Companion Diagnostics

[gdpawel]

The headlong rush to develop pre-tests (companion diagnostics) to identify molecular predisposing mechanisms does not guarantee that a cancer 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 cancer agents of the same class.

The drug discovery model over the last number of years has been limited to one gene/protein, one target, one drug. The 'cell' is a system, an integrated, interacting network of genes, proteins and other cellular constituents that produce functions. You need to analyse the systems' response to drug treatments, not just one target or pathway.

The decoding of the human genome in 2000, sparked hopes that a new era of tailored medicine was just around the corner. However, uncovering the genetic differences that determine how a person responds to a drug, and developing tests, or biomarkers, for those differences, is proving more challenging than ever. As a result, patients with cancer are still being prescribed medicines on a trial-and-error basis or one-size-fits-all.

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 from the one test.

The core of 'functional' testing is the cell, composed of hundreds of complex molecules that regulate the pathways necessary for vital cellular functions. If a 'targeted' drug could perturb any one of these pathways, it is important to examine the effects of the drug within the context of the cell. Both genomics and proteomics can identify potential new thereapeutic targets, but these targets require the determination of cellular endpoints.

Cell-based functional pre-testing is being used for screening compounds for efficacy and biosafety. The ability to track the behavior of cancer cells permits data gathering on functional behavior not available in any other kind of testing.

In recent years, personalized care has come to be considered synonymous with genomic profiling. While breakthroughs in human genomics is applauded, there is no molecular platform that can match patients to treatments. The objective response rate of just 10 percent, almost all in breast and ovarian cancer patients in one study (Von Hoff J Clin Oncol 2010 Nov 20:28(33): 4877-83), suggests that cancer biology is demonstrably more complex than an enumeration of its constituent DNA base pairs.

Gene profiling tests, important in order to identify new therapeutic targets and thereby to develop useful drugs, are years away from working successfully in predicting treatment response for 'individual' patients. Perhaps this is because they are performed on dead, preserved cells that are never actually exposed to the drugs whose activity they are trying to assess.

It will never be as effective as the cell 'function' methodology, which has existed for the last twenty years 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 (apoptosis) 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:
BMJ 2007;334(suppl 1):s18 (6 January), doi:10.1136/bmj.39034.719942.94
Functional profiling with cell culture-based assays for kinase and anti-angiogenic agents Eur J Clin Invest 37 (suppl. 1):60, 2007
Functional Profiling of Human Tumors in Primary Culture: A Platform for Drug Discovery and Therapy Selection (AACR: Apr 2008-AB-1546)

[gdpawel]

Robert Nagourney, M.D., Ph.D.

Depending on which “authority” one consults, the recommendations may be colored by prejudices and biases.

Some physicians adhere strictly to the National Comprehensive Cancer Network guidelines. Others insist upon accrual to Cooperative Group and Phase II trials. University-based investigators will often recommend developmental studies. And some physicians will follow the path of least resistance, examining such issues as cost, chair time and reimbursement, before considering what treatment to deliver.

It is in this milieu that patients find themselves adrift. Who exactly should you trust? What is their motivation? To put it crassly, when they recommend a specific treatment, what’s in it for them: Cooperative Group points (provided to the most active accruers), academic accolades (the currency of junior faculty), cost containment (the purview of the managed care physicians), or finally, profit margins? Yes, there are a small number of physicians whose choices reflect their own pecuniary interests.

The antidote to all this uncertainty lies within each patient; answers to vexing questions crying out to be heard. These answers reflect the biologic features of each individual’s tumor. What pathway, what repair mechanism, what survival signal drives your tumor? No one has a perfect answer, not the genomic investigators (despite their protestations to the contrary), nor the immunohistochemists, despite the significant appeal of the platform. And not the immunologist (despite brilliant progress in this field over recent years).

The closest approximation to human tumor biology is human tumor biology. Using cellular constructs, in the form of native state microspheroids, we can today approximate the response profiles of patients undergoing systemic therapies. Using systems approaches to complex questions, the multitude of factors that contribute to objective response can be examined and elucidated.

No test is perfect. No patient is guaranteed a good outcome. Yet, doubling the objective response rate, and as cell function analysis has documented, improving the time to progression and overall survival can be achieved with available methodologies that apply functional cytometric profiling to individual tumors.

No one would walk away from an investment formula that would double the value of their portfolio. Few would turn down the opportunity to enhance their real estate positions predicated on reliable information from a realtor. Yet everyday, physicians convince patients to walk away from available, published, established methods that can improve response rates, diminish toxicities and avoid futile care.

In this environment it is critical for patients to take charge of their own cancer management. Patients must not be dissuaded from seeking the best possible outcomes. Physicians, no matter how well intentioned, are human. Their opinions can be colored by misconceptions and an incomplete understanding of the questions at hand. Laboratory analysis empowers patients to make smart decisions.

