Is There a Role for PI3k Inhibitors in Breast Cancer? Maybe.

Over the past decades oncologists have learned that cancer is driven by circuits known as signal transduction pathways. Signal_transduction_pathways.svgThe first breakthroughs were in chronic myelogenous leukemia (CML) where a short circuit in the gene as c-Abl caused the overgrowth of malignant blasts. The development of Imatinib (Gleevec) a c-Abl inhibitor yielded brilliant responses and durable remissions with a pill a day.

The next breakthrough came with the epidermal growth factor pathway and the development of Gefitinib (Iressa) and shortly thereafter Erlotinib (Tarceva). Good responses in lung cancers, many durable were observed and the field of targeted therapy seemed to be upon us.

220px-PI3kinaseAmong the other signal pathways that captured the imagination of the pharmaceutical industry as a potential target was phospho-inositol-kinase (PI3K). Following experimental work by Lew Cantley, PhD, who first described this pathway in 1992, more than a dozen small molecules were developed to inhibit this cell signal system.

The PI3K pathway is important for cell survival and regulates metabolic activities like glucose uptake and protein synthesis. It is associated with insulin signaling and many bio-energetic phenomena. The earliest inhibitors functioned downstream at a protein known as mTOR, and two have been approved for breast, neuroendocrine and kidney cancers. Based on these early successes, PI3K, which functions upstream and seemed to have much broader appeal, became a favored target for developmental clinical trials.

The San Antonio Breast Cancer Symposium is one of the most important forums for breast cancer research. The December 2014 meeting featured a study that combined one of the most potent PI3K inhibitors, known as Pictilisib, with a standard anti-estrogen drug, Fulvestrant, in women with recurrent breast cancer. The FERGI Trial only included ER positive patients who had failed prior treatment with an aromatase inhibitor (Aromasin, Arimidex or Femara). The patients were randomized to receive the ER blocker Fulvestrant with or without Pictilisib.

With seventeen months of follow-up there was some improvement in time to progressive disease, but this was not large enough to achieve significance and the benefit remains unproven. A subset analysis did find that for patients who were both ER (+) and PR (+) a significant improvement did occur. The ER & PR (+) patients benefitted for 7.4 months on the combination while those on single agent Fulvestrant for only for 3.7 months.

The FERGI trial is more interesting for what it did not show. And that is that patients who carried the PI3K mutation, the target of Pictilisib, did not do better than those without mutation (known as wild type). To the dismay of those who tout the use of genomic biomarkers like PI3K mutation for patient drug selection, the stunning failure to identify responders at a genetic level should send a chill down the spine of every investor who has lavished money upon the current generation of genetic testing companies.

It should also raise concerns for the new federal programs that have designated hundreds of millions of dollars on the new “Personalized Cancer Therapy Initiatives” based entirely on genomic analyses. The contemporary concept of personalized cancer care is explicitly predicated upon the belief that genomic patient selection will improve response rates, reduce costs and limit exposure to toxic drugs in patients unlikely to respond.

This unanticipated failure is only the most recent reminder that genomic analyses can only suggest the likelihood of response and are not determinants of clinical outcome even in the most enriched and carefully selected individuals. It is evident from these findings that PI3K mutation alone doesn’t define the many bioenergetic pathways associated with the phenotype. This strongly supports phenotypic analyses like EVA-PCD as better predictors of response to agents of this type, as we have shown in preclinical and clinical analyses.

Cancer Patients Need Answers Now!

I read a sad editorial in the Los Angeles Times written by Laurie Becklund, former LA Times journalist. It is, in essence, a self-written obituary as the patient describes her saga beginning almost 19 years earlier, when she detected a lump in her breast. With stage I breast cancer she underwent standard therapy and remained well for 13 years until recurrence was heralded by disease in bone, liver, lung and brain. Given a dire prognosis she became a self-made expert, conducting research, attending conferences, and joining on-line forums under the name “Won’t Die of Ignorance.” Despite her heroic effort Ms. Becklund succumbed to her illness on February 8. She was 66.

