Cancer Explained – The Role of Cell Death

Following a recent blog, I received an inquiry from one of our readers. The individual asked whether I could better explain my oft repeated statement that “cancer doesn’t grow too much, it dies too little.” The questioner was puzzled by my assertion that chemotherapy drugs acted to stop cells from growing, while she had come to believe that this was synonymous with killing them. This dichotomy is at the crux of our modern understanding of cancer.

In response, I would like to examine the very basis of what is known as carcinogenesis, the process by which cancer comes to exist.

For more than a century, scientists believed that cancer cells were growing more rapidly than normal cells. They based this on serial measurements of patient’s tumors, which revealed that tumor dimensions increased. A small lump in the breast measuring one-half inch in diameter would be found six months later to be one inch in diameter. And six months after that it was two inches in diameter. This was growth, plain and simple, and so it was reasoned that cancer cells must be growing too much. As such, cancer therapies, per force of necessity, would need to stop cancer cells from growing if they were to work at all.

Dying Cell - lo resAnd then, in 1972, a paper was published in the British Journal of Cancer that described the phenomenon of apoptosis, a form of programmed cell death. Although it would be almost a decade before cancer researchers fully grasped the implications of this paper, it represented a sea change in our understanding of human tumor biology.

Let’s use the example of a simple mathematical equation. Every child would recognize the principles of the following formula:
Tumor mass = growth rate – death rate
This simple equation represents the principle of modern cancer biology. Where cancer researchers went wrong was that they mistakenly posited that the only way a tumor mass could increase was through an increase in the growth rate. However, as any child will tell you, a negative of a negative is a positive. That is, at a given growth rate, the tumor mass can also increase if you reduce the death rate. Thus, the “growth” so obvious to earlier investigators did not reflect an increase in proliferation but instead a decrease in cell attrition. Cancer didn’t grow too much it died too little, but the end result was exactly the same.

It should now be abundantly clear exactly why chemotherapy drugs, designed to stop cells from growing, didn’t work. Yes, the drugs stopped cells from growing, and yes any population of “growing cells” would suffer the effect. But they didn’t cure cancers because the cancers weren’t growing particularly fast. Indeed, the fact that chemotherapy works at all is almost an accident. Contrary to our long held belief that we were inhibiting cell proliferation, chemotherapy drugs designed to damage DNA and disrupt mitosis, were actually working (when they did at all) by forcing the cells to take inventory and decide whether they could continue to survive. If the injury were too extreme, the cells would commit suicide through the process of cell death. If the cells were not severely damaged or could repair the damage, then they carried on to fight another day. None of this, however, had anything to do with cell growth.

Systems Biology Comes of Age: Metastatic Lung Cancer in the Crosshairs

Cancer therapists have long sought mechanisms to match patients to available therapies. Current fashion revolves around DNA mutations, gene copy and rearrangements to select drugs. While every cancer patient may be as unique as their fingerprints, all of the fingerprints on file with the federal AFIS (automated fingerprint identification system) database don’t add up to a hill of genes (pun intended), if you can’t connect them to the criminal.

To continue the analogy, it doesn’t matter why the individual chose a life of crime, his upbringing, childhood traumas or personal tragedies. What matters is that you capture him in the flesh and incarcerate him (or her, to be politically correct).

The term we apply to the study of cancer, as a biological phenomenon is “systems biology.” This discipline strikes fear into the heart of molecular biologists, for it complicates their tidy algorithms and undermines the artificial linearity of their cancer pathways. We frequently allude to the catchphrase, genotype ≠ phenotype, yet it is the cancer phenotype that we must confront if we are to cure this disease.

Using a systems biology approach, we applied the ex-vivo analysis of programmed cell death (EVA-PCD®) to the study of previously untreated patients with non-small cell lung cancer. Tissue aggregates isolated from their surgical specimens were studied in their native state against drugs and signal transduction inhibitors. This methodology captures all of the interacting “systems,” as they respond to cytotoxic agents and growth factor withdrawal. The trial was powered to achieve a two-fold improvement in response.

At interim analysis, we had more than accomplished our goal. The results speak for themselves.

First: a two-fold improvement in clinical response – from the national average of 30 percent we achieved 64.5 percent (p – 0.00015).

Second: The median time to progression was improved from 6.4 to 8.5 months.

Third: And most importantly the median overall survival was improved from an average of 10 – 12 months to 21.3 months, a near doubling.

These results, from a prospective clinical trial in which previously untreated lung cancer patients were provided assay directed therapy, reflects the first real time application of systems biology to chemotherapeutics. The closest comparison for improved clinical outcome with chemotherapeutic drugs chosen from among all active agents by a molecular platform in a prospective clinical trial is . . .

