April 2005

Researchers develop 'genetic blueprint' to predict response to esophageal cancer treatments

ANAHEIM - For the first time, researchers appear to be able to use a comprehensive panel of genetic variants to predict how a patient with esophageal cancer will respond to a spectrum of cancer treatments.

At the annual meeting of the American Association for Cancer Research (AACR), researchers from The University of Texas M. D. Anderson Cancer Center report that six different gene variants can predict an improved outcome in patients treated with two different chemotherapy drugs and/or with radiation therapy.

For example, the researchers say that a combination of several gene variants in patients treated with one type of chemotherapy (5-FU) more than doubled survival to 51 months, compared to 25 months in patients treated with the same drug who did not have these variants.

They say the findings represent a leap forward in the goal to provide tailored therapy to individual patients because it offers a genetic blueprint for gauging the potential effectiveness of all common esophageal cancer treatment, not just an analysis of how one or two "candidate" genes respond to a single treatment.

"Our data strongly suggest that combined pathway-based analysis may provide powerful clinical outcome predictors for esophageal cancer as well as for other cancers," says the study's lead author Xifeng Wu, M.D., Ph.D., a professor in the Department of Epidemiology.

"This points to a promising new direction for cancer pharmacogenetics," she says. "Our hope is to have a gene chip one day that can analyze a patient's genetic makeup and help physicians predict response to a wide variety of therapeutic drugs before treatment even begins."

Esophageal cancer is highly aggressive; approximately 14,520 new esophageal cancer cases and 13,570 associated deaths are expected in 2005, according to the American Cancer Society. Almost half of new cases are diagnosed at an advanced stage, when the five-year survival rate is just 14 percent. Surgery is offered to most patients, as well as one or all of the following treatments - an anti-metabolite chemotherapy agent (5FU), an alkylating agent (cisplatin) and radiation treatment.

Knowing that variations exist in how a person biologically processes those therapies, the researchers collected tissue samples from 210 esophageal cancer patients. They then developed a "pathway analysis" that examined variants in 40 different genes believed to be involved in metabolism, DNA damage repair activity and action of these of therapies. Next, they compared differences in gene variants with outcomes in patients.

"This was like putting together a recipe, searching for different ingredients that work well together for patients," Wu says.

They found that patients with the best outcomes were those who had gene variants that were less effective at neutralizing the killing power of the cancer treatments. Conversely, patients whose genes efficiently counteracted chemotherapy and radiation treatment had shorter survival times overall.

Findings include:



The researchers also discovered an additive effect between these genes and others that conferred smaller advantages. The higher the number of beneficial variants the patient had, the longer survival was, they found.

As promising as the study is, significant hurdles remain before these findings can be incorporated into treatment, Wu says. Because more data are needed to support their findings, the investigators are accumulating a cohort of 800 esophageal patients from which they can draw a comprehensive genetic profile using blood samples.

If successful, such pathway-based analyses can be conducted for the wide variety of cancers that are treated with 5FU, cisplatin and radiation, as well as other drug treatments, Wu says.

The study was funded by grants from the National Cancer Institute and an M. D. Anderson Cancer Center Multidisciplinary Research Program for esophageal cancer. Jaffer Ajani, M.D., a professor of Gastrointestinal Medical Oncology, is the study's lead clinical collaborator.