The Emperor’s New Gene Profile

The role of genomic testing for predicting response to chemotherapy

I read — with great interest — the recent study by Von Hoff, et al. in the Nov. 20, 2010 issue of the Journal of Clinical Oncology, as well as the associated editorial in the same issue. The manuscript, titled Pilot Study Using Molecular Profiling of Patient Tumors to Find Potential Targets and Select Treatments for the Refractory Cancers, reported the results obtained in 106 patients who consented to study using immunohistochemistry and microarray analysis for the identification of treatment process.

Of the original 106 patients:

  • There were 86 who underwent profiling and were considered for therapy
  • Of those, 68 were treated
  • Of whom, 66 received the recommended treatment.

The objective of the trial was to improve progression-free survival over that associated with the most recent prior therapy; to determine the percentage of time a target was identified; and finally, to gauge objective response rates by RECIST criteria.

The patients in the study:

  • Were a mixture of solid tumors, including breast, colon, ovary and others.
  • Had failed prior therapy.
  • The median age was 60 years and the majority of patients were female
  • Only the breast cancer patient population was defined in terms of the number of prior therapies — five.

At first blush, this paper would suggest that the era of molecular profiling has arrived. We need only obtain a small biopsy of tissue to identify the “targets” most likely to respond to available or investigational agents. At a closer look, however, we find that the investigators on the trial invented a criterion of response, namely a 1.3 fold improvement in time to progression. What that means is that patients who received an ineffective therapy and showed disease progression, need only improve upon that short response by a mere 30 percent to be counted among the “responders.”

Thus, a patient who failed a therapy after 10 days could theoretically be counted among the successes if their subsequent response to directed therapy was a meager 13 days in duration.

Even using this soft-boiled endpoint, only 18 of the 66 patients (27 percent) met criteria for response. However, these 18 responders should really be calculated against the total 88 patients approved for study, providing an even lower 20 percent result. Indeed, the most rigorous investigators would demand that these 18 be measured against the total 106 patient cohort, which would provide a response rate of a mere 16.9 percent.

Since most investigators don’t have the luxury of inventing their own criteria for response, we might examine this manuscript in the context of more widely used criteria like RECIST. In this context, the objective response rate of six out of 66 was 10 percent, with an additional 14 patients (21 percent) revealing stable disease for four months. However, again using the intention-to-treat analysis (the criteria other investigators must live by) the objective response rate falls to more like 6.8 percent (6/88) or most rigorously 5.7 percent (6/106).

Furthermore, four of the six (66 percent) objective responders, by RECIST criteria, and nine of the 18 (50 percent) were found in breast and ovarian cancers (mostly breast) known to be among the most chemo-responsive of all epithelial neoplasms. By these standards, the capacity of molecular profiling to identify responders begins to seem a bit underwhelming.

The design of the trail also raises some questions:

  • First, the principle end point is IHC (immunohistochemistry), followed by microarray
  • Yet, the specific predictive validity of the micro-array analysis is not addressed

While the authors note that IHC is a well-established and widely used methodology, they largely skirt the second issue noting only that “For MA (microarray), excellent reviews and commentary have been written on the subject of gene arrays and their potential and actual use for predicting clinical response for chemotherapy.”

In essence, we are left with a report that provides a very low objective response rate and succeeds only by meeting its own invented criteria to support the predictive validity for what appears to be mostly an established use of IHC. Should we consider this the birth of molecular profiling? By comparison, our functional platform in similarly heavily pretreated patients has consistently provided significantly higher response rates than those reported in the current analysis. Is it not time for the molecular profiles to match our results?

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.

2 Responses to The Emperor’s New Gene Profile

  1. Vikram Patel says:

    This is an interesting analysis of a published peer-reviewed article, which begs the question of the review process itself. I wish this analysis was presented to the editor of the journal.

    • I could not agree more. The accompanying editorial did not remotely address the real shortocmings of the manuscript becasue it was written by a devotee. The title “Emperor’s New Gene Profile” was chosen for a reason. Everyone is so wedded to genomics that its repeated failures remain invisible to thier shrouded view.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: