Gene Chip Data Improved Therapy In Some Patients

[Christine]

Source: American Association for Cancer Research

Gene Chip Data Improved Therapy In Some Patients With Incurable Cancer

Science Daily — Like many oncologists, Eric P. Lester, M.D., was faced with a dilemma: seven patients with advanced, incurable cancer, an arsenal of drugs that may or may not help them, and not enough solid proof about treatment efficacy to guide him.

So Dr. Lester devised what he called a "simple-minded experiment" that illustrates the promise of personalized medicine. Using DNA microarray "chips," Dr. Lester analyzed his patients' tumors for expression of genes associated with good response to various anti-cancer drugs, and based his drug treatment plans on the results. Four out of seven patients with advanced cancer enrolled in the extremely limited study had a better outcome than expected.

The finding shows that "a personalized molecular oncology approach, basing chemotherapy on relative gene expression in tumors, holds promise even at the relatively crude level employed here," said study investigator, Dr. Lester, president of Oncology Care Associates in St. Joseph, Mich.

To obtain and analyze chip data, Dr. Lester worked with Craig Webb, Ph.D., Director of Translational Medicine at the Van Andel Research Institute in Grand Rapids, Mich.

The study is unusual because oncologists don't yet base most of their treatment decisions on gene profiling, especially when it might involve pairing drugs together in a novel combination or using varied doses, Dr. Lester said. "Much of clinical medicine is an educated guess, and this was an attempt to come up with a better approach by using the technology of a gene chip to make multiple, highly educated guesses simultaneously," Dr. Lester said.

Dr. Lester added that one of the seven participating patients died before the gene chip was used to direct therapy.

Many current clinical trials involving gene expression examine effectiveness markers for individual drugs rather than combinations of drugs or different doses of agents used together for the first time. To truly help the most patients, Dr. Lester said, all potentially effective drugs and combinations must be matched up against the unique genetic profile of a patient's tumor, he said.

"Effective cancer treatment depends on understanding the biology driving the cancer, but because each tumor is different, it is very hard to personalize care and do a rigorous scientific experiment at the same time."

In this study, Dr. Lester said he "stayed within the envelope of a reasonable standard of care" in treating his patients. That standard is often based on what insurance companies will typically reimburse for treatment given published studies about the effectiveness of a drug on a certain tumor type, and whether or not the drug is federally approved for that indication. Dr. Lester and Webb surveyed the scientific literature and compiled a list of genes whose expression levels may predict response to a drug given the tumor type.

In some cases, treatment strategies suggested by the chips varied significantly even for the same type of cancer. For example, one patient whose lung cancer had spread to his brain and bones achieved a "near complete response" when treated with two chemotherapy drugs, in addition to Tarceva and Avastin, while another lung cancer patient responded to third-line drugs such as etoposide.

Acknowledging the risk involved with using novel combinations of drugs where no set safety profile exists, Dr. Lester said that "this is constantly done in medicine. People are taking antibiotics at the same time as using heart and cholesterol pills, and blood pressure medication."

"This kind of polypharmacy will become more common in cancer, but at the moment, it is hard to figure out the difference between doses that are effective or that could be toxic," he said.

The best way to get around such issues is to build a database of gene expression data and match them with patient outcomes, he said. "Now when I see new patients I am itching to look at what the genes can tell me," Dr. Lester said. "It is a smarter way to treat cancer."

This finding was presented in Atlanta, Ga. at the American Association for Cancer Research's second International Conference on Molecular Diagnostics in Cancer Therapeutic Development.

Note: This story has been adapted from a news release issued by American Association for Cancer Research.

[gpawelski]

The Microarray (gene chips) is a device that measures differences in gene sequence, gene expression or protein expression in biological samples. Microarrays may be used to compare gene or protein expression under different conditions, such as cells found in cancer.

Hence the headlong rush to develop tests to identify molecular predisposing mechansims whose presence still does not guarantee that a drug will be effective for an individual patient. Nor can they, for any patient or even large group of patients, discriminate the potential for clinical activity among different agents of the same class.

Genetic profiles are able to help doctors determine which patients will probably develop cancer, and those who will most likely relapse. However, it cannot be suitable for specific treatments for "individual" patients.

Cancer cells often have many mutations in many different pathways, so even if one route is shut down by a targeted treatment, the cancer cell may be able to use other routes. Targeting one pathway may not be as effective as targeting multiple pathways in a cancer cell.

Another challenge is to identify for which patients the targeted treatment will be effective. Tumors can become resistant to a targeted treatment, or the drug no longer works, even if it has previously been effective in shrinking a tumor. Drugs are combined with existing ones to target the tumor more effectively. Most cancers cannot be effectively treated with targeted drugs alone.

Gene profiling tests, important in order to identify new therapeutic targets and thereby to develop useful drugs, are still years away from working successfully in predicting treatment response for "individual" patients. Perhaps this is because they are performed on dead, preserved cells that were never actually exposed to the drugs whose activity they are trying to assess.

It will never be as effective as the cell "function" method, which exists today and is not hampered by the problems associated with gene expression tests. That is because they measure the net effect of all processes within the cancer, acting with and against each other in real time, and it tests living cells actually exposed to drugs and drug combinations of interest.

The key to understanding the genome is understanding how cells work. The ultimate driver is a "functional" assay (is the cell being killed regardless of the mechanism) as opposed to a "target" assay (does the cell express a particular target that the drug is supposed to be attacking). While a "target" assay tells you whether or not to give "one" drug, a "functional" assay can find other compounds and combinations and can recommend them from the one assay.

The core of the functional assay is the cell, composed of hundreds of complex molecules that regulate the pathways necessary for vital cellular functions. If a "targeted" drug could perturb any one of these pathways, it is important to examine the effects of the drug within the context of the cell. Both genomics and proteomics can identify potential new therapeutic targets, but these targets require the determination of cellular endpoints.

Cell-based functional assays are being used for screening compounds for efficacy and biosafety. The ability to track the behavior of cancer cells permits data gathering on functional behavior not available in any other kind of assay.

Source: Cell Function Analysis