The False Economy of Genomic Analyses

We are witness to a revolution in cancer therapeutics. Targeted therapies, named for their capacity to target specific tumor related features, are being developed and marketed at a rapid pace. Yet with an objective response rate of 10 percent (Von Hoff et al JCO, Nov 2011) reported for a gene array/IHC platform that attempted to select drugs for individual patients we have a long way to go before these tests will have meaningful clinical applications.

So, let’s examine the more established, accurate and validated methodologies currently in use for patients with advanced non-small cell lung cancer. I speak of patients with EGFR mutations for which erlotinib (Tarceva®) is an approved therapy and those with ALK gene rearrangements for which the drug crizotinib (Xalkori®) has recently been approved.

The incidence of ALK gene rearrangement within patients with non-small cell lung cancer is in the range of 2–4 percent, while EGFR mutations are found in approximately 15 percent. These are largely mutually exclusive events. So, let’s do a “back of the napkin” analysis and cost out these tests in a real life scenario.

One hundred patients are diagnosed with non-small cell lung cancer.
•    Their physicians order ALK gene rearrangement     $1,500
•    And EGFR mutation analysis     $1,900
•    The costs associated $1,500 + $1,900 x 100 people =    $340,000
Remember, that only 4 percent will be positive for ALK and 15 percent positive for EGFR. And that about 80 percent of the ALK positive patients respond to crizotinib and about 70 percent of the EGFR positive patients respond to erlotinib.

So, let’s do the math.

We get three crizotinib responses and 11 erlotinib responses: 3 + 11 = 14 responders.
Resulting in a cost per correctly identified patient =     $24,285

Now, let’s compare this with an ex-vivo analysis of programmed cell death.

Remember, the Rational Therapeutics panel of 16+ drugs and combinations tests both cytotoxic drugs and targeted therapies. In our soon to be published lung cancer study, the overall response rate was 65 percent. So what does the EVA/PCD approach cost?

Again one hundred patients are diagnosed with non-small cell lung cancer.
•    Their physicians order an EVA-PCD analysis    $4,000
•    The costs associated: $4,000 x 100 people =    $400,000
•    With 65 percent of patients responding, this
constitutes a cost per correctly identified patient =     $6,154

Thus, we are one quarter the cost and capable of testing eight times as many options. More to the point, this analysis, however crude, reflects only the costs of selecting drugs and not the costs of administering drugs. While, each of those patients selected for therapy using the molecular profiles will receive an extraordinarily expensive drug, many of the patients who enjoy prolonged benefit using EVA/PCD receive comparatively inexpensive chemotherapeutics.

Furthermore, those patients who test negative for ALK and EGFR are left to the same guesswork that, to date has provided responses in the range of 30 percent and survivals in the range of 12 months.

While the logic of this argument seems to have escaped many, it is interesting to note how quickly organizations like ASCO have embraced the expensive and comparatively inefficient tests. Yet ASCO has continued to argue against our more cost-effective and broad-based techniques.

No wonder we call our group Rational Therapeutics.

About Dr. Robert A. Nagourney
Dr. Nagourney received his undergraduate degree in chemistry from Boston University and his doctor of medicine at McGill University in Montreal, where he was a University Scholar. After a residency in internal medicine at the University of California, Irvine, he went on to complete fellowship training in medical oncology at Georgetown University, as well as in hematology at the Scripps Institute in La Jolla. During his fellowship at Georgetown University, Dr. Nagourney confronted aggressive malignancies for which the standard therapies remained mostly ineffective. No matter what he did, all of his patients died. While he found this “standard of care” to be unacceptable, it inspired him to return to the laboratory where he eventually developed “personalized cancer therapy.” In 1986, Dr. Nagourney, along with colleague Larry Weisenthal, MD, PhD, received a Phase I grant from a federally funded program and launched Oncotech, Inc. They began conducting experiments to prove that human tumors resistant to chemotherapeutics could be re-sensitized by pre-incubation with calcium channel blockers, glutathione depletors and protein kinase C inhibitors. The original research was a success. Oncotech grew with financial backing from investors who ultimately changed the direction of the company’s research. The changes proved untenable to Dr. Nagourney and in 1991, he left the company he co-founded. He then returned to the laboratory, and developed the Ex-vivo Analysis - Programmed Cell Death ® (EVA-PCD) test to identify the treatments that would induce programmed cell death, or “apoptosis.” He soon took a position as Director of Experimental Therapeutics at the Cancer Institute of Long Beach Memorial Medical Center. His primary research project during this time was chronic lymphocytic leukemia. He remained in this position until the basic research program funding was cut, at which time he founded Rational Therapeutics in 1995. It is here where the EVA-PCD test is used to identity the drug, combinations of drugs or targeted therapies that will kill a patient's tumor - thus providing patients with truly personalized cancer treatment plans. With the desire to change how cancer care is delivered, he became Medical Director of the Todd Cancer Institute at Long Beach Memorial in 2003. In 2008, he returned to Rational Therapeutics full time to rededicate his time and expertise to expand the research opportunities available through the laboratory. He is a frequently invited lecturer for numerous professional organizations and universities, and has served as a reviewer and on the editorial boards of several journals including Clinical Cancer Research, British Journal of Cancer, Gynecologic Oncology, Cancer Research and the Journal of Medicinal Food.

