Personalized Cancer Care Off to Slow Start

[gpawelski]

It was hoped some day that Genomic Analyses of cancer tumors would be able to identify in advance which patients will benefit from use of cancer drugs (clinical responders). A new draft report from the Agency for Healthcare Research and Quality (AHRQ) suggests that day is still a ways off.

The study looked at whether the presence of specific mutations in people who had breast and colon cancer and chronic myeloid leukemia determined if patients would respond to expensive new drugs commonly used to fight the diseases. Only in colon cancer did the mutation matter and in that case, while it ruled out the effectiveness of drug therapy, the relevant mutation only appears in a small percentage of cases.

In the finding most likely to cause controversy, the AHRQ report found there was "no consistent associations" between breast cancer patients with the relevant CYP2D6 polymorphism and the outcome of tamoxifen therapy, whether as primary treatment or in as post-operative adjuvant therapy. Estimates vary, but anywhere from 10 to 40 percent of women have the gene variant of CYP2D6 that is believed to slow the metabolism of tamoxifen and make it less effective. A number of companies sell a $300 test that can show if women have the allegedly telltale CYP2D6 polymorphism.

As is often the case, the 13 studies identified by the systematic review didn't contain enough data to draw definitive conclusions. "Most studies were relatively small and thus underpowered to detect what would be a plausible effect size for the modification of response to tamoxifen by a single polymorphism," the report noted.

Numerous studies in recent years have noted that colon cancer patients with the KRAS mutation do not respond to epidermal growth factor receptor inhibitors like cetuximab (Imclone Systems/Bristol Myers Squibb's Erbitux) and panitumumab (Amgen's Vectibix). The Food and Drug Administration, the European Medicines Agency and the American Society of Clinical Oncology have issued guidelines suggesting patients with the mutation shouldn't be given the drugs.

The AHRQ-sponsored review confirmed that finding. "Patients with KRAS mutations were less likely to experience treatment benefit, compared to patients whose tumors were wild-type for KRAS mutations," the report said. About 20 percent of patients have KRAS mutations, which generally signal a more virulent form of the disease.

Chronic myeloid leukemia is one of the great success stories for targeted chemotherapy drugs and imatinib (Novartis' Gleevec) has been a godsend for patients with CML since it came on the market a decade ago. But resistance is growing, and at least two similar drugs are now on the market, dasatinib (Bristol-Myers' Sprycel) and nilotinib (Novartis' Tasigna).

Some mutations of the BCR-ABL1 gene make the cancer resistant to imatinib (Gleevec), which is designed to block the action of the hyperactive tyrosine kinase receptors in people with CML. But don't look to any tests currently on the market to determine what they are. The review of 31 studies found that "the presence of any BCR-ABL1 mutation does not appear to predict differential response to treatment in CML patients treated with imatinib-, dasatinib- (Sprycel), or nilotinib- (Nilotinib) based regimens."

Indeed, the report said there is "no evidence that presence of any BCR-ABL1 mutation can differentiate response to tyrosine kinase inhibitor therapies."

"It is possible that pharmacogenetic (how our inherited genes affect the way we respond to drugs) testing and the subsequent use of targeted therapies will add cost without producing clinically meaningful improvements in patient outcomes," the report said.

http://www.ahrq.gov/clinic/ta/pharmgentest.pdf

Source: Gooznews on Health

There are some challenges in the development and practical use of pharmacogenomics. Many doctors now do not widely practice pharmacogenomics when treating patients since the field is still new.

Pharmacogenetic testing is also expensive, and insurance plans may not cover the costs of available tests. Researchers are working to develop more efficient and less expensive testing methods.

Although federal legislation has been passed that makes it illegal for companies and insurers to discriminate against people based on their genetic information, some ethical, legal, and privacy issues remain unresolved, which may affect the continued development of pharmacogenomics.

[gpawelski]

I can empathsize with the frustration. Nothing was presented at the 2009 American Society of Clinical Oncology (ASCO) breast cancer symposium, in San Francisco, reporting any progress at all in drug selection through the use of molecular profiling.

Little progress has been made in identifying which therapeutic strategies are likely to be effective for individual patients. Identifying markers that can predict response to a particular drug remains a great challenge.

When microarrays and high throughput RT-PCR emerged some years back, you'd think that there would be quite a bit of progress by now. Sad to say, there has not.

However, a study was presented at the symposium about progress in drug selection through the use of cell-based functional profiling.

