Personalized Cancer Care: N-of-1

The New York Yankees catcher Yogi Berra famous quote, “Déjà vu all over again,” reminds me of the growing focus on the concept of “N- of-1.” For those of you unfamiliar with the catchphrase, it refers to a clinical trial of one subject.

In clinical research, studies are deemed reportable when they achieve statistical significance. The so-called power analysis is the purview of the biostatistician who examines the desired outcome and explores the number of patients (subjects) required to achieve significance. The term “N” is this number. The most famous clinical trials are those large, cooperative group studies that, when successful, are considered practice-changing. That is, a new paradigm for a disease is described. To achieve this level of significance it is generally necessary to accrue hundreds, even thousands of patients. This is the “N” that satisfies the power analysis and fulfills the investigators expectations.

So what about an N-of-1? This disrupts every tenet of cancer research, upends every power analysis, and completely rewrites the book of developmental therapeutics. Every patient is his or her own control. Their good outcome reflects the success or failure of “the trial.” There is no power analysis. It is an “N” of 1.

This “breakthrough” concept however, has been the underpinning of the work of investigators like Drs. Larry Weisenthal, Andrew Bosanquet, Ian Cree, myself and all the other dedicated researchers who pioneered the concept of advancing cancer outcomes one patient at a time. These intrepid scientists described the use of each patient’s tissue to guide therapy selection. They wrote papers, conducted trials and reported their successful results in the peer-reviewed literature. These results I might add have provided statistically significant improvements in clinical responses, times to progression, even survival. By incorporating the contribution of the cellular milieu into clinical response prediction, these functional platforms have consistently outperformed their genomic counterparts in therapy selection So why, one might ask, have the efforts of these dedicated investigators fallen on deaf ears?

I think that the explanation lies in the fact that we live in a technocracy. In this environment, science has replaced religion and medical doctors have abdicated control of clinical development to the basic scientists and basic scientists love genomics. It is no longer enough to have good results; you have to get the results the right way. And so, meaningful advances in therapeutics based on functional platforms have been passed over in favor of marginal advances based on genomic platforms.

There is nothing new about N-of-1. It has been the subject of these investigators compelling observations for more than two decades. Though functional platforms (such as our EVA-PCD®) are not perfect, they provide a 2.04 (1.62 to 2.57, P < 0.001) fold improvement in clinical response for virtually all forms of cancer – as we will be reporting (Apfel C, et al Proc ASCO, 2013).

It seems that in the field of cancer therapeutics “perfect is the enemy of good.” By this reasoning, good tests should not be used until perfect tests are available. Unfortunately, for the thousands of Americans who confront cancer each day there are no perfect tests. Perhaps we should be more willing to use good ones while we await the arrival of perfect ones. After all, it was Yogi Berra who said, “If the world was perfect, it wouldn’t be.”

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. . . .

Cancer Medicine – A Humbling Experience

In his brilliant 1998 book, Consilience, Edward O. Wilson, notes: “The cost of scientific advance is the humbling recognition that reality was not constructed to be easily grasped by the human mind.”

This sententious point has remained a guiding principle in my thinking about human cancer. It is critically important for scientific investigators to be humble. We are explorers in a field more complex than any man-made system. We must be instructed by biology – as biological events will always find a way to outsmart our best efforts to explain them.

I was reminded of E.O. Wilson, when a colleague forwarded a recent publication from Molecular Cancer Therapy, “Molecular Profiling of Patient with Colorectal Cancer and Matched Targeted Therapy in Phase I Clinical Trials,” Dienstmann, R. et al MOL CANCER THER Sept 2012. The study conducted by the Molecular Therapeutics Research Unit at Vall d’Hebron Institute of Oncology in Barcelona, Spain, evaluated 254 patients for evidence of specific genetic aberrations. Their genomic analyses included, KRAS, BRAF, PIK3CA, PTEN, and pMET. Patients were then provided clinical therapy trials that matched the targeted agents (drugs with activity against the specific mutation) with their individual mutation profiles

In all, 68 patients received treatment constituting a total of 82 different molecularly targeted therapies. The clinical response rate for this population of patients who received molecularly selected therapy was 1.2%. No that isn’t a typo; it was really one point two percent.