[gdpawel]

BOSTON — Lack of evidence that links diagnostic tests to health outcomes has led payers in the United States to be skeptical about the clinical usefulness of those tests and is hindering the growth of personalized medicines, according to a newly completed analysis by the Tufts Center for the Study of Drug Development.

While the number of personalized medicines and companion diagnostics in use in the U.S. has gradually increased—from a handful in 2001 to several dozen in 2011—surveys conducted by Tufts CSDD show that lack of evidence concerning the clinical usefulness of many current companion diagnostics is a major factor limiting the potential of personalized medicine.

“Scientifically, the process of biomarker discovery and validation in general, and parallel development of drugs and companion diagnostics in particular, has been slow. Additionally, regulatory and reimbursement issues have limited uptake in clinical practice, particularly with respect to companion diagnostics, but also for drugs lacking effective diagnostics,” said Joshua Cohen, Ph.D., senior research fellow at Tufts CSDD and author of the study.

Without clinically useful diagnostics, development of personalized medicine is likely to continue at a relatively slow pace, he noted.

Companion diagnostics are tests linked to a therapeutic drug that stratify populations into responders and non-responders and indicate the likelihood of adverse events in particular patients.

The study, reported in the July/August Tufts CSDD Impact Report, released today, also found that:

* Lack of clinical usefulness of many companion diagnostics has led payers to deny or restrict reimbursement of tests.

* A minority of U.S. payers require documentation that a diagnostic test has been conducted prior to prescribing personalized drugs — even when the diagnostic is included on the label.

* Pharmacogenomic experts foresee moderate growth over the next five years in post hoc development of companion diagnostics to personalize already approved drugs, co-development of companion diagnostics, and personalized drugs.

About the Tufts Center for the Study of Drug Development

The Tufts Center for the Study of Drug Development [url]http://csdd.tufts.edu at Tufts University provides strategic information to help drug developers, regulators, and policy makers improve the quality and efficiency of pharmaceutical development, review, and utilization. Tufts CSDD, based in Boston, conducts a wide range of in-depth analyses on pharmaceutical issues and hosts symposia, workshops, and public forums, and publishes Tufts CSDD Impact Reports, a bi-monthly newsletter providing analysis and insight into critical drug development issues.

Tufts Center for the Study of Drug Development

[gdpawel]

Companion diagnostics and their companion therapies are what's being pushed as "personalized medicine" as they enable the identification of likely responders to therapies that work in patients with a specific molecular profile.

However, companion diagnostics tend to only answer a targeted drug-specific question and may not address other important clinical decision needs.

These companion diagnostics are being used to predict responsiveness and determine candidacy for a particular therapy often included in drug labels as either required or recommended testing prior to therapy initiation.

Landscape trends suggest companion diagnostic tests in their current "one-test/one-drug" embodiment will not adequately cover decision support needs as physicians become inundated with more biomarker data likely to be interrelated, nuanced and at time even contradictory.

Two years ago, Ryan Kuper was diagnosed with lung cancer. A very compelling aspect of Ryan's journey was Rational Therapeutic's ability to recognize Ryan's sensitivity to the drug Xalkori (crizotinib), after his genomic analysis failed to identify the gene target.

In the end, it was the functional platform that provided Ryan's doctors with the treatment plan that has proven to be effective against his widely metastatic non-small cell lung cancer.

Hear more about Ryan and the functional cytometric profiling assay.

[url]http://www.youtube.com/watch?v=BKh-rMCc4dQ&feature=youtu.be

These so-called "smart drugs" focus their effects on specific, identifiable processes occurring within cancer cells. The new "targeted" drugs are highly promising in that they "sometimes" provide benefit to patients who have failed traditional therapies. However, they do not work for everyone, they often have unwanted side effects, and they are all extremely expensive. Patients, physicians, insurance carriers, and the FDA are all calling for the discovery of "predictive tests" that allow for rational and cost-effective use of these drugs.

There was a predictive test (functional cytometric profiling) developed that holds the key to solving some of the problems confronting this high-price healthcare system that is seeking ways to best allocate available resources while accomplishing the critical task of matching individual patients with the treatments most likely to benefit them. Not only is it an important predictive test, it is also a unique tool that can help to identify newer and better drugs, evaluate promising drug combinations, and serve as a "gold standard" correlative model with which to develop new DNA, RNA, and protein-based tests that better predict for drug activity.

But how does one get ASCO and others to understand this and allow its judicious use? They have single-handedly done more over the past 20 years to keep assay-testing (pre-testing) technology under a bushel basket and out of the public light. It has hurt literally hundreds of thousands of patients. We'd be much further along and technology would have improved, even more accurate. New treatments would have been discovered and targeted immediately to the people who could most benefit from them. This has been one great lost of opportunity in clinical cancer research.