7 Responses to The False Economy of Genomic Analyses

  1. The question of whether to consider spending $3,000 or more for a cell-based functional profiling test gets more interesting, especially with the lastest press release from Pfizer about their new drug Xalkori (crizotinib). The drug will cost $9,600 per patient per month and the gene test for it will cost $1,500 per patient. A biotech executive states the real cost of the drug is $9,600 plus 25 ALK tests, because that’s how many patients will need to be screened for one to actually get Xalkori.

    There are lots of things which determine if drugs work, beyond the existence of a given target (like ALK). Does the drug even get into the cancer cell? Does it get pumped out of the cell? Does the cell have ways of escaping drug effects? Can cells repair damage caused by the drug? Do combinations of drugs work in ways which can’t be predicted on the basis of static gene expression patterns?

    Tumor biology is a lot more complex than we’d like it to be. Cancer is more complex than its gene signature. Many common forms of cancer present as a host of mutated cells, each with a host of mutations. And they’re genetically unstable, constantly changing. That’s why so many cancers relapse after initially successful treatment. You kill off the tumor cells that can be killed off, but that may just give the ones that are left a free reign.

    The idea of searching for clinical responders by testing for a single gene mutation seems like a nice theoretical idea, but you may have to test for dozens of protein expressions that may be involved in determining sensitivity/resistance to a given drug. Because if you miss just one, that might be the one which continues cancer growth. And at $1,500 a pop, that’s a lot of dough, on top of the inflated price of the single drug!

    The key to understanding the genome is understanding how cells work. The ultimate driver is “functional” pre-testing (is the cell being killed regardless of the mechanism) as opposed to “target” pre-testing (does the cell express a particular target that the drug is supposed to be attacking). While a “target” test tells you whether or not to give “one” drug, a “functional” pre-test can find other compounds and combinations and can recommend them, all from the one test.

  2. Linda S says:

    I recently had a Caris profile completed for ovarian cancer and I came away from the report with more questions than answers. I am most notably confused by the differing results between the IHC and the Microarray portions, which differed from each other for specific markers. I was told the IHC trumps the Microarray when there is a discrepancy.

    How accurate are these actual tests (I am separating the accuracy of the tests themselves from predictive chemo with literature association recommendations)? One very significant biomarker for my prognosis was exactly at the threshold and it was marked as above threshold on the IHC and marked as “no change” on the microarray. In another instance, I was marked as ER negative when I know my original pathology report indicated ER positive.

    How accurate are these tests and who has approved their use?

    Linda

    • Linda:

      You touch on several very important points. First, the accuracy of any given test can be defined 2 ways. A test functions within its performance characteristics defined as sensitivity and specificity. These describe whether the tests can find what they are looking for in a reliable way. The second characteristic is the predictive accuracy. This is more what most patients are actually looking for and can be summed up as “How likely will this positive (drug sensitive) result translate into a true response for me?” This is a more fluid concept and in part reflects the individual patient’s underlying characteristics and likelihoods of response prior to the test being run. That data is still being generated (I presume) on their part.

      The final point is perhaps the most interesting of all and defines the shortcomings of genomic analyses. The presence of a gene or mutation does not guarantee its expression. Brown eyed people often have blued eyed genes tucked into their (unexpressed) genetic makeup. When a genomic analysis finds that you have a given gene it does not tell you whether your cancer will then behave accordingly. It only tells you that it “can” behave accordingly. That is like a weather man telling you “it could rain today”. You want to know whether it is likely to rain today and how likely. Thus, the information needs to be more definitive. The best approximation for this is given by IHC, which measures protein expression. Cells with normal genes and normal numbers of gene copies may use those genes to make more of a given protein. If that protein is important for your response to a drug, then this may and I stress MAY tell you your likelihood of benefit. Again, proteins may be expressed and detected by IHC but still may have minor features (glycosylation) that limit their actual function.