While I applaud the scientific concept of this trial and must admit that I might have expected a somewhat higher response rate, I am not surprised by the result. In keeping with E. O. Wilson’s quote, human biology is not a puzzle designed to be solved by humans; it is instead the complex product of a billion years of evolution. Rather than demanding that cancer patients respond to those treatments we have selected for them based on genetic information, we should be instructed by the tumor’s behavior of each patient and use those insights to select amongst active drugs, whatever genetic elements they may have been originally designed to target. In my lectures, I describe this approach as the wisdom of whole cell experimental models.

I am continually humbled by the complexity of human tumor biology and delighted to have the insights that my patient’s cancer cells provide through the functional profile created by our EVA-PCD assay. Not only do I gain exciting scientific knowledge, but my patients have very good responses to the drugs we select. Not a bad day’s work.

Chemosensitivity Testing Captures Attention of “Nature Biotechnology”

An interesting editorial appeared in the February 2013 issue of Nature Biotechnology titled “Dishing out cancer treatment.” The lead line reads, “Despite their limitations, in-vitro assays are a simple means for assessing the drug sensitivity of a patient’s cancer . . . we think assays deserve a second look.”

The author describes the unequivocal appeal of laboratory analyses that are capable of selecting drugs and combinations for individual patients. At a time when 100’s of new drugs are in development, drug discovery platforms that can mimic human tumor response in the laboratory are becoming increasingly attractive to patients and the pharmaceutical industry. While the author, rooted in contemporary molecular biology, examines the field through the lens of genomic, transcriptomic, proteomic and metabolomic profiling, he recognizes that these analyte-based approaches cannot capture the tumor in its microenvironment, yet we now recognize that these micro-environmental influences are critical to accurate response prediction.

As one reads this piece, it is instructive to remember that no other platform can examine the dynamic interaction between cells and their microenvironment. No other platform can examine drug synergy. And no other platform can examine drug sequence.

It is these complexities however, that will guide the next generation of drug tests and ultimately the process of drug discovery. Even the most ardent adherents to genomic profiling must ultimately recognize that genotype does not equal phenotype. Yet, it is the tumor phenotype that we must study.

I am gratified that the editors of so august a journal as Nature Biotechnology have taken the time to reexamine this important field. Perhaps, if our most scientific colleagues are beginning to recognize the importance of functional analyses, it may be only a matter of time before the clinical oncology community follows suit.

The editor’s final line is poignant, “After years spent on the sidelines, perhaps in-vitro screening methods deserve another look.” We couldn’t agree more.

Chemosensitivity Testing: Lessons Learned

Like all physicians and scientists engaged in the study of cancer biology and cancer treatment, I had accepted that cancer was a disease of abnormal cell growth. I remember reading the lead article in the New England Journal of Medicine (NEJM) that described the clonogenic assay (Salmon, S. E., Hamburger, A. W., Soehnlen, B. S., et al. 1978. Quantitation of differential sensitivity of human tumor stem cells to anticancer drugs. N Engl J Med 298:1321–1327).

I sat in a laboratory at Georgetown University reading about a lab test that could accurately predict the outcome of cancer patients, without first having to give patients toxic drugs. It seemed so logical, so elegant, so inherently attractive. Sitting there as a medical student, far removed from my formal cancer training, I thought to myself, this is a direction that I would like to pursue.

But I was only a first year student and there were miles to go before I would treat cancer patients. Nonetheless, selecting drugs based on a laboratory assay was something I definitely wanted to do. At the time I had no idea just how difficult that could prove to be.

After medical school I found myself in California. There I met an investigator from the National Cancer Institute who had recently joined the faculty at the University of California, Irvine. He too had read the NEJM paper. Being several years ahead of me in training he had applied the clonogenic technique at his laboratory at the National Cancer Institute. Upon his arrival in California, he had continued his work with the clonogenic assay.

All was going along swimmingly until the NEJM published their report documenting the results of five years experience with the clonogenic assay.  It wasn’t a good report card. In fact the clonogenic assay got an “F.”

Despite the enthusiastic reception that the assay had previously enjoyed, the hundreds of investigators around the world who had adopted it and the indefatigable defense of its merits by leading scientists, it seemed that something was very wrong with the clonogenic assay and I desperately needed to know what that was.

