A new statistical method that identifies similar groups of genes from large tissue samples could be used by health care professionals to predict the effectiveness of treating patients suffering from a variety of disorders including cancer, according to a research article published in Genome Biology today. The statistical method, named gene-shaving, because it cuts away useless or irrelevant data to leave clusters of similar genes, was used by the research team at Stanford University, USA, to analyse the genetic information of tumors removed from patients suffering from diffuse large cell B-lymphoma (DLCL). The researchers found that they could identify distinct clusters of genes that, from previous studies, were highly indicative of a patient's chance of survival.
"One important motivation for developing gene shaving was the wish to identify distinct sets of genes whose variation in expression could be related to a biological property of the samples," says Robert Tibshirani, one of the lead researchers from the Stanford University project team. "In the present example, finding genes whose expression correlates with patient survival is an obvious challenge."
The team used more than 4,500 gene expression measurements taken from tumours of 48 patients with DLCL. The measurements were gathered using new DNA array techniques that allow researchers to gather detailed genetic information from a tissue sample. "A major challenge in interpreting these results is to understand the structure of data produced by such studies, which often consist of millions of measurements," continues Tibshirani.
The gene shaving process involves repeatedly applying a complex mathematical formula to the large sea of genetic expression data in order to find the clusters, or islands, of genes that are useful to the researchers. By selecting the clusters of genes that include the strongest individual genes for predicting survival, researchers have been able to identify the patient's chance of survival based on the genetic information in the sample tumor.
Gene shaving will allow researchers to analyse more genetic information at greater detail than is presently possible. "Gene shaving differs from hierarchical clustering and other widely used methods for analysing gene expression studies because it can find clinically and biologically relevant subdivisions in gene expression data, "says Tibshirani, "This is important because genes may belong to more than one cluster."
With the wealth of genetic information now available, the gene shaving method could find wider applications throughout this field as scientists strive to uncover the meaning behind the genomic information they have meticulously gathered. "Today statistics is more important that ever, because of the ease with which we can collect large amounts of data," says Tibshirani, "The challenge is to sort through all of this data and separate out the consistent patterns from the noise."
The gene shaving article is one of the first to be published by Genome Biology, a new peer-review journal that will give free access to all of the primary research articles it publishes. Speaking at a conference at the beginning of July, Patrick Brown, Associate Professor of Biochemistry at Stanford and co-author of the gene-shaving paper with Tibshirani, called on the scientific community to boycott biomedical journals that refuse to make their research articles available for free.
He said, "Scientists have to take full control of the process of disseminating scientific information by insisting that their work be treated as a freely available public resource." Calling for a fundamental change in the way research results, observations and ideas are reported and shared, he argued that rather than transferring ownership of scientific information to "parasitic" commercial publishers, scientists should only publish with organisations that are good "science citizens" and make the information freely available for their colleagues and the public around the world.
For further information or a full copy of the article, please contact:
Andrew McLaughlin
Email: andrew@biomedcentral.com
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Voice mail: 44-020-7631-9131
Robert Tibshirani can be contacted at:
Email: tibs@stat.Stanford.EDU
Notes for Editors
1. The article 'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns,, by Trevor Hastie, Robert Tibshirani, Michael B Eisen, Ash Alizadeh, Ronald Levy, Louis Staudt, Wing C Chan, David Botstein and Patrick Brown will be available free-of-charge on the Genome Biology website from Friday 4th July 2000 at http://genomebiology.com/2000/1/2/research/0003.1
2. The article will also be lodged in the NIH permanent free-access archive of research, PubMed Central: http://www.pubmedcentral.nih.gov
3. A summary of the Freedom of Information conference mentioned in the news release can be found at: http://www.biomedcentral.com/info/conference/summary.asp
4. Funding for this research project was received from the National Science Foundation and the National Institutes for Health
5. Further information on Robert Tibshirani is available at:
6. http://www-stat.stanford.edu/~tibs/
7. Genome Biology is a new journal that will give free access to research at http://genomebiology.com. Genome Biology is part of the Current Science Group - a group of independent companies that collaborate closely with each other to publish and develop information and services for the professional biomedical community. The Group has its head-office in London (UK), with additional offices in Philadelphia, New York and Tokyo.
Journal
Genome Biology