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Gov't Creates Gene Database of Normal Human Tissues

Researchers at the National Cancer Institute, part of the National Institutes of Health, have built the largest open-source database for normal tissue from human organs. Scientists searching for genes that go awry and cause disease can use the NCI database as a crucial point of reference because it pinpoints which genes are expressed in many of the body's major organs under normal conditions, without known disease.

Scientists can compare the genes from their own biological samples to this dictionary of normal expression. "Genes identified by the database as abnormally active in a particular disease could become potential targets, guiding researchers to better candidates for new drug therapies, immune-based vaccine treatments, and potential biomarkers to help with diagnosis," explained Javed Khan, M.D., chief of the Oncogenomics Section of NCI's Pediatric Oncology Branch. A study validating the database appears in the March 2005 issue of Genome Research.

"The NCI database is an important addition to the growing body of knowledge about gene expression in normal human tissues," added James Jacobson, Ph.D., acting branch chief of the Diagnostics Research Branch in NCI's Division of Cancer Treatment and Diagnosis. "These data give investigators a baseline against which to compare gene expression data obtained from tumor or other disease specimens, and should be a valuable resource for the research community."

The normal organ database uses a technology known as gene expression microarrays, more commonly known as gene chips, to provide a kind of fingerprint that researchers and clinicians can use to compare cells and tissue they suspect may have cancerous or other malfunctioning genes. To create these fingerprints, Khan and his team assembled a complementary DNA (cDNA) microarray, using a pair of glass slides on which thousands of known genes have been printed in tiny spots. Cells can be tested by manipulating them so that genes activated in the cel l will match up with the known gene samples, like two pieces of Velcro attaching to each other. The cellular genes are treated with fluorescence and literally light up the gene dots on the chip. The light pattern is then measured with a special type of microscope and the results are fed into a computer for analysis.

Gene expression microarrays have been used in numerous applications, including identifying novel genes associated with certain cancers, classifying tumors, and predicting patient outcome. Another NCI-funded study recently demonstrated that microarray analysis of identical tissue samples at geographically separate laboratories can produce the same quality of results as those done within a single lab**. The normal organ database takes that one step further, enabling scientists and clinicians to compare the gene expression results for their own tissue or genes of interest to a baseline standard that represents a generic picture of normal gene activity, organ by organ, in the human body. Users of the array on the new NCI web site (http://home.ccr.cancer.gov/oncology/oncogenomics/) will find expression profiles for 18,927 genes, which include most of the genes that are known to help direct basic activities of the human body.

Recently the Human Genome Project revealed a surprisingly low number of human genes (20,000-25,000), and Khan said it had been previously reported that "only a fraction of that, perhaps 10,000 genes, are actively transcribed in normal cell processes." Thus it becomes strategically useful to characterize this essential backdrop. "The normal organ database provides a platform that may help scientists find new targets in the cells of previously incurable cancers. The driving force of research in our section is to translate genomic information to the clinic. The goal is to save lives and improve the quality of life for children with high-risk cancer."

Until now, no publicly available, normal human organ database has us ed so many tissue samples (158), or included samples of tissue from different parts of the same organs from multiple donors. Tissue samples were harvested an average of 11 hours after death, from males and females of different ethnic groups, ranging from ages 3 months to 39 years old.

The very large cDNA microarray they constructed has more than 42,000 detectors built into two chips using verified cDNA libraries upon which many other researchers currently rely. Analyzing the organ tissue with this tool allowed Khan and his team to identify 18,927 genes that constitute their database. "We found that each organ had a unique expression level profile," said Khan, "and, remarkably, any truly random subset of 1,000 genes could distinguish one organ from another."

Each organ revealed a very distinct profile of active genes, different from all others. However, the gene profiles from different organs that share similar biological functions also showed patterns of expression. For example, though the cerebrum and the cerebellum are two distinct parts of the brain, located apart from each other and doing very different jobs, their gene expression profiles reflected their commonality as part of the nervous system. Similarly, "muscle contraction" genes were found in skeletal muscle, smooth muscle tissue, and the heart -- all organs that share a common way of functioning.

To illustrate the kind of useful data that can emerge from using this tool, Khan's team analyzed 100 samples of the most common pediatric solid tumor cancer, neuroblastoma (NB), which accounts for 7 percent to 10 percent of all childhood cancers. Even though the tumor samples were taken from a variety of patients with different stages of cancer, the database kicked out a list of 19 genes that were consistently overexpressed compared to normal brain tissue.

"All of these genes are involved in one way or another with the kinds of activities associated with the development of cancer - - processes such as apoptosis, growth, proliferation and transcription," said Khan. These results provide scientists studying and treating NB with a focused set of genes to explore.


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Source:NIH


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