It so happens that in parallel to clonogenic assays, my colleague was working on a simpler, faster way to measure drug effects. Using the appearance of cells under the microscope and their staining characteristics, one could skip the weeks of growth in tissue culture and jump right to the finish line. The simple question to be answered was: Did the drugs and combinations kill cancer cells in the test tube? And if they did kill cancer cells in the test tube, would those drugs work in the patient? The answer was, “YES!”

Despite the clonogenic assay’s supporters, it turned out that killing cancer cells outright in the test tube was a much, much better way to predict patient’s outcomes. It would be years before I understood the depth of this seemingly simple observation and the historical implications it would have for cancer therapy.

In Chapter 7 of my soon-to-be-released book, Outliving Cancer I examine the impact of programmed cell death on human biology.

Yet Another Study Agrees: Functional Profiling Provides Insight

It was during the last weeks of December that a particularly interesting article crossed my desk. The study done by a group from Toronto, Canada, is entitled Variable Clonal Repopulation Dynamics Influence Chemotherapy Response in Colorectal Cancer. The study examined the proliferative capacity and drug sensitivity in colorectal cancer cells that were tracked using a process known as lentiviral lineage tracking. The investigators showed that despite serial passages, the cell populations remained stable from a genomic standpoint.

What was most interesting was the finding that these genomically related subpopulations became progressively more resistant to oxaliplatin after drug exposure, suggesting what they described as “inherent functional variability.”

As one of several investigators engaged in the field of functional profiling (EVA-PCD), I found the article both interesting and extremely consistent with our laboratory observations. First, cancer cells display biological differences that may reflect environmental (microenvironmental) influences, epigenetics and other drivers not readily identified at the DNA level.

Second, these investigators, using extremely sophisticated molecular techniques, found, as the lead investigator said, “We should not be putting our eggs exclusively in the genetics basket.” This quote from the lead investigator, John Dick, was particularly resonant.

As many of you who read my blogs know, a recurring theme in these pages is the need to broaden our scope and examine the protein, metabolic and functional characteristics of the cancer cells in their native state. Once again we find that as our most accomplished molecular brethren drill down to the bedrock of cancer biology, they are confronted by complexities and crosstalk that can only be effectively studied at the level of cell biology.

I wish all of readers of this blog a happy New Year, and look forward to a healthy and productive 2013.

Cancer and the Great Divide

There are two types of cancer patients: those we can treat and those we can’t. As I reflect on this year and the years past during which we have applied the process of laboratory-guided treatment, I am reminded of this fact.

The EVA-PCD functional profile enables us to choose active treatments for patients, but I have sometimes wondered whether we are, in fact, choosing patients for the available drugs.  While the end result may not be all that different, e.g. superior clinical outcomes over randomly administered (standard) therapies, the path to that outcome, leaves room for interesting discussion.

I first pondered this issue at the time of completion of our earliest study. That study was conducted in childhood acute lymphoblastic leukemia (ALL). Recognizing that the corticosteroids were among the most important drugs for ALL, we exposed freshly isolated lymphoblasts from ALL patients to dexamethasone (ex vivo). At the fourth day we measured the degree of cell death and separated the patients in “sensitive” and “resistant “ subgroups. Strikingly, those children whose lymphoblasts died in the laboratory following exposure to dexamethasone (ex-vivo), virtually all survived without relapse, while those children whose lymphoblasts did not die in the laboratory following dexamethasone exposure (ex-vivo) relapsed at an alarming rate with only 25 percent still alive at the sixth year of follow up (p=0.009).

What we had succeeded in doing by Day 4 of diagnosis was something that all the known prognostic factors, like age, WBC and male vs. female could not do, namely accurately identify the responders and survivors.

Today, when I test patients in our laboratory, I consistently double or even triple the response rates over standard protocols, yet a subset of patients are not found sensitive to the available therapies. Patients who do not respond to chemotherapy are today known, in the oncologic vernacular, as “failing therapy.” If we view these “non-responders” as a biologically distinct group (not unlike the dexamethasone-resistant ALL patients above) then our role, in the field of functional profiling, is to quickly segregate the responders (to available drugs) from the non-responders and move those “non-responders” immediately to something that will work for them. In this light, patients no longer “fail therapies” but instead “therapies fail patients.” It is then our mandate to use the ex-vivo platforms to find (and yes, discover) novel therapies and combinations that will meet their unmet need.

