Patterns of gene expression within tumor cells predict whether patients with diffuse large B-cell lymphoma are likely to be cured by chemotherapy, according to an article in the June 20th issue of the New England Journal of Medicine.

Researchers analyzed thousands of genes in lymphoma biopsy samples and determined that the activity of as few as 17 genes could be used to predict patients' response to treatment. "We're able to reliably predict the survival of these patients using data from a small number of genes, indicating that this technique should be entirely manageable for routine use," said National Cancer Institute investigator Louis M. Staudt, M.D, Ph.D., senior author on the study.

Diffuse large B-cell lymphoma is the most common type of non-Hodgkin's lymphoma in adults. Approximately 16,000 new cases are diagnosed in the United States each year, and standard chemotherapy for the disease is effective in only 40 percent of patients. Profiling gene expression in patients' tumors may help clinicians decide which patients are suitable candidates for standard therapy and which should consider other options for treatment.

The discovery of the predictive genes relied on DNA microarray technology, which allows researchers to determine which genes are active in cells. Microarrays, also known as gene chips, are glass slides that have been coated with thousands of spots of DNA, each representing a different gene. To measure the activity of genes, researchers use RNA transcripts to make a fluorescent gene probe. When the gene probes are allowed to bind to their corresponding DNA spot on the chip, the spots on the chip light up. Scientists use the pattern and intensity of emitted light to determine the activity of each of the chip's thousands of genes.

For this study, researchers used the Lymphochip, a specialized microarray containing 12,000 DNA spots representing genes expressed in normal and malignant lymphoid cells. Developed as part of the National Cancer Institute's Cancer Genome Anatomy Project, the Lymphochip is particularly useful for finding differences in gene expression among lymphoid cancers.

Staudt and his colleagues profiled gene expression in 240 tumor biopsies from patients with the lymphoma and identified more than 600 genes whose expression varied significantly between patients who had responded well to treatment and those whose response was poor. These genes highlight aspects of the tumors that affected response to therapy, including how fast tumor cells were dividing and from what type of normal lymphocyte the tumor originated. Many of the predictive genes suggest that a patient's immune response to the tumor is important for achieving a cure with chemotherapy.

Focusing on genes where the difference in expression was most dramatic between the two groups of patients, researchers narrowed the number of key genes down to 17. From these genes, the investigators created a formula that could be used to predict survival following chemotherapy. This predictor classified the patients into four groups of equal size. The five-year survival rates for these groups were 73 percent, 71 percent, 34 percent, and 15 percent.

Currently, physicians rely on the International Prognostic Index to evaluate their lymphoma patients. This predictive index is based on clinical factors including age, tumor stage, and spread of disease. Although useful for some purposes, Staudt noted that the index has not been successful in identifying the best candidates for alternate therapies. "Based on variations in gene expression, we can now do a better job of predicting patient outcomes," he said.

As an example, Staudt explained that 32 of the 240 patients in the current study were classified in the group with the poorest prognosis according to the standard index. Of these, four were in fact cured by standard chemotherapy and gene expression had successfully identified each of them.

For those that don't respond to chemotherapy, alternatives are available. "For half of the patients with diffuse large B-cell lymphoma, conventional chemotherapy appears to be a reasonable option, but for patients in the poor-risk group, we have to consider other therapies," Staudt said. "One possibility for some patients would be a bone marrow transplant. There are also numerous clinical trials for which these patients may be eligible. "

Trials designed to correlate clinical results with molecular data will allow researchers to identify drugs that are effective in subgroups of cancer patients, an approach that has already proven effective in finding new agents to treat breast cancer and leukemia. Staudt said gene profiling will make it possible to obtain more information from clinical trials in the future. "It makes sense to get the maximum amount of information from patients' valuable participation in clinical trials," he said. "It's a better investment in the research for both doctors and patients."