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NanoString Courting Early-Access Customers for New Copy Number Variation Assays


This story was originally published on June 16.

By Ben Butkus

NanoString Technologies last week launched an early-access program for its new copy number variation analysis assays for the nCounter platform for multiplexed gene expression and molecular analysis.

In addition, NanoString disclosed that researchers at the University of Miami, Harvard Medical School, Broad Institute, and Toronto's Hospital for Sick Children have been beta-testing the new CNV assays to help prep the product for a commercial launch.

"Development has been going fantastic, and we're really excited about the technical performance, so we want to get it out there and into some of our users' hands," Sean Ferree, director of product development for NanoString, told PCR Insider.

"So we're doing a limited launch, and are looking for interested customers who would like to use the nCounter platform to study a custom set of genomic regions that may be varying in their copy number," Ferree added.

The CNV assays are the latest effort by NanoString to ferret out new applications for nCounter and associated CodeSets, which the company initially developed as an alternative to both qPCR and microarrays for gene expression studies.

In April, NanoString introduced human miRNA expression CodeSets for the nCounter platform, claiming that researchers would be able to directly detect and count miRNAs in a highly multiplexed fashion with specificity and sensitivity comparable to qPCR at a fraction of the cost (PCR Insider, 4/22/10).

"We're trying to continue to expand the system and the applications it can address," Ferree said. "The really great thing about this assay is that it's a drop-in solution, similar to the miRNA assays. So it uses the same instrumentation with no new consumables needed, plug and play."

CNVs have in recent years gained importance as a form of structural variation associated with disease susceptibility, drug response, and cancer prognosis.

Researchers have used technologies such as microarrays and high-throughput sequencing to discover thousands of putative CNVs; however, many of these technologies produce a significant number of false positives.

As such, quantitative real-time PCR has become a useful tool for validating detected variants of interest, but the technique can be labor-intensive and difficult to scale up to validate or screen many genomic regions at once, NanoString said.

According to Ferree, the workflow for validating variants using NanoString's technology is "a lot simpler." As an example, he said that as part of the early-access program, NanoString will target variants in as many as 200 different genomic regions in a single-tube assay.

"To do that with PCR, you would need at least 200 different PCR reactions to measure with this sort of fidelity the amplification of these genomic regions," he said. "In many cases, researchers are finding you need multiple probes across the region to really tell you how much of that region is being amplified … so you may need 600 PCR reactions."

Amnon Koren, a post-doctoral student in the genetic department at Harvard Medical School and a beta-tester of the new CNV assays, told PCR Insider that he became interested in NanoString's platform after learning about colleagues at Harvard and the Broad Institute who have submitted for publication research that used the nCounter for RNA expression profiling.

"We saw that it would also be a good technology for DNA copy number measurement," Koren said. "We're planning to measure CNV over several hundred individuals over about 200 loci, and we're thinking of using NanoString's technology to do it."

Koren said that his group is particularly interested in seeing how well the technology works compared to Affymetrix microarrays. "We're trying to see if NanoString gives better data than Affymetrix for copy numbers."

So far, he added, early results have indicated that the nCounter CNV assays are more reproducible than Affymetrix arrays and may be more sensitive for higher order copy numbers.

"Affymetrix gives very good results for copy numbers of between, say, zero and four —for simple deletions and duplications, you can use Affymetrix and get pretty good results," he said. "But once you go to higher order loci, with perhaps up to six or eight copy numbers in different individuals, then Affymetrix is less accurate, with saturation problems."

He also said that the NanoString assays made more sense for their particular project than qPCR in terms of time and labor.

"If you want to look at maybe 200 loci … with qPCR it's hundreds of parallel reactions, whereas with NanoString it's one reaction," he said. "We can do 500 or even more probes in one reaction. With qPCR it would be a huge project; and we'd need technicians. With NanoString it's about one week; and the experiment can be performed by one person. And I can tell you that it's very simple and straightforward; you can't make mistakes; and it's very easy to run, very automated."

Other beta-testers include Dale Hedges of the Hussman Institute for Human Genomics at the University of Miami; Steven McCarroll's group in the department of genetics at Harvard; and Steve Scherer, director of the Centre for Applied Genomics at the Hospital for Sick Children in Toronto.

In a statement, Hedges said that his group has been "very impressed with the nCounter system's ease of use and capacity to generate results concordant with traditional qPCR," and that the group's initial results suggest that nCounter will "provide a promising alternative for the validation and screening of CNVs."

With the beta-testing nearly complete, NanoString is now seeking customers to apply the nCounter CNV assays to their work over the next few months prior to a full commercial launch later this year.

"As with developing any new application, we've talked to the market in order to set the … technical performance requirements and ease of use," Ferree said. "Now we're looking for feedback on the actual workflow; as well as the technical performance of the assay.

"Because it's a different type of application than, say, microRNA, where we're able to cover the entire database for miRNAs … we are interested in getting that feedback before we do a full launch to really make sure we are addressing the needs of the market," he added.