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Genetic analysis of glioblastoma brain tumors can aid in treatment decisions

10.11.2005


Screening glioblastoma brain tumors for two gene variations can reliably predict which tumors will respond to a specific class of drugs, a new study shows. The findings may lead to improved treatment for this devastating disease. The study was funded in part by the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health (NIH), and appears in the November 10, 2005, issue of the New England Journal of Medicine.*



Glioblastomas are the most common malignant brain tumors in adults, and they are notoriously difficult to treat successfully. "The survival with glioblastoma is usually a year on average, and that hasn’t improved in a while, so this is a very serious and challenging disease," says Paul Mischel, M.D., of the David Geffen School of Medicine and Jonsson Comprehensive Cancer Center at the University of California, Los Angeles (UCLA), who led the study. While drugs are available to help treat glioblastoma, they often have minimal effect, and doctors usually have time to try only one or two treatments before the disease causes severe impairment. Glioblastomas feature many genetic variations that affect their response to different treatments. Researchers are trying to identify these genetic factors and to tease apart how they affect the disease in order to determine which patients are the most likely to benefit from specific drugs.

In the new study, Dr. Mischel and his colleagues performed genetic analysis on tissue from recurrent malignant glioblastoma patients, 26 of whom responded either very well or very poorly to the drugs erlotinib (Tarceva®) and gefitinib (Iressa®). These two drugs belong to a class called EGFR (epidermal growth factor receptor) kinase inhibitors, and both are currently approved by the by the U.S. Food and Drug Administration (FDA) to treat advanced lung cancer that has not responded to other treatments.


Based on results from other studies, the researchers hypothesized that variations in several different genes might play a role in the tumor’s response to EGFR inhibitors. They looked for mutations in genes called EGFR and HER2/neu, and they analyzed the activity of EGFR, an EGFR variant called EGFRvIII, and a gene called PTEN. Many tumors – not just brain tumors – have mutations or abnormal activity of one or more of these genes, which help to control cell growth and other functions.

Glioblastomas that produced both EGFRvIII and PTEN were 51 times more likely to shrink when treated with EGFR inhibitors than tumors without this combination of proteins, the researchers found. Patients whose tumors expressed these proteins and who received an EGFR inhibitor went almost 5 times longer on average before their tumors progressed (243 days vs. 50 days) than those whose tumors did not express both of the proteins. In contrast, EGFR and HER2/neu activity had no effect on how tumors responded to these drugs. Similar results were found in tissues from another group of 33 glioblastoma patients who had taken part in a clinical trial of erlotinib at the University of California, San Francisco.

The findings suggest that both EGFRvIII and PTEN proteins are important for tumors to be susceptible to EGFR inhibitors, Dr. Mischel says. Their data further suggest that EGFRvIII may act to sensitize glioblastoma cells, while PTEN loss may act as a resistance factor. The researchers tested their results in several different cell models and repeatedly found that expression of these two proteins made the cells sensitive to EGFR inhibitors and that PTEN loss promoted resistance in those models.

The study shows that genetic analysis of glioblastomas can predict the tumors’ sensitivity to specific drugs. Adjusting treatment based on each tumor’s genetic activity could significantly prolong life for a subset of glioblastoma patients, Dr. Mischel says. It also may prevent patients from undergoing unnecessary and expensive treatments, and it could allow some people to be treated with the most effective therapy immediately, before the tumors can grow and develop new mutations that make them more difficult to treat.

Kinases are enzymes that play key roles in cell proliferation, metabolism, and other functions, and they are often overactive in cancer cells. Because cancer cells may become dependent on the persistent signals created by altered kinases in a way in which non-cancerous cells do not, kinase inhibitors such as EGFR inhibitors can often target cancer cells without seriously affecting the rest of the body. Therefore they cause fewer side effects than most other cancer drugs. The drug imatinib (Gleevec®), which is FDA-approved to treat chronic myeloid leukemia, is one of the early success stories for this kind of treatment.

The study also reveals important information about how glioblastomas and other tumors develop, Dr. Mischel says. Knowing that EGFRvIII and PTEN play critical roles in tumor response to treatment could lead to new combination therapies that target both proteins. Such therapies might also be beneficial for other types of cancer.

Screening for these factors also might allow researchers to better determine a treatment’s effects in clinical trials, Dr. Mischel adds. Traditional clinical trials that do not take into account each tumor’s genetic makeup often fail to show enough of an effect to warrant FDA approval for a drug because only a subset of patients respond well to the treatment.

The researchers are now planning prospective clinical trials to determine whether selecting treatment based on each tumor’s genetic activity can lead to better patient survival. They also plan to continue looking for other tumor susceptibility factors, to develop new treatments that target those factors, and to try to learn how some patients become resistant to treatment. Researchers also need to develop their genetic screening techniques into a diagnostic test so that it can be available to all people with glioblastoma, Dr. Mischel says.

Natalie Frazin | EurekAlert!
Further information:
http://www.ninds.nih.gov/

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