Stalking Leukemia Genes One Whole Genome at a Time

An article by Gina Kolata on the front page of the July 8, Sunday New York Times, “In Leukemia Treatment, Glimpses of the Future,” tells the heartwarming story of a young physician afflicted with acute lymphoblastic leukemia. Diagnosed in medical school, the patient initially achieved a complete remission, only to suffer a recurrence that led him to undergo a bone marrow transplant. When the disease recurred a second time years later, his options were more limited.

As a researcher at Washington University himself, this young physician had access to the most sophisticated genomic analyses in the world. His colleagues and a team of investigators put all 26 of the University’s gene sequencing machines to work around the clock to complete a whole genome sequence, in search of a driver mutation. The results identified FLT3. This mutation had previously been described in acute leukemia and is known to be a target for several available small molecule tyrosine kinase inhibitors. After arranging to procure sunitinib (Sutent, Pfizer Pharmaceuticals), the patient began treatment and had a prompt and complete remission, one that he continues to enjoy to this day.

The story is one of triumph over adversity and exemplifies genomic analysis in the identification of targets for therapy. What it also represents is a labor-intensive, costly, and largely unavailable approach to cancer management. While good outcomes in leukemia have been the subject of many reports, imatinib for CML among them, this does not obtain for most of the common, solid tumors that lack targets for these new silver bullets. Indeed, the article itself describes unsuccessful efforts on the part of Steve Jobs and Christopher Hitchens, to probe their own genomes for effective treatments. More to the point, few patients have access to 26 gene-sequencing machines capable of identifying genomic targets. A professor of bioethics from the University of Washington, Wiley Burke, raised additional ethical questions surrounding the availability of these approaches only to the most connected and wealthiest of individuals.

While brute force sequencing of human genomes are becoming more popular, the approach lacks scientific elegance. Pattern recognition yielding clues, almost by accident, relegates scientists to the role of spectator and removes them from hypothesis-driven investigation that characterized centuries of successful research.

The drug sunitinib is known for its inhibitory effect upon VEGF 1, 2 and 3, PDGFr, c-kit and FLT3. Recognizing the attributes of this drug and being well aware of C-KIT and FLT3’s role in leukemias, we regularly add sunitinib into our leukemia tissue cultures to test for cytotoxic effects in malignantly transformed cells.  The insights gained enable us to simply and quickly gauge the likelihood of efficacy in patients for drugs like sunitinib.

Once again we find that expensive, difficult tests seem preferable to inexpensive, simple ones. While the technocrats at the helm of oncology research promise to drive the price of these tests down to a level of affordability, everyday we wait 1,581 Americans die of cancer. Perhaps, while we await perfect tests that might work tomorrow, we should use good tests that work today.

Venture Capital Goes Genomic

During the 1960s, 70s and into the 90s, a field of investigation arose that examined buyer’s practices when it came to the consumption of goods and services. Algorithms were developed to interrogate consumer choice. One such treatise was reported in 1994 (Carson, RT et al, Experimental Analysis of Choice, Marketing Letters 1994). What these researchers explored were the motivations and forces that drove consumption. When choices are offered, decisions are driven by such factors as complexity and utility. Complexity demands personal expertise or failing that, input from experts, while utility places a value on the good or service.

A recent report from a small biotechnology company called Foundation Medicine has brought this field of endeavor to mind. It seems that this group will be offering DNA sequencing to select chemotherapy drugs. This service, currently priced at $5,800, will focus upon a small cassette of genes that they described as “key” in tumor growth. Based on their technology they have already raised $33.5 million from the likes of Third Rock, Google and Kleiner Perkins Caulfield & Byers, venture capital sources. The CEO of Foundation substantiates the approach by pointing out that fully 150 people have already used their services. One hundred and fifty!

It seems from this report that our colleagues in the field of molecular profiling have studied the dictates of “Experimental Analysis of Choice” to a “T.” What we have is the perfect storm of medical marketing.

First, the technology is so complex as to be beyond the ken of both patients and physicians alike. Thus, expertise is required and that expertise is provided by those engaged in the field. Second, the utility of drug selection is beyond reproach. Who in their right mind wouldn’t want to receive a drug with a higher likelihood of a response when we consider the toxicities and costs, as well as the consequences of the wrong treatment? Dazzled by the prospect of curative outcomes, patients will, no doubt, be lining up around the block.

