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BETHESDA, Md.—Although the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) doesn't have any skin cancer efforts among the nearly 100 clinical studies it is currently conducting, the agency has just made a major research contribution to efforts to fight the deadliest form of skin cancer: melanoma. Announcing the results of study appearing April 15 in the early online issue of Nature Genetics, the NIH reports that a team led by its own researchers has become the first to systematically survey the landscape of the melanoma genome.

In so doing, the NIH reports, the researchers have made what it calls "surprising new discoveries" using whole-exome sequencing, an approach that decodes the 1 percent to 2 percent of the genome that contains protein-coding genes. One of the most notable finding were mutations in one particular gene, known as TRRAP, which "emerged as remarkable for occurring at the exact position in six separate individuals with melanoma," the NIH notes. TRRAP harbors a recurrent mutation clustered in one position along the string of DNA code in about 4 percent of cases.

"These data suggest that TRRAP is a driver and probably an oncogene," says study senior author Dr. Yardena Samuels, an investigator in the Cancer Genetics Branch of the NHGRI's Division of Intramural Research. Oncogenes are cancer-causing genes that enable the cell to survive despite stressful conditions, rather than die off normally. "This was one of the most important discoveries in the study since we never expected to identify novel hot-spot mutations," she said.

Another particularly notable part of the study was that the researchers used cell signaling pathway analysis, in the process identifying glutamate signaling as a pathway involved in melanoma. "We are starting to explore what mutations do to the glutamate pathway," Samuels says, noting that ongoing research will entail complex biochemistry.  She added that NIH colleagues published a study in the April 21, 2003, issue of Nature Genetics almost exactly eight years ago, implicating the glutamate signaling pathway in melanoma.

"This work demonstrates that our intramural researchers are on the front line of genomics and bioinformatics, providing high quality data and analysis to address important questions about health and disease," observes Dr. Daniel Kastner, NHGRI's scientific director.

In their work, the researchers conducted a comprehensive genome analysis and explored the melanoma genome's functional components, with an eye toward mutations in particular. They studied melanoma at the metastatic stage because that is when the tumor cells have the highest accumulation of gene mutations.

"Melanoma is one of the most challenging solid cancers to work with because it has such a high rate of mutation," Samuels notes, also adding that melanoma is the most serious form of skin cancer and its incidence is increasing faster than any other cancer.  "Whole-exome sequencing will help us identify the most important changes."

"It is now clear that genomic analysis will have a major impact on our ability to diagnose and treat cancer," adds Dr. Eric D. Green, director of NHGRI. "This study represents a collaboration of basic science, clinical research, genome sequencing and data analysis at its best."

NHGRI researchers and a colleague from the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins designed and analyzed the new study, while National Cancer Institute (NCI) researchers and colleagues from the University of Texas MD Anderson Cancer Center in Houston and the University of Colorado Denver School of Medicine collected melanoma tumor samples.

"This study is an example of the vital utility of preserving high-quality tumor samples that include clinical information," notes study co-author Dr. Steven Rosenberg, chief of surgery at NCI. "Furthermore, it is a powerful example of the importance of bridging basic science and clinical medicine."

As a first step in the study, NHGRI researchers obtained 14 metastatic melanoma tumor samples and matching blood samples from a collection maintained at NCI. Whole-exome sequencing of the 28 samples was performed at the NIH Intramural Sequencing Center.

The exome sequence data required a number of analytic steps to separate functionally important mutations from a large number of total results. The first of these analyses differentiated the mutations that occur sporadically in the tumor, called somatic mutations, from inherited mutations. It entailed a comparison between the mutations observed in the blood samples and those from the tumor cells of the same individual. Researchers eliminated from further analysis any tumor mutations that also occurred in normal tissue.

Within that large set of somatic mutations, the sequence contained thousands of mutations that occur but are presumed to have no role in tumor development, called passenger mutations, since they likely are just along for the ride. Researchers derived a rate for occurrence of passenger mutations versus driver mutations, known as the background mutation rate. This statistic differs for each cancer type. In their study, the authors provide what they say is the most comprehensive data to date about this aspect of melanoma mutation analysis.

The researchers excluded from further analysis any inherited genetic alterations already annotated in such datasets as the Single Nucleotide Polymorphism Database, or dbSNP, and the 1000 Genomes Project. Additionally, bioinformatic analysis looking at genes conserved across species suggested which mutations were worth additional functional investigation.

"Most of the mutations are passenger mutations, which means they don't have a functional role in melanoma," Samuels says.

Once the passenger mutations were ruled out, the team could focus on those most likely to cause melanoma. The researchers identified 68 genetic changes that appeared to be somatically mutated at elevated frequency. They then identified 16 genes deemed to be melanoma driver mutations, factoring for both the background mutation rate and the numbers of respective mutations found in the tumors in this study. Of the 16, only the oncogene BRAF had ever been implicated in melanoma.

The ionotropic glutamate receptor gene, GRIN2A, was the most highly mutated of the genes newly implicated in melanoma. It contained mutations in 33 percent of an NCI sample set and in 25 percent of a larger set of samples that combined those maintained by NCI and two other collections. The researchers suggest that this gene is important because of its role in the signaling pathway.

"There are some indications that suggest that this is a tumor-suppressor gene," Samuels comments, "but we still need to prove that using functional studies."

It was at this point that the researchers got to the "hot spots" that Samuels mentioned early in this article. They looked for these hot spot mutations—essentially recurrent mutations—that occurred in multiple patient tumors. The BRAF gene, with a hot-spot mutation previously implicated in melanoma, led a list of nine additional genes with mutations that occurred in more than one tumor. Mutations in seven of the nine genes caused protein-coding changes. These seven hot-spot mutations led the researchers to look precisely for these mutations in 153 additional melanoma tumors.

That, in turn, led to the TRRAP findings and the realization it might very well be a driver of melanoma and an oncogene. TRRAP is found in many species, which the NIH team says suggests its importance in normal function and suggests that mutations in this gene would detrimentally affect protein function. To confirm a possible cell-survival function for TRRAP, the researchers disrupted the gene in mutant cell lines, and the cells had an increase in cell death over time. This, the researchers say, showed that TRRAP is a cancer-causing oncogene, because the mutant cell is clearly dependent on it.

However, Samuels cautions that while this discovery is exciting, it remains a basic science finding and does not necessarily suggest a therapy.

As part of their sequencing analysis, NISC investigators developed a statistical tool named Most Probable Genotype. The tool calculates reliability of data produced in the sequencing process.

"This paper is not only about biology," Samuels notes. "We are providing an effective tool for the other researchers who conduct exome sequencing so they too are able to validate which DNA alternations are reliably detected."

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