Inaccurate Lab Tests Might Lead To Inappropriate Treatment Of Breast Cancer
Main Category: Breast CancerArticle Date: 07 Jan 2008 - 7:00 PDT
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Thousands of breast cancer patients might receive improper medications as a result of inaccurate results for two laboratory tests used to determine the most effective treatments for specific patients, the Wall Street Journal reports. According to the Journal, pharmaceutical companies are "trying to develop more medicines tailored to the individual characteristics of patients and their diseases," but recent studies that have found "problems in testing point to a potential snag for such drugs: They depend on accurate lab results."
The tests used to determine the most effective treatments for specific breast cancer patients are "less straightforward than many traditional lab procedures" and "require pathologists to make judgment calls after looking at tissue through a microscope, rather than giving simple yes-or-no answers," the Journal reports. One of the tests determines whether breast cancer patients have excessive amounts of the protein Her-2 present in their tumors, an indication that they would benefit from Herceptin, manufactured by Genentech.
The second test determines whether breast cancer patients have cell proteins that serve as receptors for estrogen and progesterone -- which can help tumors grow -- an indication that they would benefit from tamoxifen to suppress or block the hormones.
Study
A 2006 study conducted by Genentech examined test results from local labs nationwide and found that the labs reported false positives for Her-2 tests 14% to 16% of the time and reported false negatives 18% to 23% of the time. In addition, the College of American Pathologists and the American Society of Clinical Oncology estimate that labs might report inaccurate results for Her-2 tests 20% of the time.
Allen Gown, chief pathologist of PhenoPath Laboratories, said, "If we tried to market pregnancy tests with this rate of inaccuracy, they would be taken off the market," adding, "It means there are a lot of women being treated inappropriately."
According to the Journal, concerns about the accuracy of the tests "could add momentum to efforts by Congress and consumer groups to push for increased oversight over the lab-testing business, which is booming because of factors such as the rise in genetic testing and the aging of the baby boom generation." CMS, which regulates labs, has required them to demonstrate proficiency in 83 types of tests since 1992.
Barry Straube, chief medical officer at CMS, said that the agency might add to the list of additional tests, such as those used to determine the most effective treatments for specific breast cancer patients (Wilde Mathews, Wall Street Journal, 1/4).
Reprinted with kind permission from http://www.kaisernetwork.org. You can view the entire Kaiser Daily Health Policy Report, search the archives, or sign up for email delivery at http://www.kaisernetwork.org/dailyreports/healthpolicy. The Kaiser Daily Health Policy Report is published for kaisernetwork.org, a free service of The Henry J. Kaiser Family Foundation© 2005 Advisory Board Company and Kaiser Family Foundation. All rights reserved.
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What Is The Clinical Relevance Of Gene Profiling?
posted by Gregory D. Pawelski on 18 Feb 2008 at 6:07 pmThe 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 "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.
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.
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