Breast Cancer Patients Could Receive Wrong Treatment Because Of Errors In Widely Used Lab Tests
Main Category: Breast CancerAlso Included In: Public Health
Article Date: 08 Jan 2008 - 7:00 PDT
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The Wall Street Journal on Friday examined the efficacy of two diagnostic tests used to determine which drugs to prescribe women with invasive breast cancer. According to the Journal, thousands of women with breast cancer might be receiving the wrong treatment because of errors in the two tests predominantly used to determine which drugs to prescribe. The test requires pathologists to make subjective calls after analyzing tissue with a microscope, the Journal reports.
One test examines whether a woman's tumor cells have too much of the HER2 protein. If the cells do contain too much HER2, patients are prescribed Genentech's drug Herceptin. The other test checks for the presence of cell proteins that act as receptors for the hormones estrogen or progesterone, the Journal reports. If the cell proteins are detected, physicians usually prescribe drugs such as tamoxifen, which blocks the production of the hormones.
According to the Journal, recent studies have found that there is a "potential snag" for these cancer-fighting drugs -- which drug should be prescribed depends upon accurate lab tests. Both pathologists and oncologists said labs inexperienced in a particular test might not understand how small variations in procedure -- such as how much tissue samples are heated and what preservative is used -- can impact results. Lee Newcomer, senior vice president of UnitedHealth Group, said, "We all make the assumption that every test is done well. It turns out it's not a correct assumption." Several private insurers -- including UnitedHealth, Aetna and WellPoint -- say that in general, they will pay for second-opinion breast cancer tests. However, Newcomer said that even though UnitedHealth covers a second test, few physicians order them.
In addition, a study published in 2006 and led by researchers at Genentech on HER2 tests found that 14% to 16% of women judged to be HER2-positive actually were negative for the protein. Of the women said to be negative, 18% to 23% were actually HER2-positive, the study found. The American Society of Clinical Oncology estimates that around 20% of HER2 testing might be inaccurate. In a separate study published online in August 2007 in the Journal of Clinical Oncology, researchers examined the accuracy of labs in various countries. The study found that 70% of 105 women who initially tested negative for the protein that acts as a receptor for estrogen were found to be positive when the tissue was retested by an experienced lab, while the positive tests were almost always correct.
Barry Straube, chief medical officer at the Centers for Medicare and Medicaid Services, said the agency is examining stricter quality-control requirements. Labs currently must pass outside proficiency checks on 83 types of tests, which do not include tests for breast cancer, the Journal reports. CMS is "considering adding additional tests," Straube said, adding the two breast cancer tests are likely candidates. The College of American Pathologists also plans to require proficiency checks this year from the labs it oversees that offer the HER2 test (Mathews, Wall Street Journal, 1/4).
Reprinted with kind permission from http://www.nationalpartnership.org. You can view the entire Daily Women's Health Policy Report, search the archives, or sign up for email delivery here. The Daily Women's Health Policy Report is a free service of the National Partnership for Women & Families, published by The Advisory Board Company.
© 2007 The Advisory Board Company. All rights reserved.
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What Is The Clinical Relevance Of Gene Profiling?
posted by Gregory D. Pawelski on 20 Jan 2008 at 7:01 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.
Literature Citation: Eur J Clin Invest 37 (suppl. 1):60, 2007
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