But, let’s deconstruct what this report is actually telling us. First, a scientifically interesting technology has been brought to the market. Second, it exists to meet an unmet need. So far, so good. What is lacking, however, is evidence. Not necessarily evidence in the rarefied Cochrane sense of idealized survival curves, nor even Level II evidence, but any evidence at all. Like whirling dervishes, patients and their physicians are drawn into a trancelike state, when terms like NextGen sequencing, SNP analysis and splice variants are bandied about.

Despite the enthusiastic reception by investors, I fear a lack of competent due diligence. To wit, a recent article in Biotechniques, “Will the Real Cancer Cell Please Stand Up,” comes to mind. It seems that cancer cells are not individual entities but networks. A harmonic oscillation develops between tumor, stroma, vasculature and cytokines. In this mix, the cancer cell is but one piece of the puzzle.

Indeed, according to recent work from Baylor, some of the tumor promotion signals in the form of small interfering RNAs, may arise not from the cancer cells, but instead from the surrounding stroma. How then, will even the most punctiliously perfect genomic analyses of a cancer cells play out in the real world of human tumor biology and clinical response prediction? Not very well I fear. But then again such a discussion would require data on the predictive validity of the method, something that appears to be sorely lacking.

Will today’s gene profile companies prove to be the biotech Facebook IPOs of tomorrow?

Gee (G719X) Whiz: Novel Mutations and Response to Targeted Therapies

In a recent online forum a patient described her experience using Tarceva as a therapy for an EGFR mutation negative lung cancer. For those of you familiar with the literature you will know that Lynch and Paez both described the sensitizing mutations that allow patients with certain adenocarcinoma to respond beautifully to the small molecule inhibitors.  The majority of these mutations are found in Exon 19 and Exon 21, within the EGFR domain. Response rates for the EGFR-TKI (gefitinib and erlotinib) clearly favor mutation positive patients. Depending upon the study, mutation positive patients have response rates from 53 – 100 percent, generally around 70 percent, while mutation negative response patients have a response rate of 0 – 25 percent, generally about 10 percent.So why don’t all the mutation positive patients respond and conversely why do some mutation negative patients respond?

The story outlined in this online forum gives some insight. The individual in question carried a rare, and only recently recognized, Exon 18 mutation known as a G719X. This uncommon form of mutation had previously been unknown and few laboratories knew to test for it. Nonetheless, G719X positive patients respond to erlotinib and related agents. Indeed, there may be reason to believe that the more potent irreversible EGFR/HER2 dual inhibitor HKI-272, may be even more selective for this point mutation.

The excellent and durable response described by this individual, would not have been possible had the patient’s first physician followed the rules. That is, had her physician refused to give erlotinib to an (putatively) EGFR mutation negative patient she might well not be here to tell her story. More to the point, her good response (a clinical observation) led to the next level of investigation, namely the identification of this specific EGFR variant

The lessons from this experience are numerous. The first is that cancer biology is complex and, to paraphrase E.O. Wilson, was not put on earth for us to necessarily figure it out. The second, is that molecular biologists can only seek and identify that which they know about apriori.  To wit, if you don’t know about it (G719X) and you don’t have a test for it, and you don’t know to look for it, then it’s a virtual certainty that you aren’t going to find it.

The premise of our work at Rational Therapeutics is that the observation of a biological signal identifies a candidate for therapy whether we understand or recognize the target. Crizotinib was originally developed as a clinical therapy for patients who carried the CMET mutation. Serendipity led to the recognition that the responding subpopulation was actually carrying a heretofore-unrecognized ALK gene rearrangement. Sorafenib was originally evaluated for the treatment of BRAF mutation positive diseases. Yet it was the drug’s cross-reactivity with the VGEF tyrosine kinases that lead to its broad clinical applications. Each of these phenomena represents accidental successes. Were it not for the clinical observation of response in patients, the investigators conducting these trials would have been unlikely to make the discoveries that today provide such good clinical responses in others.

To put it quite simply, these patients and their disease entities educated the molecular biologists.

When we first identified lung cancer as a target for gefitinib, and began to administer the closely related erlotinib to lung cancer patients, neither Lynch nor Paez had identified the sensitizing EGFR mutations. That had absolutely no impact upon the excellent responses that we observed. It didn’t matter why it worked, but that it worked.  While the EGFR story has now been well-described, might we not use functional analytical platforms (functional profiling) to gain insights into the next, and the next generation of drugs and therapies that target pathways like MEK, ERK, SHH, FGFR, PI3K, etc., etc., etc. . . .