Oh, that’s right there isn’t any.

The Pot Calling the Kettle Black

The January issue of the Journal of the National Comprehensive Cancer Network features a point-counterpoint on the topic of the validity of chemosensitivity assays for drug selection in recurrent ovarian cancer. Having conducted a similar exercise with Maurie Markman, MD, as a part of a special symposium at the Society of Gynecologic Oncology in New Orleans in February 2003 — attended by hundreds of gynecologic oncologists — I was surprised on several levels.

First, (and perhaps, in this case, to his credit) Dr. Markman’s position hadn’t changed whatsoever in eight years — one could virtually excerpt his commentary, verbatim from the discussion that we had almost a decade ago. His references and scientific arguments strike me as no more convincing today than they did then, but at least they are consistent.

Second, that the authors arguing in the affirmative neglected to mention seminal influences in the field. Strikingly, Dr. Larry Wiesenthal, a pioneer and mentor, was never mentioned. Of all the modern-day investigators in this field, Dr. Wiesenthal’s contributions should certainly have been referenced. Despite this, these authors do repeatedly cite the marginal contributions of other platforms.

Third, these investigators who claim that there are no published prospective clinical correlations in ovarian cancer, appear to not read their own literature. In a paper that I authored with the chairman of the Gynecologic Oncology Group (Dr. Philip DiSaia) we provided unequivocal, statistically significant evidence in a blinded prospective analysis that assay sensitivity correlated with response (P = 0.035) and time to progression (P = 0.022). (Nagourney RA., Brewer, CA., Redecki S., et al. Gynecologic Oncology ADA 35-39. 2003.)

At least in our neck of the woods, that’s called significant.

What is perhaps the most surprising aspect of these articles is the sudden, newfound interest in this field on the part of these investigators. After a decade of efforts on my and other investigator’s parts to incorporate these methods into GOG trials fell upon deaf ears, it’s surprising to me that these arguments are finally being heard. Maybe my voice, or that of pioneers like Dr. Wiesenthal, has gotten louder? I hadn’t noticed.

In the scientific literature we use statistical tools like analysis of variance (ANOVA) to discern trends and explore new findings. When I examine these two manuscripts for new insights, I find that Dr Markman’s position, to his credit, hasn’t changed; that the statistical significance of our response and survival data also hasn’t changed; that the well documented scientific basis of our work hasn’t changed. But, I do identify one new correlate associated with this sudden enthusiasm for the field. A small (but potentially loud) line found at bottom of the first page “receives research support from…”

The Frustrating Reality – When a Tumor Sample isn’t Sufficient for Testing

A dying leukemia cell

A dying leukemia cell

The principles underlying the Rational Therapeutics EVA-PCD platform reflect many years of development. Recognizing the importance of cell death measures — apoptotic and non-apoptotic — our laboratory dismissed growth-based assays. The closure of Oncotech, the principal purveyor of proliferation-based assays, illustrates the demise of a failed paradigm in the study and testing of human tumor biology. A second principal of our work is the need to examine all of the operative mechanisms of cell death (autophagic, necrotic, etc.). Laboratories that measure only one mechanism of cell death (e.g. caspase activation as a measure of apoptosis) miss important cell responses that are critical to the accurate prediction of clinical response. The third principle of our work is the maintenance of cells in their native state.

These fundamentals provide the basis of our many successes, but also a constraint. Because we do not propagate, subculture or expand tissues, we can only work with the amounts of tissue provided to us by our surgeons. While some labs propagate small biopsy samples into larger populations by growth to confluence, this introduces irreconcilable artifacts, which diminish the quality of sensitivity profiles. Avoiding this pitfall, however, demands that a tissue sample be large enough (typically 1cm3) to provide an adequate number of cells for study without growth or propagation.

This is the reason our laboratory must request biopsies of adequate size. The old computer dictum of “garbage in, garbage out” is doubly true for small tissue samples. Those that contain too few tumor cells, are contaminated, fibrotic or inadequately processed will not serve the patients who are so desperately in need of therapy selection guidance. As a medical oncologist, I am deeply disappointed by every failed assay and I am more familiar than most with the implications of a patient requiring treatment predicated on little more than intuition or randomization.

We do everything within our power to provide results to our patients. This sometimes requires low yield samples be repeatedly processed. It may also set limitations on the size of the study or, in some circumstances, forces us to report a “no go” (characterized as an assay with insufficient cells or insufficient viability). Of course, it goes without saying that we would never charge a patient for a “no-go” assay beyond a minimal set up fee (if applicable). But, more to the point, we suffer the loss of an opportunity to aid a patient in need.

