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Study Demonstrates Gene Expression Microarrays are Comparable and Reproducible

sitate that microarray data produced in different laboratories be combined for analysis. Even if all procedures and equipment were the same, small differences between labs, such as in handling the tissue samples, extracting the RNA, or scanning the microarrays, could result in different profiles. To test the feasibility of multi-lab microarray studies, the NCI’s Director’s Challenge program set up this preliminary study to compare results between labs. Twelve different tumor tissues, five cancer cell lines, and five purified RNA samples were prepared, blinded, and randomized for analysis in four laboratories: University of Michigan Medical School, Ann Arbor, Mich.; Dana Farber Cancer Institute/Whitehead Institute, Boston, Mass.; Memorial Sloan-Kettering Cancer Center, New York, N.Y.; and H. Lee Moffitt Cancer Center, Tampa, Fla. All five cell lines and RNA samples were derived from lung carcinomas, while the tissue samples were derived from multiple normal and cancerous tissues. The labs followed a common protocol for all steps of sample preparation and microarray analysis and the resulting gene expression profiles were analyzed and compared. Sample correlation within each lab was extremely high; microarray data from the RNA samples had the highest correlation values, followed by the cell lines, and then finally the tissue samples. This was not surprising, as RNA required the fewest steps of preparation, while tissues required the most. The between-lab correlation values decreased slightly for all samples, but in all cases expression profiles of similar samples could be accurately grouped together. The researchers also examined variations of individual gene measurements to help determine causes of variability, and they found that laboratory practices comprised the smallest source of variation in these studies. Measurement errors common to all labs were the next most common contributor, and biological differences in different samples were the largest source of variat
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Source:NIH


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