of genetic changes that may cause the cancer, such as point mutations, structural rearrangements, and other events in the genome.
In the past, a variety of methods would also have been used, including microarrays and conventional sequencing. Second-generation sequencing offers the benefit of addressing many questions in a single experiment. “There are things we can find with sequencing that we wouldn’t have found before,” Dr. Gabriel says, adding, “we’ve found rearrangements in the glioblastomas, for example, that we weren’t able to see on the SNP arrays. There are also interesting transformations of some genes that were new to us. In ovarian cancer we’re finding, using a combination of point mutations and structural rearrangements, new pathways important in the cancer.”
One of the key strategies of their approach is targeting only the coding portion of the genome, which is just 1–2% of the overall genome. They utilize Solexa, using a method invented at the Broad Institute, and work in collaboration with Agilent Technologies. “We call it hybrid selection. It’s a technology that uses long oligos that Agilent synthesizes on arrays. The long oligos are cleaved off the arrays and capture corresponding parts of the human genome. We’re able to isolate the part that gets captured and sequence that.”
The most powerful of these is a set of all human exons—from all 20,000 human genes. That allows the scientists to target every gene in one experiment. “The power of using next-generation sequencing and the richness of the information that we’re getting now, in an almost routine way, is impressive,” adds Dr. Gabriel. “There’s still a long way to go to really work out the best and most sensitive and specific analysis. I think that some of the errors that are created in this data are still poorly understood. One of the main challenges right now is increasing the accuracy of our interpretation of data.”
Matthew Ferber, Ph.D., is a codirector of the clinical molecular genetics laboratory at Mayo Clinic. His group is working on hereditary colon cancer. They start with 22 colon cancer genes on a Roche NimbleGen (Roche Applied Science) capture array, then elute the DNA and submit it for second-generation sequencing on the 454 and Solexa platforms.
The goal of this initial experiment was to compare the two platforms to see which is most useful for diagnostic purposes. “Each company right now has its strengths and weaknesses,” Dr. Ferber explains. Ultimately, the comparison seems pretty much a wash, and Dr. Ferber has not yet made a final decision.
“At the end of the day, the answer no clinical lab wants to hear is, you’ll have to sequence with both platforms to get a clear clinical picture. The economics of this for a clinical laboratory becomes untenable. There must be a convergence of the technology that allows for high throughput, short run time, long reads, all at an economical price.”
Second-generation sequencing has developed rapidly since its introduction in 2005. Now appearing in research, industrial, and clinical laboratories, it is finding new uses and new applications, and in some cases supplanting older technologies.