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CREDIT: (© ISTOCKPHOTO.COM/NANTELA Produced by the Science Genomics To help researchers make such distinctions, Oxford Gene Technology supplies a range of microarrays, such as the CytoSure ISCA Arrays, which look for genetic defects involved with known syndromes, such as Prader Willi and Williams-Beuren syndromes. PerkinElmer (Waltham, Massachusetts) has also developed assays for detecting disease-related structural changes in chromosomes. For example, the company provides genomic testing of oncology samples with its OncoChip. ìThis is a high-density whole-genome array, targeting more than 1,800 cancer genes and clinically relevant balanced translocations,î says Christopher Williams, market segment leader at PerkinElmer. The array can reveal copy-number variations as low as 10 kilobases in the targeted regions. Additionally, the CytoScan HD Cytogenetics Solution, from Affymetrix, offers probes for both copy-number variation and single nucleotide polymorphisms (SNP). The probes for copy-number variation can reveal chromosomal changes that could cause clinical concerns, and the SNP probes help researchers assess more detail on the exact variationóspecifically the changes in individual nucleotides. ìThis is the highest density microarray on the market,î says Last. ìItís being used in the classical sense of cytogenetics, [to detect] inherited disorders, and increasingly in oncology, especially [for] hematological malignancies.î The array can reveal copy-number variations in chromosomal segments as small as 25,000 nucleotides. For the moment, this is a research-useonly tool, but Affymetrix is running clinical trials to test the use of this platform as an in vitro diagnostic. Agilent (Santa Clara, California) also makes microarrays that detect copy-number variations, such as its CGH (comparative genomic hybridization) plus SNP microarrays. ìThese can be customized from more than 28 million probes in our library, and users can even upload their own probe sequences,î says Patricia Barco, product manager for cytogenetics at Agilent. Within an exon, for example, these microarrays can detect copy-number variations in DNA segments as small as 100 base pairs. ìThese can be used in prenatal and postnatal research and cancer,î Barco says. The most popular format, according to Anniek De Witte, product manager, clinical software at Agilent, includes 180,000 probes divided into four samples. ìThis is the best balance of the number of samples and resolution,î she says. In addition, the Agilent CytoGenomics 2.5 software compares the results from these arrays with external and internal databases to distinguish between common variations and ones that could cause clinical problems. Creating Custom Tools To apply microarrays to clinical problems, physicians need approved tools. One FDA-cleared diagnostic tool, the Pathwork Tissue of Origin test from Pathwork Diagnostics in Redwood City, California, uses an Affymetrix microarray to determine the tissue type in which a patientís cancer started, such as breast or colon. Raji Pillai, senior director, product development and clinical affairs at Pathwork Diagnostic says, ìThis test uses formalin-fixed, paraffin-embedded [FFPE] tissue from a patientís tumor and 2,000 transcript markers to provide a readout of a tumorís gene-expression profile.î Using several thousand different tumor specimens and proprietary computational algorithms, researchers at Pathwork Diagnostics have identified a set of 2,000 genes that can be used to distinguish 15 kinds of tumors. When a pathologist receives a cancer sample that is difficult to iden- www.sciencemag.org/products Life Science Technologies tify visually, they can send it to Pathwork Diagnostics. ìIt takes four to five days to report out a result thatís interpreted by ìThe resolution a pathologist in our lab,î says David Cra- is far higher with ford, the companyís chief commercial an array. The officer. A company pathologist reviews the results to ensure the most accurate challenge is interpretation of this diagnostic. determining if a In the future, the company hopes to small aberration develop microarray tests that determine a tumorís tissue of origin and also dis- is pathogenic or tinguish between tumor subtypes. Such nonpathogenic, advanced tests might even ìprovide in- or a variance formation on the [patientís] predicted response to a particular therapy,î Cra- of unknown ford says. In addition to being used for studying an individualís genetic profile, microarrays can be used to explore genetic variations across different populations and cultures. For example, Jennifer Stone, market development manager at Illumina in San Diego, California, says, ìWe developed our Infinium HumanCore BeadChip family of microarrays to provide a solution for population-level or biobank studies.î Such research involves tens to hundreds of thousands of samples. ìThese genetic studies are on a scale above and beyond whatís historically been done,î says Stone. Because these microarrays accommodate a large number of samples, they provide an opportunity for researchers to perform robust statistical analyses which can reveal differences in the distribution of genetic variation between normal and diseased populations. The HumanCore microarrays provide a standard set of over 300,000 SNP probes, which covers the entire genome and includes additional probes specifically focused on ìvariants that exist in the population and lead to the loss of function of genes,î explains Stone. These new microarrays can also be customized, so researchers can study variants found from their own experiments or from public databases. To explore genetic variations across entire populations, researchers need a family of flexible microarrays. Thus the second member of the HumanCore family, the Infinium HumanCoreExome BeadChip, includes the standard set of over 300,000 SNP probes plus 240,000 exome-focused markers. With this combination of markers, a scientist can compare single nucleotide variations between samples and potentially determine how they impact a proteinís production, as indicated by the exome-based markers. As companies begin to create increasingly customized continued> 859