As the New Year is upon us I am filled with the expectation that 2013 will be one of discovery and innovation. Never before have so many interesting compounds been available for study. If we are fortunate enough to succeed in our efforts to collaborate with members of the drug development community and have the opportunity to intelligently apply functional profiling, for drug discovery, 2013 could be a very good year indeed.

A Tale of Two Trials

As I read through the November 10 issue of the Journal of Clinical Oncology there were two very different but highly instructive reports.

They first examined the impact of gemtuzumab ozogamicin for patients with acute myeloid leukemia. The second involved the incorporation of bevacizumab and erlotinib into the treatment of Stage III NSCLC in combination with radiation.

By way of introduction, gemtuzumab ozogamicin (GO) is an anti CD33 antibody linked to the highly toxic chemical calicheamicin. Calicheamicin, a member of enendyne class, is among the most toxic substances known to man. By linking this poison to an antibody directed against leukemia cells, it was reasoned that this novel conjugant would provide an effective therapy for leukemia. And indeed it did. But despite compelling science and what appeared to be initially good results (particularly in older patients with AML), and FDA approval for the agent, the drug was withdrawn from the market. Now, with the publication of a new study from the United Kingdom, GO is once again in the limelight as its inclusion in induction therapy resulted in a statistically significant three-year relapse-free survival advantage (p=.0007) and three year overall survival advantage (p=.05).

It appears, with regard to GO, that the clinical trial process failed to identify the clinical utility of an active and novel form of therapy for a potentially lethal disease.

The second article of interest regards a pilot study that incorporated an anti-VGEF antibody (bevacizumab) with EGFR TKI (erlotinib) along with chemotherapy and radiation. In this trial the objective response rate of 39 percent, median progression-free survival of 10.2 months and median overall survival of 10.4 months, were not demonstrably superior to contemporary results, yet toxicity was significantly enhanced. The investigators recommended against further exploration of this combination. Here the aggressive integration of targeted and conventional therapies proved a misadventure.

While these two reports are very different, they represent similar failings of the contemporary clinical trial process. The GO experience reflects the failure to identify efficacy due to contemporary clinical trial’s dilution of the benefit in select candidates, mixed in the overall population, with limited responsiveness to the agent. The second trial represents clinicians’ desire to engage in theoretically attractive clinical trials only to find that they reflect ineffective and/or more toxic treatment regimens.

On one hand, laboratory models that accurately identify responders can segregate those most likely to benefit from those who will not. GO represents just one of many interesting new classes of drugs for whom selective methodologies could prove highly valuable. The lung cancer experience reflects the failure of the research community to dedicate adequate resources to predictive clinical models.

Combinations of chemotherapy with target therapies have been the subject of investigation in our laboratory for more than a decade. For example, we observed antagonism between platins and the EGFR antagonists (gefitinib and erlotinib) two years before publication of the unsuccessful INTACT I and II Trials and three years before the unsuccessful TALENT and TRIBUTE trials.

All four of these trials combined platin based doublets with EGF-TKI’s. More recently we successfully identified favorable interactions between erlotinib and VGEF inhibitors in individual patients that have provided durable responses in our NSCLC patients as first line therapy, now out to four and five years since diagnosis. These experiences represent opportunities to explore novel therapies and avoid inadvertent antagonisms and misadventures.  In the recent JCO, a good treatment was missed while a bad treatment was advanced.

Functional profiling through use of the EVA-PCD® assay may represent the “critical path” from bench to bedside that the deputy director of the Center for Drug Evaluation and Research at the Food and Drug Administration, Janet Woodcock has described as a crying need.

November is Lung Cancer Awareness Month

With November designated as Lung Cancer awareness month we have the opportunity to focus national attention on this disease, the leading cause of cancer death in America.

It may come as a surprise to many that lung cancer causes more deaths than prostate, breast and colorectal cancer combined. Lung cancer is the big kahuna. And up until the last several years, no one seemed to be paying much attention. It may be that people considered lung cancer a disease associated with cigarette smoking and therefore, in some way, the individual victim’s fault. However, we are now witness to a changing biology wherein the predominant histology of lung cancer, previously squamous cell, has transitioned to adenocarcinoma.