Ms. Becklunla-laurie-becklund-cropp-jpg-20150209d experienced the anguish that every patient feels when his or her own individual and highly personal needs simply aren’t being addressed. She opines that entities like the Susan G. Komen Fund, which has raised over $2.5 billion in the last 20 years, “channels only a fraction of those funds into research or assistance to help those who are already seriously sick.” She continues, “We need people, patients, doctors, scientists, politicians, industry and families to make a fresh start.” Her frustration is palpable as she states her outcome seemed to be based on the roll of the dice, like playing “Chutes and Ladders.”

The author’s plight is shared by the millions of patients who are confronting advanced cancers. They are not interested in “why” or “how” their cancers came to be. They can no longer benefit from early detection or cancer awareness campaigns. They need practical, actionable, clinical answers today.

Ms. Becklund’s commentary resonates with me and with everyone who has cOutliving Cancerancer or knows someone who does. As an oncology fellow at Georgetown, I found myself losing patient after patient to toxic and largely ineffective treatments, all despite my best efforts. I described this in my book “Outliving Cancer.” It was then that I decided that I would dedicate myself to meeting the individual needs of each of my patients and I have used a laboratory platform (EVA-PCD) to do so. I have encountered surprising resistance from clinicians and researchers who seem to prefer the glacial pace of incremental advancement found in population studies over individual solutions found in the study of each patient’s unique biology. Ms. Becklund correctly points out that every treatment must meet each individual’s need.

The role of the scientist is to answer a question (treatment A vs. treatment B) while that of the clinical physician must be to save a life. Every patient is an experiment in real time. It may well be that no two cancer patients are the same. Indeed, the complexity of carcinogenesis makes it very possible that every patient’s cancer is an entirely new disease, never before encountered. Although cancers may look alike, they may be biologically quite distinct. Meaningful advances in cancer will only occur when we learn to apply all available technologies to treat patients as the individuals that they are. Let us hope that Ms. Becklund’ s final essay does not fall upon deaf ears.

Two Women with Metastatic Breast Cancer – Same Age, Same Disease, Two Very Different Functional Profiles

A day in the life of advanced breast cancer. Two different 37-year-old breast cancer patients, both mothers of young children, were seen in consultation on the same day.

The first had been referred by a colleague who was concerned that the patient’s ER positive breast cancer had disseminated to her brain despite aggressive standard chemotherapy. She was to undergo a craniotomy and a portion of fresh tumor would be submitted from the surgery to Rational Therapeutics for EVA-PCD functional profiling.

The second mother had metastatic triple negative breast cancer, which recurred after aggressive standard chemotherapy. She underwent neo-adjuvant treatment (preoperative) but at the time of her surgery, there was no evidence of response to the treatment. By the time we met her, only months into her diagnosis, new areas of metastatic disease were cropping up daily.

Microscope Detail2-lo resThe EVA-PCD assay results on these two “similar” patients were entirely different.

The results of the first patient with the ER positive tumor and brain metastases clearly identified treatments directed toward the PI3K pathway, with or without chemotherapy. We are recommending a combination of Everolimus plus chemotherapy.

The second patient had a completely different profile. Indeed, the degree of drug resistance was quite striking. A three-drug combination was among the most active from almost two dozen drugs tested.  The other option appeared to be a new class of drugs called the cyclin dependent kinase (CDK) inhibitors.

On a functional level, we used targeted drugs to probe for sensitivity to inhibitors of these cancer signal pathways. Unlike genomic profiles that tell you whether the gene is present or absent, we can tell whether the gene is driving the tumor. Functional profiling.

One patient is now under my care and the other will begin treatment under the care of a colleague in Orange County, CA. We will await results of these assay-directed therapies and wish these two young patients every success.

Triple Negative Breast Cancer: Worse or Just Different?

The term “triple negative breast cancer” (TNBC) is applied to a subtype of breast cancers that do not express the estrogen or progesterone receptors. Nor do they overexpress the HER2 gene. This disease constitutes 15 – 20 percent of all breast cancers and has a predisposition for younger women, particularly those of black and Hispanic origin. This disease may becoming more common; although, this could reflect the greater awareness and recognition of this disease as a distinct biological entity.