Cancer patients never undergo therapy without a tissue biopsy. Many have large-volume disease at presentation, so it is virtually always possible to obtain tissue for study if a dedicated team of physicians makes the effort to get it processed and submitted to our laboratory. The time and energy required to conduct an excisional biopsy pales in comparison to the time, energy and lost opportunities associated with months of ineffective, toxic therapy.

Forms of Cell Death

Following the description of apoptosis in the British Journal of Cancer in 1972, scientists around the world incorporated the concept of programmed cell death into their cancer research. What is less understood is the fact that apoptosis is not synonymous with programmed cell death. Programmed cell death is a fundamental feature of multicellular organism biology. Mutated cells incapable of performing their normal functions self-destruct in service of the multicellular organism as a whole. While apoptosis represents an important mechanism of programmed cell death, it is only one of several cell death pathways. Apoptotic cell death occurs with certain mutational events, DNA damage, oxidative stress and withdrawal of some growth factors particularly within the immune system. Non-apoptotic programmed cell death includes: programmed necrosis, para-apoptosis, autophagic cell death, nutrient withdrawal, and subtypes associated with mis-folded protein response, and PARP mediated cell death. While apoptotic cell death follows a recognized cascade of caspase mediated enzymatic events, non-apoptotic cell death occurs in the absence of caspase activation.

With the recognition of programmed cell death as a principal factor in carcinogenesis and cancer response to therapy, there has been a growing belief that the measurement of apoptosis alone will provide the insights needed in cancer biology. This oversimplification underestimates the complexity of cell biology and suggests that cancer cells have but one mechanisms of response to injury. It has previously been shown that cancer cells that suffer lethal injury and initiate the process of apoptosis can be treated with caspase inhibitors to prevent caspase-mediated apoptosis. Of interest, these cells are not rescued from death. Instead, these cells committed to death, undergo a form of non-apoptotic programmed cell death more consistent with necrosis. Thus, commitment to death overrides mechanism of death.

Labs that focus on measurements of caspase activation can only measure apoptotic cell death. While apoptotic cell death is of importance in hematologic cancers and some solid tumors, it does not represent the mechanism of cell death in all tumors. This is why we measure all cell death events by characterizing metabolic viability at the level of cell membrane integrity, ATP content, or mitochondrial function. While caspase activation is of interest, comparably easy to measure and useful in many leukemias and lymphomas, it does not represent cancer cell death in all circumstances and can be an unreliable parameter in many solid tumors.

Probing Human Biology

Functional Analyses Unravel The Complexities of Signal Transduction

The application of functional analyses in human tumors is the topic of our upcoming presentation at the American Association of Cancer Research to be held in Washington D.C, in April 2010 (Nagourney, R. et. al, Horizontal and vertical signal pathway inhibition in human tumor primary culture micro-spheroids. Abstract 1764, to be presented Monday, April 19, 2010).

Scientists now realize that cancer biology, indeed all biology, is driven by signaling pathways. Cells speak to each other and the messages they send are interpreted via intracellular pathways known as signal transduction. Many of these pathways are activated or deactivated by phosphorylations on select cellular proteins. Tyrosine kinases, and serine/threonine kinases are among the most important classes of enzymes responsible for these chemical cascades inside the cell. In recent years small molecules have been developed to inhibit these chemical reactions. Hundreds of such compounds are in development for cancer today. While most scientists use genomic or proteomic platforms to detect mutations in these pathways that might result in response to these chemicals, we have taken a different tack. By applying functional analysis, to measure the end result of pathway activation or deactivation, we can predict whether patients will actually respond. Our results in lung cancer patients to date have exceeded the best outcomes using DNA profiles, clearly supporting the predictive accuracy use of functional analyses in this and related areas.

Focusing upon two fundamental pathways, the EGFR and the insulin-like growth factor pathway, we have explored how small molecule inhibitors influence these important survival signaling pathways. This is but one of many applications of functional profiling in the study of human tumor biology.

Chemosensitivity-Resistance Assay as Functional Profiling

Modern cancer research can be divided into three principal disciplines based upon methodology:

1.     Genomic — the analysis of DNA sequences, single nucleotide polymorphisms (SNPs), amplifications and mutations to develop prognostic and, to a limited degree, predictive information on cancer patient outcome.

2.     Proteomic — the study of proteins, largely at the level of phosphoprotein expressions.

3.     Functional — the study of human tumor explants isolated from patients to examine the effects of growth factor withdrawal, signal transduction inhibition and cytotoxic insult on cancer cell viability.