While the incidence in males has fallen, the incidence in females has risen. Strikingly, the incidence of lung cancer in non-smokers is rapidly climbing. Indeed, up to 20 percent of lung cancers today do not appear to be directly related to cigarettes or known exposures at all.

Our recent publication of a clinical trial in lung cancer patients was highly instructive. First, we were able to double the response rate and nearly double the survival through functional profiling (EVA-PCD®).

Second, there was no “right” treatment for patients. Different treatment combinations worked best for each patient with no single combination working for all.

Third, many patients did well with first line targeted agents. In fact, several long-term survivors have never received any form of cytotoxic chemotherapy, despite widely metastatic disease at presentation.

Several questions remain. Among them, the role of the repeat biopsies in patients with recurrent disease.  Several patients under my care have undergone additional biopsies each time a recurrence was documented with the new assay findings guiding us to a different treatment regimen. It is not impossible to imagine a day when cancer treatments will be modified and changed the way contemporary internists switch antihypertensives or cholesterol lowering drugs. That is, lung cancer like these maladies is becoming a chronic disease.

With several patients out over five years this strategy has served us well in select cases. A second issue surrounds the early introduction of experimental agents. Should we not have the opportunity to utilize drugs that have succeeded in Phase I trials, (and are thereby known to be safe for human administration), for patients whose cancer tissue reveals a favorable profile ex-vivo? I, for one, would relish the opportunity to administer second-generation EGFr-TKIs to c-MET inhibitors, to appropriately selected candidates. Smart drugs need smart mechanisms to get to market.

With the advent of lung cancer awareness month we have the opportunity to educate the public and expand awareness of the desperate need for advances in this disease. The disparity in funding for lung cancer patients compared with ovarian or breast cancer patients is disturbing. For every lung cancer death, there are five to 10 times more dollars expended on research to prevent breast and ovarian cancer deaths. While we applaud the successes in breast and ovarian cancer treatment we encourage lung cancer patients to call your congressperson to make lung cancer a front burner issue.

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One of our most gratifying success stories is Pat Merwin, now four years since diagnosis. Pat has organized a local (Long Beach, CA) observance of the national lung cancer awareness vigil to be held on Tuesday, November 13. I could not be happier than to be the invited speaker for this important occasion and to be with many of my patients.

The Tumor Micro Environment

As I was reading the October 1 issue of the Journal of Clinical Oncology, past the pages of advertisement by gene profiling companies, I came upon an article of very real interest.

While most scientists continue to focus on cancer-gene analyses, a report in this issue from a collaboration between American and European investigators provided compelling evidence for the role of tumor associated inflammatory cells in metastatic human cancer. (Asgharzadeh, S J Clin Oncol 30 (28)3525–3532 Oct 1, 2012) Through the analysis of children with metastatic neuroblastoma, they found that the degree of infiltration into the tumor environment by macrophages had a profound effect upon clinical outcome. This study confirmed earlier reports that macrophage infiltration is an integral part and potential driver of the malignant process.

Using immunohistochemistry and light microscopy the investigators scored patients for the number of CD163(+) macrophages, representing the alternatively activated (M2) subset within the tumor tissue. They then examined inflammation related gene expressions to develop a “high” risk, “low” risk algorithm and applied it to the progression free survival in these children.

Highly significant differences were observed between the two groups. This report adds to a growing body of literature that describes the interplay between cancer cells and their microenvironment. Similar studies in breast cancer, melanoma and multiple myeloma have shown that tumor cells “co-opt” their non-malignant counterparts as they drive transformation from benign to malignant, from in-situ to invasive and from localized disease to metastatic. These same forces have the potential to strongly influence cellular responses to stressors like chemotherapy and growth factor withdrawal. While we may now be on the verge of identifying these tumor attributes and characterizing their impact upon survival, these analyses represent little more than increasingly sophisticated prognostics.

The task at hand remains the elucidation of those attributes and features that characterize each patient’s tumor response to injury toward ultimate therapeutic response. To address this level of complexity, we need the guidance of more global measures of human tumor biology, measures that incorporate the dynamic interplay between tumors cells, their stroma, vasculature and the inflammatory environment.  These are the “real-time” insights that can only be achieved using human tissue in its native state. Ex vivo analyses offer these insights. Their information moves us from the realm of prognostics to one of predictives, and it is after all predictive measures that our patients are most desperately in need of today.