
The study, the largest of its kind, appears online in Nature Medicine.
The researchers looked at 442 lung cancer tissue samples collected from six cancer hospitals in North America. They tested the cancer samples to look at the expression of hundreds of genes, and factored in clinical predictors such as tumor stage and the patients' gender and age. The results showed that the lung cancers could be divided into groups with better and worse survival rates.
Typically, lung cancer patients receive chemotherapy after surgery to reduce the risk of the cancer coming back. But specialists know that some patients with stage I disease, the earliest stage, have an aggressive disease with poor prognosis while some patients with more advanced stage II disease have a relatively good prognosis. The question is how to identify which patients need the additional therapy and which patients could potentially avoid it.
"We found that looking at clinical data along with gene expression can be a more reliable indicator. Gene expression is not just a black box approach -- which a lot of researchers think it is. Sometimes knowing the context actually helps you use that information more efficiently," says study author David Beer, Ph.D., professor of surgery and radiation oncology at the University of Michigan Medical School and co-director of the Cancer Genetics Program at the U-M Comprehensive Cancer Center.
The researchers looked at 442 lung cancer tissue samples collected from six cancer hospitals in North America. They tested the cancer samples to look at the expression of hundreds of genes, and factored in clinical predictors such as tumor stage and the patients' gender and age. The results showed that the lung cancers could be divided into groups with better and worse survival rates.
Typically, lung cancer patients receive chemotherapy after surgery to reduce the risk of the cancer coming back. But specialists know that some patients with stage I disease, the earliest stage, have an aggressive disease with poor prognosis while some patients with more advanced stage II disease have a relatively good prognosis. The question is how to identify which patients need the additional therapy and which patients could potentially avoid it.
"We found that looking at clinical data along with gene expression can be a more reliable indicator. Gene expression is not just a black box approach -- which a lot of researchers think it is. Sometimes knowing the context actually helps you use that information more efficiently," says study author David Beer, Ph.D., professor of surgery and radiation oncology at the University of Michigan Medical School and co-director of the Cancer Genetics Program at the U-M Comprehensive Cancer Center.
To read the complete article, click the following link: http://www.sciencedaily.com/releases/2008/07/080721110309.htm