Gene profiling predicts resistance to breast cancer drug Herceptin

Feb 20, 2007

Using gene chips to profile tumors before treatment, researchers at Harvard and Yale Universities found markers that identified breast cancer subtypes resistant to Herceptin, the primary treatment for HER2-positive breast cancer. They say this advance could help further refine therapy for the 25 to 30 percent of breast cancer patients with this class of tumor.

In the February 15 issue of Clinical Cancer Research, the researchers found that HER2-positive tumors that did not respond to Herceptin expressed certain basal markers, growth factors and growth factor receptors. One of these, insulin-growth factor receptor 1(IGF-1R), was associated with a Herceptin response rate that was half that of tumors that did not express IGF-1R.

They also discovered that resistant tumors continue to over-express the HER2 growth factor protein -- an important finding given that many scientists had thought that loss of HER2 was likely responsible for Herceptin resistance.

"Herceptin has revolutionized the care of HER2-positive breast cancer for many patients, but unfortunately, not for some. This work demonstrates that digging deeper into the molecular subtypes of these tumors helps us understand why some tumors are resistant and may point to ways to remedy that," said the study’s lead author, Lyndsay Harris, M.D., associate professor and Director of the Breast Cancer Disease Unit at Yale University Medical Center.

If additional studies validate these findings, it may be possible to select those patients that will be resistant to Herceptin and treat them with additional drugs to restore Herceptin sensitivity, according to Harris. "Our goal is to see what the tumor tells us before any treatment starts and tailor therapy accordingly," she said.

To determine Herceptin sensitivity, investigators took a small tumor biopsy from 48 patients with newly diagnosed and operable stage II/III breast cancer. They examined the biopsy tissue using both single and multi-gene microarrays, looking for RNA that has been activated to produce proteins.

They then treated the women with a combination of Herceptin and the chemotherapy drug Navelbine weekly for 12 weeks. Although this is not the first study to test Herceptin use before surgery, it is the first to examine the use of Navelbine, a drug approved for lung cancer treatment, in combination with Herceptin to treat HER2-positive tumors. "We were motivated to use Navelbine because we found it has few side effects when used to treat metastatic breast cancer," said Harris, who conducted much of the research study at Harvard before moving to Yale.

After treatment, the tumors were surgically removed and gene chips were again used to examine RNA transcription -- making these investigators the first to use such a technique on Herceptin treated tumors. "This kind of profiling has been done to look at response to chemotherapy drugs, but not at Herceptin resistance," Harris said.

The researchers then divided tumors into groups depending on how well they responded to therapy, and examined the baseline and post-therapy RNA profiles to find genes that were more commonly expressed in Herceptin sensitive and Herceptin resistant tumors.

They first found that some single gene markers, such as HER2 and ER (estrogen receptor), did not change in the majority of tumors. "That tells us that the cancer cells are still creating HER2 surface proteins even as Herceptin is being used, and that means HER2 loss does not appear to be a mechanism of resistance in early stage breast cancer," Harris said.

Then, using multigene chips, the researchers derived a bevy of transcribed genes that likely play a role in Herceptin resistance. Some, such as IGF-1R, were suspected, because this protein is frequently over-expressed in breast tumors, Harris says, but others were not. For example, non-responding tumors were more likely to express genes associated with basal-like breast cancer, which the researchers found to be surprising. "Most basal-like tumors are HER2-negative," Harris said.

Herceptin resistant tumors were also more likely to express a variety of growth factors, suggesting that "activation of parallel pathways may release tumors from dependence on HER2 proliferation and survival," she said.

Although the study was not designed to look at outcome, the researchers determined that 42 of 48 patients had a clinical response (16 complete responses and 26 partial responses) from the neoadjuvant treatment, and five patients experienced cardiotoxicity. After a median 2.6-year-follow-up, three of 48 patients relapsed and one died of her disease.

Source: American Association for Cancer Research

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gdpawel
not rated yet Jan 10, 2008
What is the Clinical Relevance of Gene Profiling?

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%u2019ve 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 %u201Ctargeted%u201D 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.