The Tyranny of Medical Experts

Over the last several years a number of decisions have been handed down from medical experts, I use the term “handed down” advisedly. Like the Olympian Gods or appellate court judges, these dictates are provided to the unsuspecting medical public as fiats. Among these are the roles of mammograms for women under 50 (not recommended), PSA screening for men (not recommended), and a variety of determinations that seem to many counterintuitive. In the past, similar recommendations have been handed down regarding a series of “unnecessary” tests, the cessation of which could save millions of dollars annually.

These topics were the subject of a recent article by Drs. Pamela Hartzband and Jerome Groopman, members of the faculty at Harvard Medical School. Published in the Saturday, March 31, 2012, Wall Street Journal, their article “Rise of the Medical Expertocracy,” focuses on the new paternalism that has come to define “Best Practices” in the healthcare. What most concerns these authors is the transition from physicians as experts, to governmental entities as experts. With this new bureaucracy comes an entirely new industry dedicated to the generation of medical metrics designed to provide doctors and hospitals report cards on their performance. Like evidence-based medicine, yesterday’s catchphrase for improving treatments, “Best Practices” are now being forced upon practitioners.

Where the purveyors of these approaches have gone wrong, is their misguided attempt to apply average treatments to average patients with the expectation of average outcomes. Despite the appeal of simplified treatment algorithms, there are no average patients and it follows that there are no average outcomes.

In a recent presentation at the American Association for Cancer Research meeting held in Chicago March 31 – April 4, 2012, one of the presenters at the melanoma session described whole genome sequencing on 21 human melanomas. To their chagrin they found 21 completely different phosphoprotein signatures. From the macroscopic to the most microscopic mankind in general and his tumors in particular, distinguish themselves for their unique attributes.

The theme of Drs. Hartzband and Groopman’s article echoes loudly in our study of cancer patients. We will only succeed in saving money and saving lives when we stop banging round pegs into square holes and get down to the challenging, but very doable work of matching each individual to their best treatment option – truly personalized medicine.

If It is Too Good to Be True . . .

The February 12, 2012, CBS 60 Minutes covered a story that has sparked a great deal of interest among cancer patients and medical professionals. The topic was an investigator named Anil Poti who, while working at Duke University developed a laboratory platform for the study of human lung cancer.

Using molecular profiling, Dr. Poti and his collaborators, reported their capacity to distinguish responding and non-responding cancer patients, providing survival curves that were nothing short of astonishing. I recall attending the original lectures given by these investigators at the American Association of Cancer Research meeting several years ago.

As an investigator in the field of drug response prediction, working in lung cancer I had a particular interest in their platform and I was extremely impressed by the outcomes they reported. At the time, I wondered how the static measurement of gene profiles could possibly characterize the nuances of human biology, to encompass the epigenetic, siRNA, pseudogene, non-coding DNA and protein kinetics that ultimately characterize the human phenotype. Nonetheless, with such compelling data I was prepared to be convinced.

That is until a relatively unheralded report in the Cancer Letter raised concerns by several biostatisticians regarding the reproducibility of Dr. Poti’s findings. And then more comments were followed by a full NIH investigation. A panel of biostatisticians was convened and a formal report provided the explanation for Dr. Poti’s excellent results.

They had been invented. The clinical outcomes were not real results. The findings had been retrofitted to match the patient responses and this was the subject of the 60 Minutes report.

What the 60 Minutes report did not address however, was the real problem. That being the inability of contemporary genetic profiling to truly define human biology. For all the reasons enumerated above, siRNA, non-coding DNA, etc., the simple measurement of gene sequences cannot accurately predict biological behavior. This is what the 60 Minutes reporters and the physicians they interviewed, never discussed. The problem at hand is not an errant investigator but an errant scientific community. Our love affair with the gene that began in 1953 (Watson and Crick) has now been confronted by a most heartbreaking example of infidelity (pun intended).

Genes do not make us what we are; they only (sometimes) permit us to become what we are, with the vagaries of transcription and translation lying between.

This leads us to the reasons I find this so critically important:

1. I cannot stress strongly enough that this is NOT what I do. Genomic analysis (their work) and functional analysis (our work) are distinctly different platforms.
2. I strenuously resist any attempt on the part of anyone to tar me or my work with this brush.
3. It is precisely because genomic analysis cannot accurately predict cancer patient outcomes, that these investigators found it necessary to invent their data.
4. Despite this, functional analyses can and do provide these types of predictive results in lung cancers and other diseases as we have reported in numerous publications.
5. Finally, while imitation is the sincerest form of flattery, this is one instance in which I would prefer to decline the compliment.