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Gene chip helps doctor target cancer treatment


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By Maggie Fox

WASHINGTON (Reuters) - It looked bad for Chuck Fleming -- lung cancer had spread through his body. But his oncologist decided to try using a "gene chip" to see which out of a laundry list of chemotherapy options might work best.

Nine months later, Fleming is not cured, but he feels well enough to consider playing golf again and his targeted treatments -- a daily pill and a twice-monthly infusion -- do not make him feel weak and nauseated.

Dr. Eric Lester is convinced this personalized approach to treating cancer is the way to go in a world in which doctors now have dozens of drugs to choose from, every patient's tumor is different, and no one has any time to waste.

Lester wants to collaborate with other oncologists to build up a database of information about the various genetic mutations seen in tumors and match them to drugs that work the best against them. Cancer experts agree gene chips are the obvious way to do this.

"It is a smarter way to treat cancer," said Lester, of Oncology Care Associates in St. Joseph, Michigan.

Lung cancer is a serious killer -- only about 15 percent of patients live for five years or more.

Most have no symptoms until the tumors have spread, making a cure nearly impossible. This is what happened with Fleming, a 63-year-old automotive consultant.

"I was consulting in Mexico and my shoulder started to hurt and I started taking ibuprofen and a couple of tequilas," Fleming said in a telephone interview.

It took several consultations to discover he had not hurt his shoulder playing golf, but had lung cancer that had spread to his bones and his brain.

There are many options for treating lung cancer. Some are the new targeted therapies, which home in on specific genetic mutations.


They have fewer side-effects than chemotherapy. But they do not work on every tumor. Currently, doctors rely on their instincts and personal experience to choose the right ones.

Lester bought some Affymetrix gene chips -- small tiles of silicon that light up to show which genes are most active in a tissue sample.

He worked with Craig Webb of the Van Andel Research Institute in Grand Rapids, Michigan, who has a computer program for analyzing gene chips.

Scientists know a little about some of the genes that are over-active or under-active in cancer -- genes such as EGFR, which stimulates tissue growth.

But Lester discovered why it is not so straightforward to simply read a gene chip and choose a drug. For EGFR alone, there were nine different results, five suggesting a cancer-causing mutation but four others saying little.

A drug called Avastin targets EGFR, as does a pill called Tarceva. There were some other clues that Fleming's tumors might resist some standard chemotherapy drugs and not others.

"On that basis and recognizing that the man was faced with a very horrible disease, I chose to give him Tarceva up front," Lester said.

But to be safe he also gave Lester a standard, but toxic, chemotherapy combination.

"There are a lot of leaps of faith involved in looking at (gene) chip data and taking that to patient care, but as a practicing clinician I can't wait for 1,000 more experiments to be done," Lester said.

"This man would be dead if we didn't get lucky enough to find a chemotherapy regimen that would make him get better."

Lester presented data on Fleming and five other patients who tried his do-it-yourself gene analysis method to a meeting of the American Association for Cancer Research in Atlanta.

The chemotherapy made Fleming's hair fall out and he lost more than 100 pounds (50 kg) from his 300-pound frame. "It was like somebody was giving me poison. I would come home and the next day I would sit in the shower and throw up," Fleming said.

After Fleming's tumors shrank, Lester put him on Tarceva and Avastin alone.

"I have got a new life," Fleming said. "I am much happier at this stage in my life than I would have been being dead from cancer."

http://www.upmccancercenters.com/news/r ... icle=12611

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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.

In the new paradigm of requiring a companion diagnostic as a condition for approval of new targeted therapies, the pressure is so great that the companion diagnostics they’ve approved often have been mostly or totally ineffective at identifying clinical responders (durable and otherwise) to the various therapies.

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. Understanding “targeted” treatments begins with understanding the cancer cell.

If you find one or more implicated genes in a patient's tumor cells, how do you know if they are functional (is the encoded protein actually produced)? If the protein is produced, is it functional? If the protein is functional, how is it interacting with other functional proteins in the cell?

All cells exist in a state of dynamic tension in which several internal and external forces work with and against each other. Just detecting an amplified or deleted gene won't tell you anything about protein interactions. Are you sure that you've identified every single gene that might influence sensitivity or resistance to a certain class of drug?

Assuming you resolve all of the preceeding issues, you'll never be able to distinguish between susceptibility of the cell to different drugs in the same class. Nor can you tell anything about susceptibility to drug combinations. And what about external facts such as drug uptake into the cell?

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 culture 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.

It would be more advantageous to sort out what's the best "profile" in terms of which patients benefit from this drug or that drug. Can they be combined? What's the proper way to work with all the new drugs? If a drug works extremely well for a certain percentage of cancer patients, identify which ones and "personalize" their treatment. If one drug or another is working for some patients then obviously there are others who would also benefit. But, what's good for the group (population studies) may not be good for the individual.

Patients would certainly have a better chance of success had their cancer been chemo-sensitive rather than chemo-resistant, where it is more apparent that chemotherapy improves the survival of patients, and where identifying the most effective chemotherapy would be more likely to improve survival above that achieved with "best guess" empiric chemotherapy through clinical trials.

It may be very important to zero in on different genes and proteins. However, when actually taking the "targeted" drugs, do the drugs even enter the cancer cell? Once entered, does it immediately get metabolized or pumped out, or does it accumulate? In other words, will it work for every patient?

All the validations of this gene or that protein provides us with a variety of sophisticated techniques to provide new insights into the tumorigenic process, but if the "targeted" drug either won't "get in" in the first place or if it gets pumped out/extruded or if it gets immediately metabolized inside the cell, it just isn't going to work.

To overcome the problems of heterogeneity in cancer and prevent rapid cellular adaptation, oncologists are able to tailor chemotherapy in individual patients. This can be done by testing "live" tumor cells to see if they are susceptible to particular drugs, before giving them to the patient. DNA microarray work will prove to be highly complementary to the parellel breakthrough efforts in targeted therapy through cell function analysis.

As we enter the era of "personalized" medicine, it is time to take a fresh look at how we evaluate new medicines and treatments for cancer. More emphasis should be put on matching treatment to the patient, through the use of individualized pre-testing.

Upgrading clinical therapy by using drug sensitivity assays measuring "cell death" of three dimensional microclusters of "live" fresh tumor cell, can improve the situation by allowing more drugs to be considered. The more drug types there are in the selective arsenal, the more likely the system is to prove beneficial.

Source: Cell Function Analysis

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