On molecular profiling, TNBC has distinct features on heat maps. The usual hormone response elements are deficient, while a number of proliferation markers are upregulated.  Not surprisingly, this disease does not respond to the usual forms of therapy like Tamoxifen and the other selective estrogen response modifiers known as SERMs. Nonetheless, TNBC can be quite sensitive to cytotoxic chemotherapy. Indeed, the responsiveness to chemotherapy can provide these patients with complete remissions. Unfortunately, the disease can recur. Complete remission maintained over the first three to five years is associated with a favorable prognosis, with recurrence rates diminishing over time and late recurrences more often seen in estrogen receptor-positive cancers.

Triple negative breast cancer is not one, but many diseases.

MTOR-pathway-ger Among the subtypes are those that respond to metabolic inhibitors such as the PI3K and mTOR directed drugs. Another subset may respond to drugs that target epidermal growth factor. There are basal-types that may be somewhat more refractory to therapy, while a subset may have biology related to the BRCA mutants, characterized by DNA repair deficiencies and exquisite sensitivity to Cisplatin-based therapies. Finally, a last group is associated with androgen signaling and may respond to drugs that target the androgen receptor.

Some years ago, we used the EVA-PCD platform to study refractory patients with breast cancer and identified exquisite sensitivity to the combination of Cisplatin plus Gemcitabine in this patient group. We published our observations in the Journal of Clinical Oncology and the combination of Cisplatin or Carboplatin plus Gemcitabine has become an established part of the armamentarium in these patients.

The I-SPY-2 trial has now used genomic analyses confirming our observations for the role of platins in TNBC. This iSignal_transduction_pathways.svgn part reflects the DNA repair deficiency subtype associated with the BRCA-like biology. More recently, we have examined TNBC patients for their sensitivity to novel therapeutic interventions. Among them, the PI3K and mTOR inhibitors, as well as the glucose metabolism pathway inhibitors like Metformin. Additional classes of drugs that are revealing activity are the cyclin-dependent kinase inhibitors, some of which are moving forward through clinical trials.

One feature of triple negative breast cancer is avid uptake on PET scan. This reflects, in part, the proliferation rate of these tumors, but may also reflect metabolic changes associated with altered glucose metabolism. In this regard, the use of drugs that change mitochondrial function may be particularly active. Metformin, a member of the biguanide family influences mitochondrial metabolism at the level of AMP kinase. The activity of Metformin and related classes of drugs in triple negative breast cancer is a fertile area of investigation that we and others are pursuing.

When we examine the good response of many triple negative breast cancers to appropriately selected therapies, the potential for durable complete remissions and the distinctly different biology that TNBC represents, the question arises whether TNBC is actually a worse diagnosis, or simply a different entity that requires different thinking. We have been very impressed by the good outcome of some of our triple negative breast cancer patients and believe this a very fertile area for additional investigation

Mammography – The Evolving Story of a Diagnostic Tool

The use of low-dose radiation to detect occult breast malignancies can be traced to work done at the MD Anderson Cancer Center in the 1950s. Early published studies conducted by the “Egan technique,” correctly identified the majority of palpable cancers subsequently proven malignant at the time of surgery. As a diagnostic tool, mammography is an effective means of confirming the presence, and defining the extent, of breast pathology in woman at high risk for cancer, or who note a pamammogramslpable lump. No one is arguing the diagnostic use of this technique. Where the controversy has arisen over the last years is the use of mammography as a screening technique.

To clarify the use of terminology, screening techniques are applied to the general population to identify unrecognized disease. The popularity of mammography as a screening technique led to the recommendation that every woman over 40 should have an annual mammogram. The problem with screening techniques is that they apply a diagnostic tool to a population at low risk. This burdens the technology with numerous false positives, engendering  costs, risks, and toxicity for those who undergo unnecessary biopsies and surgery. The entire discussion came into sharper focus in the past week with the publication of a large Canadian study that examined the impact of mammographic screening over a 25-year follow up in women ages 40-59.