Life Science Technologies Genomics 860 Featured Participants Affymetrix www.affymetrix.com Agilent www.agilent.com Ambry Genetics www.ambrygen.com Expression Analysis www.expressionanalysis. com Illumina www.illumina.com Life Technologies www.lifetechnologies.com Oxford Gene Technology www.ogt.co.uk Pathwork Diagnostics www.pathworkdx.com PerkinElmer www.perkinelmer.com Washington University School of Medicine in St. Louis medschool.wustl.edu tools, the concept of what makes a microarray has begun to evolve. Traditionally, microarrays consisted only of nucleotides attached to a solid surface, but variations on this theme also exist. For example, Life Technologies (Carlsbad, California) developed its TaqMan OpenArray Real-Time PCR plates, which include 3,072 wells. ìThe arrays can be formatted from our inventory of eight million TaqMan assays,î says Jami Elliott, market development manager at Life Technologies. The real-time PCR assays, which use TaqMan probes (so named because these assays rely on the Taq polymerase), can be used to measure gene expression, identify biomarkers, and more. If eight million choices arenít enough, Joshua Trotta, director, business development genetic analysis at Life Technologies, says, ìWe can custom design one.î Ongoing Data Dilemmas Rather than making microarrays, Expression Analysis, a Quintiles company in Durham, North Carolina, uses arrays to conduct a wide range of studies for customers, such as gene-expression profiling. In doing so, Expression Analysis uses microarrays from several vendors, including Affymetrix, Illumina, and Fluidigm in South San Francisco, California. According to Pat Hurban, vice president of R&D at Expression Analysis, ìMicroarrays are very mature as a technology, but there are still a number of challenges in working with the data, especially when you want to drill down into the biology.î He adds, ìItís one thing to provide a statistical treatment of data, but another to understand the pathways involved and translate that into biology.î This company uses a collection of proprietary tools in an effort to bridge that knowledge gap. In fact, Hurban advises researchers to reassess the best technology to use as a project advances. ìYou must be mindful of the technical limitations of microarrays,î he says. For example, he points out that microarrays provide excellent discovery tools. ìItís not uncommon to identify specific genes of interest with microarrays,î Hurban says. ìWhen it comes to translational research, the question becomes: Is it advisable www.sciencemag.org/products to continue on a microarray platform as you get closer to the clinic or transition to a more suitable and robust technology, such as [quantitative] PCR or sequencing.î In a recent project, Expression Analysis worked with a client who had what Hurban describes as ìa preliminary gene-signature panel that was very useful as a diagnostic in a certain indication area.î Researchers at Expression Analysis worked with patient samples from the sponsor to put that signature on microarrays. ìWe showed the validity of this panel,î Hurban says. ìUltimately, the sponsor wanted to turn this signature into a diagnostic and became concerned with the microarray results because the precision was a bit of a challenge.î Consequently, the client eventually turned to a PCR-based platform for the final diagnostic. As a result, Hurban says, ìYou might use a microarray to some point, and then go to another technology.î Tomorrowís Tools The ongoing advances in sequencing technology have made more than a few experts predict the demise of microarrays. For example, Elizabeth Chao, director of translational medicine at Ambry Genetics in Aliso Viejo, California, says, ìThe expression arrays that Iíve been using for 14 years are incredible tools, but RNA sequencing is starting to replace microarrays in research and translation.î She adds, ìSequencing is not replacing microarrays in the clinical setting yet, but it probably will soon.î The data generated by sequencing can be both beneficial and challenging. Sequencing provides a gigantic amount of data in a short period of time, but it can be difficult to interpret so much data. Chao is confident that interpreting sequencing data will improve rapidly. She says, ìBioinformatics has really come up, and new methods are making it possible to look at sequences across the entire genome.î To evolve with changes in technology, some companies provide services that teach researchers to use the growing amounts of data. For example, Todd Smith, senior leader, research and application at PerkinElmer, says, ìWe can help people as they go from microarrays to DNA sequencing.î This can include analytical techniques for handling the higher volume of data. These technologies, though, will likely complement each other, according to Smith and his colleagues. ìThere are applications where microarrays work best, and others where sequencing works best,î says Williams. ìThere are areas where sequencing wonít work well, but microarrays can.î As an example, Williams says they are about to start a study that involves 160 samples that must be processed in a matter of weeks. ìThereís no way we could go through that with sequencing and get it turned around in time to have meaningful data,î he says. Moreover, Smith says microarrays are superior to sequencing when it comes to searching for structural variations in a genome. Though some experts may have differing opinions, the general consensus predicts that microarrays will continue to benefit basic research and provide clinical tools related to genomics. In the end, microarrays will advance where they work the best. Mike May is a publishing consultant for science and technology. DOI: 10.1126/science.opms.p1300072 Produced by the Science
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