Simple 2-gene test sorts out similar gastrointestinal cancers
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A powerful two-gene test distinguishes between a pair of nearly identical gastrointestinal cancers that require radically different courses of treatment, researchers report this week in the online Early Edition of the Proceedings of the National Academy of Sciences.
“This simple and accurate test has the potential to be relatively quickly implemented in the clinic to benefit patients by guiding appropriate treatment,” says senior author Wei Zhang, Ph.D., professor in the Department of Pathology at The University of Texas M. D. Anderson Cancer Center.
The analytical technique employed to tell gastrointestinal stromal tumor (GIST) from leiomyosarcoma (LMS) with near perfect accuracy will have wider application in more individualized diagnosis and treatment of other types of cancer, study co-authors from M. D. Anderson and the Institute for Systems Biology in Seattle conclude.
GIST was once thought to be a type of leiomyosarcoma because both originate in the smooth muscle cells of the gastrointestinal tract. However, GIST is treatable with the targeted medication known as Gleevec and is relatively unresponsive to chemotherapy. The opposite is true of LMS.
An existing test distinguishes among the two cancers with about 87 percent accuracy, but intensive and time-consuming additional analyses are required for uncertain cases, Zhang says.
The researchers used common whole genome microarrays to measure gene expression in 68 GIST or LMS tumors, but then applied an analytical twist. Rather than identifying multiple genes that might distinguish each type of cancer, the researchers instead analyzed every possible pair of genes, says first author Nathan Price, Ph.D., research scientist at the Institute for Systems Biology, a process called Top Scoring Pair analysis.
The result was a cancer classifier based on the expression ratio of two genes. If the gene OBSCN expresses more of its RNA than the gene C9orf65, then the tumor is GIST. If C9orf65 is more abundant, it’s LMS.
The test accurately identified 67 of the 68 microarrayed tumors, with the exception being one tumor with nearly a 50-50 split between the two expressed genes upon which no diagnosis could be made. An additional test using a more accurate measurement procedure on the two genes identified 20 of the original samples (including the sample with near equal gene expression) and 19 independent samples with 100 percent accuracy, the authors report.
Genomic approaches to diagnosing, selecting treatment and determining a cancer patient’s prospects of responding to care are beginning to work their way into the clinic, the researchers note. These approaches can rely on dozens of genes as biomarkers.
Top scoring pair analysis allows the use of fewer genes to distinguish between similar cancers or between groups of patients who have one type of cancer yet respond differently based on genetic indicators, the authors note. For example, paired gene analysis may be used to determine which patients benefit from different types of chemotherapy and which patients are at risk of relapse.
Zhang said the research group is using this analytical strategy to identify gene pairs that can predict which GIST patients respond to Gleevec and how other types of cancer respond to treatment as well.
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NEWS EMBARGO: 5 p.m. EST Feb. 12, 2007
Co-authors with Zhang and Price are: Jonathan Trent, M.D., Ph.D., of M. D. Anderson Department of Sarcoma Medical Oncology; Adel El-Naggar, M.D., Ph.D., David Cogdell, and Ellen Taylor, all of M. D. Anderson’s Department of Pathology; Kelly Hunt, M.D., and Raphael E. Pollock, M.D., Ph.D., of M. D. Anderson Department of Surgical Oncology; and Leroy Hood, Ph.D., M.D. and president, and Ilya Shmulevich, Ph.D., of the Institute for Systems Biology.
This research was funded by the National Cancer Institute and the National Institute of General Medical Sciences, both of the National Institutes of Health; the Commonwealth Foundation for Cancer Research; the American Cancer Society; the Texas Tobacco Settlement Fund; and by grants from the Michael and Betty Kadoorie Foundation and the Goodwin Fund.
University of Texas M. D. Anderson Cancer Center
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