In this study, launched in 1980, more than 89,000 women were divided into two groups. One group underwent routine physical examination and the second group had routine physical examination combined with mammogram. There were 3,250 diagnoses of cancer in the 44,925 women who underwent mammography and 3,133 cancers diagnosed in the 44,910 women who underwent physical examination alone. Five hundred patients in the mammography group and 505 women in the control group died of their disease. While women who had mammograms were more likely to be diagnosed with breast cancer, this did not have an impact on their risk of dying from the disease. Furthermore, 22 percent of women with positive mammograms did not have cancer at definitive workup. The conclusion of paper and the accompanying editorial by Mette Kalager from Oslo, Norway, was that ”the rationale for screening by mammography needed to be urgently reassessed.”

What are the shortcomings of the study? Mammographers have claimed that the equipment used was suboptimal, leading to less sensitive detection that might have occurred with modern, high-quality digital equipment. There was also no group over 60. It is also theoretically possible that some patients obtained mammography after concluding the study, or had mammograms done during the study, contaminating the final results. Nonetheless, this is a high quality randomized study in a large population that fails to provide an impact upon survival for a widely used technique.

Prior meta-analyses conducted between the 1960s and 1980s revealed a reduction in deaths in breast cancer between 15 percent and 25 percent in the population of women age 50 to 69. Explanations for the disparity between the current study and those older studies may include the relative lack of sophistication of the population during the 1960s through 1980s, who might fail to evaluate a breast lump, thus, earlier detection would have a significant impact on those not responding to even physical evidence of disease.

A second confounding variable is the broad use of Tamoxifen, which has so profoundly influenced the natural history of breast cancer, that the earlier detection of breast cancer may be less important than the potent efficacy of anti-hormonal agents. This is an interesting wrinkle in the story, as it is contrary to most contemporary thinking that holds that early detection, not treatment is the principal influence upon better outcomes today.

So where does this study leave us?  There are several points that must be considered. The first is that mammography is a test not a treatment. Tests perform according to their performance characteristics, described as “sensitivity and specificity.” Within this framework mammograms are sensitive and specific enough to provide immense value ….in the right patient population, e.g. those at some risk for the disease in question. How you define that “risk” is the rub.

Mammograms identify the disease; they do not influence its biology. While some may demand that more sensitive equipment for the detection of disease be implemented, a different principle may underlie the findings. This would be that cancer, at virtually any stage of diagnosis, is a systemic disease with its own trajectory. Under this scenario, mammograms in an unselected population provide little more than a lead-time bias. This term is applied when a test identifies an event earlier than it might have been found, but has no impact on the ultimate outcome. Lead-time bias is a common phenomenon in screening techniques and has been the rallying cry for those who argue against PSA screening for men. Once again, the number of patients diagnosed versus the number of patients requiring intervention is the overarching dilemma.

While we seek to decipher the genetic basis of cancer using increasingly sophisticated genomic techniques, we recognize that cancer is common and that a substantial percentage of patients may not die of their disease. Cancer results from stresses that force cells to either die or seek novel mechanisms to survive. Deprived of estrogen, testosterone, nutrients, oxygen or growth factors, cells within the aging human body discover novel ways to stay alive, albeit to the detriment of the organism as a whole. However humbling, it can be argued, that it is pathways that aberrant cells pursue that guides the trajectory of the disease, largely independent of our roles as diagnosticians and treating physicians.

Future Cancer Shock: Two Lung Cancer Trials Fall Short of Goal

Hsp90 pathwayTwo related clinical trials were reported in the last several months describing the use of heat shock protein 90 (HSP90) inhibitors in lung cancer. Both trials fell short of their pre-specified endpoints casting a pall upon these drugs. However, the study of HSP90 inhibitors should not be abandoned based on these finding, as this is a fertile area of investigation and offers opportunities for the future.

Human cells marshal many defenses against stress. Thermal injury can damage basic cellular functions by denaturing (inactivating) proteins. The machinery of cells is largely comprised of protein enzymes. Excessive heat coagulates proteins much the same way the albumin of an egg turns white during cooking. The loss of fluidity and function ultimately results in cell death. The heat shock proteins come to the rescue by shepherding these proteins away from injury and protecting them from denaturation. There are many different heat shock proteins found in human cells, but one of the most abundant and active in cancer cells is known as HSP90 for its molecular weight in the range of 90-kilodaltons. Over the last two decades, investigators have explored the use of small molecules to inhibit these important proteins. Among the first compounds to be isolated and applied were derivatives of Geldanamycin. Although Geldanamycin itself is a poison that causes severe liver damage, its derivative 17-AAG, also known as Tanespimycin, has successfully entered clinical trials.

