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Editorials |
University of Chicago Pathology, University of Chicago Hospitals, Hospital Mailcode MC0004, 5841 S. Maryland Ave., Chicago, IL 60637, Fax 773-702-6268
Microarrays were first applied to experimental studies of gene expression, but newer microarray applications, such as comparative genomic hybridization, have evolved and preceded it to clinical introduction. Challenges to clinical use include potentially dramatic biological changes in gene expression as a result of preanalytic variation in patient and sample handling, analytical variation resulting from the complex assay process, and daunting analytical and statistical problems in simultaneous measurement of thousands of signals ranging over several orders of magnitude.
Arrays come in many formats, including chips, slides, microfluidic devices, and beads. They differ in the sets of genes assayed and in the probe sequences used to assay for a given gene. Some systems hybridize the sample and control to the same array, using two-color labeling, whereas another system hybridizes the sample and control to separate arrays. As a result, formats have incommensurable merits and often incommensurable data. Published information comparing formats are too limited for conclusions other than that data interchange might be feasible (1)(2).
This flowering of ingenuity is acceptable for hunting candidate genes with one format and verifying results by more common techniques, but for clinical applications, this variety is an obstacle. The typical application envisions a multiparametric "gene-expression signature" in which the expression patterns for many genes are combined to generate a "classifier" for diagnosis or prognosis. Laboratory 1, which uses array system brand A, publishes a well-designed study showing that a gene-expression signature distinguishes benign from malignant omphalomas. How should Laboratory 2, which uses brand X, adapt the "signature"? Clinical studies are also hampered by lack of well-defined controls. This problem is analogous to deciding, without benefit of reference materials, which of two immunoassays is better—when they use independently derived antibodies and different calibrators and controls—and then making this decision for 10 000 immunoassays at once. Some suppliers already provide tools to control for variation, including replicate probes, "spike-in" RNA controls, normalization algorithms, and image-quality metrics, but these also differ among formats. For comparing results among methods, it would be decidedly helpful to have widely available, standardized, renewable pools of RNA species that could monitor RNA purification, monitor cDNA labeling, verify sensitivity, and serve as controls.
A NIST workshop in March 2003, "Metrology and Standards Needs for Gene Expression Technologies: Universal RNA Standards" (3), initiated a consortium effort to design, produce, and validate two types of RNA reference materials applicable to both microarrays and quantitative reverse transcription-PCR (QPCR). A more recent consortium workshop focused on one type of RNA reference material (4). Cronin et al.(5) ably summarize the first meeting. Each RNA reference material will be a cRNA pool used to generate labeled cDNA, which is then hybridized to a (correspondingly modified) array:
During an actual assay, the APS could be cohybridized with a complex sample in two-color format. In the single-color format, the APS and the complex sample would have to be hybridized to separate arrays. The performance of a simple cRNA pool will not necessarily reflect performance of an array system with a more complex mixture. For such a format perhaps a complex sample could be labeled in parallel with and without addition of an APS, and then hybridized to separate arrays (recovery experiment).
The UHS ("spike-in" controls) would provide information on efficiency of cDNA synthesis/labeling, uniformity of hybridization, and sensitivity of detection. A pool added to samples before RNA purification could monitor that process. The utility of APS and UHS for QPCR is clear. The proposed number of materials exceeds needs but will not resolve the fundamental question of how best to normalize QPCR.
The External RNA Control Consortium proposes a detailed plan for 100 cRNA "spike-in controls", each alien to the combined genomes of humans and seven research organisms (4). If it expedites production, clinical users would accept controls alien to humans but not to Arabidopsis. The notion in both workshops, that "spike-in controls" permit comparison among arrays, should be treated with caution: sample RNA risks preanalytical variation long before a "spike-in" is added; a pretty good RNA electrophoresis profile does not assure overall performance. Even a large number of "spike-in" controls (UHS) gives no information about the performance of array probes for genes of interest.
The APS proposal is both too ambitious and too modest. The APS proposal is ambitious because a measure that permits "apparently" simple comparison among formats will meet commercial resistance. If the goal is to provide general quality control for manufacture, "alien" genes could serve. If the goal is to provide quality control for genes used in gene-expression signatures, the proposal is too modest. The goal of 96 cRNAs was chosen based on microtiter plate capacity. "Universal RNA standards" are currently available, typically pools of RNA from many sources (6). Such a "standard" can include mRNA for most genes on a large array, but at concentrations that are not individually controlled. Such material is neither easily replenished nor standardized. Given the extent of interest and the expectation of high expense, why not plan adjustable pools of 1000 cRNAs that could form a cohybridization control (negative or positive)? Issues of cost, intellectual property rights, and clone-library maintenance will have to be overcome.
In the short run, a well-chosen 96-gene APS would be helpful. As A.N. Whitehead observed, "Civilization advances by extending the number of important operations which we can perform without thinking about them" (7). There are related but thornier problems to address (or to muddle through) before clinical gene-expression arrays succeed:
This is not a litany of despair. Consider the state of immunohistochemistry and immunoassay, which are now several decades past their introduction. For some antibodies immunohistochemistry results are controversial, but for others there is clear utility. Prostate-specific antigen immunoassays have a clear utility, but the details are still controversial. NIST efforts at microarray standardization should be applauded and an early fruition desired, especially because proteomics is beginning to grab attention. Still, the data-analysis challenges in proteomics might be just as tough—with mass spectrometry you cannot even see the spots.
References
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