Contrary to analyte-based genomic and proteomic methodologies that yield static measures of gene or protein expression, functional profiling provides a window on the complexity of cellular biology in real-time, gauging tumor cell response to chemotherapies in a laboratory platform. By examining drug induced cell death, functional analyses measure the cumulative result of all of a cell’s mechanisms of resistance and response acting in concert. Thus, functional profiling most closely approximates the cancer phenotype.  Insights gained can determine which drugs, signal transduction inhibitors, or growth factor inhibitors induce programmed cell death in individual patients’ tumors. Functional profiling is the most clinically validated technique available today to predict patient response to drugs and targeted agents.

The Primacy of Microspheroids

After incorporating the realization that cancer biology was predicated on cell survival and not cell growth into our laboratory platform, we moved away from proliferative end points to cell death measures, and then redoubled our efforts to recreate the human tumor micro-environment in tissue culture. We immediately recognized that this required the preservation of cell-cell interactions found normally in the body as cellular clusters.

These cellular clusters better known as microspheroids, represent cohesive populations that interact directly with stroma, vasculature, inflammatory cells, and other tumor cells. Thus, the microspheroid recapitulates the human tumor environment. By applying cell death endpoints (the most rigorous of predictive measures) to these microspheroids, we have overcome most of the pitfalls encountered by earlier technologies. And, for the first time, a truly predictive human tumor model has been developed.

Of the two fundamental changes that we as a laboratory have brought to the field of chemosensitivity-resistance testing, the maintenance of cancerous tumor cells in their “native state” as microspheroids has been fundamental to our success.

Despite these important advances, many physicians have not grasped their significance. Falling back on their out-dated understanding of chemosensitivity studies that used growth-based endpoints (clonogenic, growth-to-confluence, and H3* thymidine incorporation, etc.) many physicians have failed to incorporate the use of these highly validated methodologies into their clinical practices.

A review of the published literature, correlating these more rigorous predictive methodologies with clinical outcomes, clearly establishes the validity of cell death in microspheroids as an important breakthrough in cancer treatment.

Chemosensitivity Testing That Makes Sense

Much of the controversy that has surrounded chemosensitivity-resistance assays (CSRA), reflects the fact that the majority of these tests were developed based on the erroneous belief that cancer was driven by its proliferative capacity and that the most active drugs could be chosen based upon their capacity to inhibit cancer cell growth. This led to a long series of unsuccessful attempts to predict clinical response based on cell proliferation endpoints.  Since the 1980’s we have come to realize that cancer represents a dysregulation of cell death and that effective drugs must kill cells outright (not inhibit their growth) in order to provide clinical response to patients.

The Ex Vivo Analysis of Programmed Cell Death (EVA-PCD) ® assay developed by Rational Therapeutics pioneered the application of drug induced cell death for the prediction of clinical response in cancer patients.  The EVA-PCD® assay was the first to incorporate this new understanding of cancer biology. By expanding the application of the EVA-PCD® platform to targeted therapies, RTI is now exploring new classes of compounds that function by inhibiting survival signals in cancer cells.  Many signaling pathways like the epidermal growth factor receptor (EGFr) have extracellular domains that function as cellular switches activating downstream phosphorylations following receptor ligation by proteins like EGF, amphiregulin and TGF alpha.

These mitogen activated protein kinases (MAPK) induce additional cascades of phosphorylations ultimately signaling transcription factors at the level of DNA. While these phenomena were originally thought to represent mitotic events, it is now recognized that most cells are not actively dividing, yet require all of these signaling pathway activations to remain alive. Thus, what was once described as growth factors are more likely better described as anti-death factors.

If indeed cancer doesn’t grow too much but dies too little, it is evident that effective therapies induce cell death, not growth inhibition in the patient.  This is why it is critical to apply lab analyses that measure cell death. Furthermore, as most of the signals for cell survival emanate from the extracellular environment, it is clear that cancer cells must be maintained in their native state to provide clinically relevant information. This is the basis of RTI’s human tumor microspheroid assay platform.

There is a Better Way

With several hundred compounds currently in development for the treatment of cancer, how will we scientists and clinical oncologists match these drugs to patients  in need?

Only 8 percent of drugs entering Phase I ever make it through the highly unproductive Phase II and Phase III trial mechanisms to win FDA approval, with 50 percent failing at the Phase III final stage of development!

We can stop this self-defeating strategy and apply selective methodologies to identify the best disease targets for these compounds. According to Joanne Woodcock of the FDA, modern science has provided much more information about the origin of cancer than about its treatment. She has called for a developmental effort in the pursuit of a “critical path,” from bench to bedside.

I believe that Ex Vivo Analysis of Programmed Cell Death (EVA-PCD)® is that critical pathway and can serve to streamline drug development.