      For these an many other reasons (synergy, sequence, etc) we utilize functional analytic platforms that provide all of the needed information at once.

  3. kitty says:

    “While, each of those patients selected for therapy using the molecular profiles will receive an extraordinarily expensive drug, many of the patients who enjoy prolonged benefit using EVA/PCD receive comparatively inexpensive chemotherapeutics.”

    Have you looked at the response rate for the “comparatively inexpensive chemotherapeutics” for NSCLC? How about side effects of these “comparatively inexpensive chemotherapeutics”. How about the response rate of chemo for people who have ALK mutatiion? As to “inexpensive chemo” — do you have a clue how much chemo for lung cancer costs?

    When you factor in need to test for mutation and mixing it in with the response rate, you are obscuring the fact that for people who do have ALK mutation, this drug not only extends life for longer than ANY chemo protocol, but it also does it with far fewer side effects. In fact, my mother who was in clinical trials for this drug has had ZERO side effects. Yes, I know that side effects are listed, but the severity of them – in people who have them and many people don’t – .

    Yes, the cost of testing is there. But for people who do have this mutation, near 90% benefit.This is far greater than any treatment for lung cancer.

    • Kitty:

      We have indeed looked at the response to conventional chemotherapy drugs. In a recently submitted Phase II trial manuscript, we showed that pts who receive “assay-directed” conventional therapy (after we removed from the analysis, those who received targeted agents more like Crizotinib) had an objective response rate (CR &PR) of 65.4%. This compares quite favorable with the 57% response rate observed with Crizotinib in the NEJM study. Our clinical benefit response rate (CR & PR & Stable Disease) was 93.5% again better that the 90% reported for Crizotinib. We are also extremely familiar with the cost of chemotherapy drugs which are uniformly less than Crizotinib.

      We are delighted that your mother has had such a good response to this new drug and applaud its development and use. We have had similarly great responses with Crizotinib.

      Our point in this and related articles is that the ALK gene and other tests (EGFr) can only find THE ONE mutation they are designed to detect. At ever increasing costs per test these unidimensional evaluations could cost thousands or even tens of thousands to locate that ONE patient out of many who fits the profile. More global assessments at the cellular level have the capacity to encompass all of the operative mechanisms of response and resistance in a single test.

      • gpawelski says:

        Implications of a New Target in NSCLC

        The incidence of ALK gene rearrangement in patients with NSCLC is in the range of 2-4 percent, while EGFR mutations are found in approximately 15 percent. These are largely mutually exclusive events. And now we have the ROS1 rearrangement in patients in the range of 1-2 percent, with another report of ALK rearrangement in the range of 1-2 percent (Bergethon, et al, J Clin Oncol. 2012; 30:863-870).

        Dr. Howard (Jack) West told Medscape Oncology that “with a growing battery of extremely uncommon but potentially highly relevant markers in NSCLC, what is needed is a multiplex platform to test a broad range of targets simultaneously, using a limited amount of tissue, and for a reasonable price. If such testing capability is not readily available, we will soon reach a breaking point where it is not feasible to seek a series of separate $1500 mutation tests from multiple laboratories in search of patient subgroups totaling 1%-3% of the larger patient population.”

        http://www.medscape.com/viewarticle/761569

        Yet with an objective response rate of 10 percent (Von Hoff, et al JCO, Nov 2011) reported for a gene array/IHC platform that attempted to select drugs for individual patients, it doesn’t seem to be a very accurate or validated methodology to use in patients with advanced NSCLC.

        And those patients who do test negative for ALK and EGFR are left to the same guesswork that has provided responses in the range of 30 percent and survivals in the range of 12 months. It’s interesting to note how quickly organizations like ASCO have embraced the expensive and comparatively inefficient molecular testing.

        If you don’t have the mutant gene, why would you want the same treatment? It’s like saying, a friend had a son who was not doing well in math and got a math tutor who greatly improved her son’s grades. My son does not have a problem with math, but would like to do better in basketball, can I get the same tutor?

  4. Reblogged this on Dr. Robert A. Nagourney – Rational Therapeutics – Blog and commented:

    While Dr. Nagourney is enjoying Spring Break with his family, here is a very topical subject in light of the constant press given to genetic testing.

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