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Cancer Consortium Traces Signature For Lung Cancer Recurrence


Early-stage lung cancer patients are usually treated surgically and sent home, but 25 percent to 30 percent of those people will have their cancer recur. Researchers from cancer institutes in the United States and Canada are paving the way to develop gene expression panels to predict which lung cancer patients will relapse. "If you know who these high-risk patients are, then you would potentially be able to offer them additional therapy," says David Beer, a professor of surgery and radiation oncology at the University of Michigan.

To develop a gene expression panel that can predict which lung cancer patients have a poorer prognosis than others, researchers need a lot of samples to analyze for markers — more than they typically have access to. To manage that, Michigan, H. Lee Moffitt, Memorial Sloan-Kettering, and Dana-Farber formed a consortium to track down a gene signature for lung cancer prognosis. "We really need to look at a larger number of tumors," says Beer. "We decided to basically pool our resources and put all of our tumors together."

In this three-year study, the researchers collected 442 lung cancer samples from different treatment sites. Each location used the same conditions for isolating samples, the same criteria for inclusion, and reagents from the same production lot. Samples from two of those sites became the training set, and researchers from the four institutions independently used those samples to build predictive models. "The models that we tested were very, very broad from one gene to thousands of genes, and they all encompassed different approaches," Beer says.

Of the four panels developed, two were able to predict prognosis in the independent, blinded test sets. Furthermore, when the gene expression panels were used in conjunction with the clinical data, they worked even better. "That meant that putting the two together is more powerful than using just one alone," Beer says. The results are reported in the August issue of Nature Medicine.

While not yet ready for the clinic, these results indicate that "there is information in the genes that can tell you about the behavior of tumors," says Beer. He and his colleagues are now working to determine whether the morphological heterogeneity of lung cancer tumors has a molecular basis. "It's possible there's a lot of different ways that lung cancer becomes a cancer," he says. "Genomically it's a more difficult problem to unravel that."

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