April 14, 2007
4 Genes Targets Against Breast Cancer Spread
Some new research demonstrates how puzzling out the genetic mechanisms of cancer spread points in the direction of useful therapies.
Studies of human tumor cells implanted in mice have shown that the abnormal activation of four genes drives the spread of breast cancer to the lungs. The new studies by Howard Hughes Medical Institute researchers reveal that the aberrant genes work together to promote the growth of primary breast tumors. Cooperation among the four genes also enables cancerous cells to escape into the bloodstream and penetrate through blood vessels into lung tissues.
Although shutting off these genes individually can slow cancer growth and metastasis, the researchers found that turning off all four together had a far more dramatic effect on halting cancer growth and metastasis.
Each individual drug under development most often gets tested by itself to determine its effectiveness. Drug developers realize this means they miss useful drugs. But since thousands of drugs exist the task of choosing drugs to try in combination seems impossible. The number of combinations becomes too great if one has to choose sets of 2 or 3 or 4 drugs to test in combination. But as this report shows, genetic research can show that a group of genes drive development of a disease. This allows researchers to narrow their focus toward drugs that target each of those genes. Then the potential combinations of drugs to test shrinks down to a practically testable set and the likelihood of finding synergistic combinations of drugs goes up by orders of magnitude.
In this case the researchers were lucky because 2 of the 4 genes they identified already have existing drugs that target them.
In the newly published experiments, the researchers also found that they could reduce the growth and spread of human breast tumors in mice by simultaneously targeting two of the proteins produced by these genes, using drugs already on the market. The researchers are exploring clinical testing of combination therapy with the drugs—cetuximab (trade name Erbitux) and celecoxib (Celebrex)—to treat breast cancer metastasis.
Think about that. Other existing drugs might be useful in combinations against cancer and we simply do not yet have enough genetic research information to point ourselves toward them.
This work builds on previous work that identified 18 genes involved in cancer metastasis. They narrowed their focus to 4 of those 18.
In an earlier study, Massagué and his colleagues had identified 18 genes whose abnormal activity is associated with breast cancer's ability to spread to the lungs. In the new study published in Nature, Massagué and his colleagues at Sloan-Kettering, along with researchers from Hospital Clinic de Barcelona and the Institute for Research in Biomedecine in Spain, focused on four of these genes. These genes, which code for proteins called epiregulin, COX2, and matrix metalloproteinases 1 and 2, were already known to help regulate growth and remodeling of blood vessels, said Massagué.
Blood vessel growth is key for cancer growth. Dr. Judah Folkman at Harvard Medical School has spent his career demonstrating that genes and proteins involved in blood vessel formation (angiogenesis) are useful targets for anti-cancer treatments. Anti-angiogenesis drugs are now useful against some forms of cancer.
Separate tests of these drugs against cancer did not suggest that in combination they'd turn out useful.
Two drugs already on the market act directly on proteins produced by the genes Massagué's group had been studying. Cetuximab is an antibody that blocks the action of epiregulin and is used to treat advanced colorectal cancer. Celecoxib is an inhibitor of COX2 that is used as an anti-inflammatory, and is being tested in clinical trials against many types of cancer. The researchers also tested whether cetuximab and celecoxib would work effectively in concert to reduce metastasis in mice.
“We found that the combination of these two inhibitory drugs was effective, even though the drugs individually were not very effective," said Massagué. “This really nailed the case that if we can inactivate these genes in concert, it will affect metastasis,” he said.
Research into interacting sets of genes will point us toward many more drug targets for cancer and for other diseases as well. Improvements in technologies for gene chips and other tools for watching gene activity will speed up the rate at which scientists can identify, monitor, and tweak sets of genes involved in disease progression. Therefore the rate at which we find relationships between genes will accelerate. In the next 10 years I expect that every single gene involved in cancer growth and spread will become a target of drug development. Once we have drugs that target large sets of genes I expect many cancers to become controllable and some to become curable.
What we really need in order to cure all cancers are gene therapies that will go into cancer cells and fix some of the mutations that make cells become cancers. This research also helps work in that direction because it helps identify genes to target for gene therapy.
