BOSTON—Gene expression profiling may help predict survival outcomes for patients with diffuse large B-cell lymphoma (DLBCL), the most common lymphoid malignancy, according to a study reported by Margaret Shipp, MD, director of the Lymphoma Program at Dana-Farber Cancer Institute in Boston. In the study, gene expression profiling was able for the first time to identify curable and noncurable lymphomas from a pool of intermediate-risk patients.
"Using gene expression profiling is a powerful way of understanding the biological basis of lymphoma, and assessing differences in outcomes among patients," Dr. Shipp said. The study also identified individual genes and molecular mechanisms that could play a part in the development of incurable lymphoma.
In the future, such discoveries could help target therapies to cancer patients based on their molecular profiles, and help develop novel molecular targets for medications, Dr. Shipp predicted.
Stratifying Risk
While 40% of DLBCL patients are cured of their disease, the majority ultimately succumb to progressive lymphoma. In the past few years, studies have looked at the cellular and molecular basis of the disease using RNA expression profiling. The goal is to understand the disease more completely, and determine the prognosis for individual patients in order to treat them more successfully.
In the 5-year study, genetic material from the tumors of 58 DLBCL patients were subjected to RNA expression profiling. In this technique, fluorescently labeled RNA from a tumor specimen is used to probe a gene chip to determine which genes the cancer cells express. Patterns of gene expression in various tumor specimens are compared using a variety of computerized tools.
A review of 6,817 genes from the tumors of the DLBCL patients identified two categories of patients with dramatically different 5-year overall survival rates of 72% vs 9%. Patients included those in low-, intermediate-, and high-risk groups. Thirty patients had achieved complete remissions, 23 had died of lymphoma, 2 had died of other causes, and 3 had recurrent refractory disease.
Most significantly, the researchers were able to separate intermediate-risk patients into two discrete groups, who also had widely varying survival rates of 71% vs 7% based on their genetic profiles. Since most DLBCL patients fall into the intermediate-risk group, such categorization can be tremendously valuable in planning therapy, Dr. Shipp said.
Several Methods Work
"We used several different algorithms to achieve our results," Dr. Shipp explained. These included a weighted voting prediction algorithm and a support vector machine algorithm. All methods used were similarly predictive of disease outcome. "The value of using several different algorithms is that we now know that more than one method works to identify curable and deadly lymphomas," Dr. Shipp said.
The algorithms also allowed identification of a number of genes that were commonly underexpressed or overexpressed in fatal vs curable tumors. These genes had functions that influenced mechanisms like cell adhesion, apoptosis, ras signaling, and immunity to tumors.
"Once we identify genes that are expressed in curable vs noncurable tumors, we can find the genetic or molecular pathways that might be sensitive to standard treatments," Dr. Shipp said. "We might also find ways to interrupt molecular pathways that contribute to fatal outcomes."
The study was a collaborative effort among Dana-Farber Cancer Institute and Brigham and Women’s Hospital in Boston, the Whitehead Institute in Cambridge, Massachusetts, and St. Bartholomew’s Hospital in London.