The data presented clearly showed the utility of cell culture assays in “targeting” chemotherapy to patient sub-groups who are most likely to benefit from treatment with given individual drugs.

Genomics is far too limited in scope to encompass the vagaries and complexities of human cancer biology when it comes to drug selection. Efforts to administer targeted therapies in randomly selected patients often result in low response rates at significant toxicity and cost.

All the mutation or amplification studies can tell us is whether or not the cells are "potentially" susceptible to this mechanism of attack. They don't tell you if one targeted drug or another targeted drug is worse or better than the other or some other drug which may target this.

The cell is a system, an integrated, interacting network of genes, proteins and other cellular constituents that produce functions (processes). It would be a benefit to analyze the systems’ response to drug treatments, not just one target or pathway.

While researchers continue to develop molecular probes to select candidates, the cell culture analysis platform serves as a functional profile capable of examining the nuances of cellular response to drugs. To exploit the full potential of targeted anticancer therapies, physicians will need laboratory tests that match patients to specific drugs.

Cell culture assays are able to accurately predict how an individual patient's cancer cells will respond to an array of drug combinations. It is able to quantify synergistic drug combinations and individually tailor treatment.

[gpawelski]

According to government researchers, genetic tests designed to predict how well lung cancer patients will fare after treatment do very little to guide doctors. Their review of studies aiming to show a gene signature for lung tumors found serious problems in the design and analysis of the studies.

Jyothi Subramanian and Richard Simon of the National Cancer Institute in Bethesda, Maryland say that researchers need some clear guidelines to follow in what is becoming a booming industry of using genes to predict who needs more treatment.

"None of the studies reviewed were successful in showing clear usefulness for the gene expression signatures over and above the known risk factors," they wrote in the Journal of the National Cancer Institute.

Researchers hoped to be able to use DNA sequences to predict risk of disease, to help choose the best drug for a patient, and to follow how well patients are doing on various therapies.

However, so many different stretches of DNA are involved in disease that experts say it will take years to sort out. And there is no clear agreement on how to design studies to show whether such tests predict what they are supposed to.

Subramanian and Simon reviewed 16 studies published from 2002 to 2009 on tests looking for active genes in non-small cell lung tumors that would predict whether a patient's tumors would return or spread.

Diagnosing lung cancer is tricky. At Stage I, before the tumor has spread, surgery can get the tumor, if the surgeon can get to it without destroying the lung. Most patients are not diagnosed until Stage IV, when the cancer has spread throughout the body, because symptoms are vague.

In between, it is hard to assess how much the tumor has spread and whether a patient would benefit from chemotherapy.

Even when a surgeon gets all the tumor and patients are designated as stage IA, meaning no spread, 30 percent of the patients relapse. So the pressure is on for a way to test the tumor to predict who needs extra treatment.

But none of the tests so far do this adequately, Subramanian and Simon said. And most of the studies did not even take into account known risk factors, such as whether the edges of the tumor looked fuzzy, they said.

"Hence, we again emphasize the fact that care must be taken to collect and use as much clinical information about patients as possible when developing prognostic signatures," they concluded.

Source: MedlinePlus U.S. National Library of Medicine

[gpawelski]

Medical research has focused a great deal on developing DNA (genomic) tests to identify various gene expressions, markers and mutations relevant to a person’s cancer. The hope is that genetic information will enable researchers to better predict how an individual will respond to various treatment options.

However, when it comes to predicting the best treatment for the individual, unlocking the complexities of a person’s DNA is not the answer, it is simply a starting point. In fact, a March 16, 2010 study in the Journal of the National Cancer Institute looked at the value of various gene tests and concluded none of the studies showed a clear usefulness.

Genomic tests provide lots of information about a patient’s genes. However, as the Journal article points out, there are so many sequences in our DNA which influence disease, that attempting to unravel such complexity just produces more and more information without a particularly useful benefit. While genes may provide a recipe, they do not determine the end results and cannot predict how an individual will respond to a specific treatment.

Like the various influences on a flower seed that cause one blossom to turn out differently from another, there are biological processes in the body that affect the development of cancer in each patient and determine how that patient’s cancer cells will uniquely react to treatment.

Despite its allure, the “genetic" path is not all that personalized. Treatment based on genetic testing is still a guessing game. Only a treatment regimen based on a “functional profile” – a real-time test of chemotherapy on the actual cancer tissue – can predict with accuracy an individual’s response to chemotherapy.