The Microvascularity Viability Assay
Anti-angiogenesis drugs work by blocking the activity of VEGF to prevent the growth of new capillaries into the tumor and thereby sustain tumor growth. VEGF causes angiogenesis by attaching to special receptors, and this action starts a series of chemical reactions inside the cell.
The ability of various agents to kill tumor and/or microvascular cells (anti-angiogenesis) in the same tumor specimen is highly variable among the different agents. There are so many agents out there now, doctors have a confusing array of choices. They don't know how to mix them together in the right order.
Avastin is a monoclonal antibody, a type of genetically engineered protein. Monoclonal antibodies are "large" molecules. These very large molecules don't have a convenient way of getting access to the large majority of cells. Plus, there is multicellular resistance, the drugs affecting only the cells on the outside may not kill these cells if they are in contact with cells on the inside which are protected from the drug. The cells may pass small molecules back and forth.
However, Vatalanib is a "small" molecule tyrosine kinase inhibitor with broad specificity that targets all VEGF receptors (VEGFR), the platelet-derived growth factor receptor, and c-KIT. It is a multi-VEGFR inhibitor designed to block angiogenesis and lymphangiogenesis by binding the intracellular kinase domain of all three VEGFRs, VEGFR-1 (Flt-1), VEGFR-2 (KDR/Flk-1), and VEGFR-3 (Flt-4). Vatalanib is a targeted drug that inhibits the activity of all known receptors that bind VEGF. The drug also potently inhibits angiogenesis.
Even with Vatalanib, do the drugs even enter the cell? Once entered, does it immediately get metabolized or pumped out, or does it accumulate? In some cases, these and other drugs, kill tumor cells without killing microvascular cells in the same time frame. In other cases they kill microvascular cells without killing tumor cells. In yet other cases they kill both types of cells or neither type of cells. The ability of these agents to kill tumor and/or microvascular cells in the same tumor specimen is highly variable among the different agents.
A major modification of the DISC (cell death) assay allows for the study of anti-microvascular drug effects of standard and targeted agents. This Microvascularity Viability Assay is based upon the principle that microvascular (endothelial and associated) cells are present in tumor cell microclusters obtained from solid tumor specimens. The assay which has a morphological endpoint, allows for visualization of both tumor and microvascular cells and direct assessment of both anti-tumor and anti-microvascular drug effect. CD31 cytoplasmic staining confirms morphological identification of microcapillary cells in a tumor microcluster.
The principles and methods used in the Microvascularity Viability Assay include: 1. Obtaining a tissue, blood, bone marrow or malignant fluid specimen from an individual cancer patient. 2. Exposing viable tumor cells to anti-neoplastic drugs. 3. Measuring absolute in vitro drug effect. 4. Finding a statistical comparision of in vitro drug effect to an index standard, yielding an individualized pattern of relative drug activity. 5. Information obtained is used to aid in selecting from among otherwise qualified candidate drugs.
A "fresh" sample tumor can be obtain from surgery or biopsy (Tru-cut needle biopsies). At least one gram of fresh biopsy tissue is needed to perfom the test, and a special kit must be gotten in advance from the lab. Arrangements have to be made with the surgeon and/or pathologist for preparation and sending of the specimen. Upgrading clinical therapy by using a drug sensitivity assay measuring "cell death" of three dimensional microclusters of live "fresh" tumor cells, can improve the conventional situation by allowing more drugs to be considered.
It is the only assay which involves direct visualization of the cancer cells at endpoint, allowing for accurate assessment of drug activity, discriminating tumor from non-tumor cells, and providing a permanent archival record, which improves quality, serves as control, and assesses dose response in vitro. Photomicrographs in the assay can show that some clones of tumor cells don't accumulate the drug. These cells won't get killed by it. Functional profiling in the assay measures the net effect of everything which goes on (Whole Cell Profiling). Are the cells ultimately killed, or aren't they?
Each of these new targeted drugs are not for everybody. According to the National Cancer Institute, those who benefit substantially from "targeted" drugs is approximately 10% to 20%. What if you are one of those few? This kind of technique exists today and might be very valuable, especially when active chemoagents are limited in a particular disease, giving more credence to testing the tumor first.
Source: Eur J Clin Invest, Volume 37(suppl. 1):60, April 2007
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’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.