The current studies examined two other HSP90 inhibitors. One Retaspimycin, has been developed by the Infinity Pharmaceuticals. This clinical trial combined Retaspimycin with Docetaxel and compared results with Docetaxel alone in 226 patients with recurrent lung cancer. None of the patients had received Docetaxel prior to the trial. Drugs were administered every three weeks and the efficacy endpoint was survival with a subset analysis focused upon those with squamous cell cancer. The trial fell short of its pre-designated endpoint. Interestingly, the study failed to provide benefit even in patients who were specifically targeted by their tumor’s expression of the K-RAS, p53 or by elevated blood levels of HSP90, the putative biomarkers for response.

The second trial examined a different HSP90 inhibitor developed by Synta Pharmaceuticals. The drug Ganetespib was combined with Docetaxel and the combination was compared with Docetaxel alone. The results just reported indicate that the combination provided a median survival of 10.7 month, while Docetaxel alone provided a median survival of 7.4 month. Although this represented a three-month improvement, it did not meet the pre-specified target.

Taken together these results could dampen enthusiasm for these agents. This would be unfortunate, for this class of drugs is active in a number of human tumors.

Through our EVA-PCD functional profile we have observed favorable activity and synergy for the HSP90 inhibitor Geldanamycin and its derivative 17-AAG as we reported at the American Association for Cancer Research meeting in 2005 (Nagourney RA et al Proc. AACR, 2005). More importantly, 17-AAG (Tanespimycin) provided objective responses in 22 percent and clinical benefit in 59 percent of patients with recurrent HER2 positive breast cancer after these patients had failed therapy with Herceptin (Modi S. et al, Clinical Cancer Research August 2011). This clearly supports the role of HSP90 inhibition in breast cancer and would suggest that other more carefully selected target diseases could benefit as well.

The function of HSP90 is not completely understood as it influences the intracellular trafficking of dozens of proteins. One of the complexities of this class of drugs is that they protect and enhance the function of both good and bad proteins. After all, the HSP90 protein doesn’t know which proteins we as cancer doctors would like it to protect.

When we apply EVA-PCD analysis to these and other related classes of compounds, we focus our attention upon the downstream effects, namely the loss of cell survival. That is, whatever proteins are influenced, the important question remains “did that effect cause the cells to die?”

Classes of compounds with nonspecific targets like the HSP90 inhibitors will surely be the most difficult to characterize at a genomic or proteomic level: What protein? What gene? Functional platforms like the EVA-PCD offer unique opportunities to study these classes of agents. We are convinced that the HSP90 inhibitors have a role in cancer therapy. It would be unfortunate if these setbacks led us to “throw the baby out with the (hot) bathwater,” thus, slowing or preventing their use in cancer treatment.

The Information Disconnect

I recently had an interesting conversation with a physician regarding her patient with an aggressive breast cancer.

A portion of tumor had been submitted to our laboratory for analysis and we identified activity for the alkylating agents and the Taxanes, but not for Doxorubicin. After our report was submitted to the treating physician she contacted me to discuss our findings, as well as the results from a genomic/proteomic laboratory that conducted a parallel analysis upon a portion of the patient’s tumor. The physician was kind enough to forward me their report. Their results recommended doxorubicin while ours did not. The treating physician asked for my input. Here, I thought, was a “teachable moment.”

Our discussion turned to the profound difference between analyte-based laboratory tests e.g. genomic and proteomic, and functional platforms like our own (EVA-PCD). Genomic, transcriptomic and proteomic platforms measure the presence or absence of genes, RNA or protein. Gene amplification, deletions or mutations and protein and phosphoprotein expressions are examined. These platforms dichotomize patients into those who do and those who do not express the given analyte, with cutoffs for gene copy number or intensity of staining.

These platforms have worked very well in diseases where there is a linear connection between the gene (or protein) and the disease state, e.g. BCR-ABL in CML for which imatinib has proven so effective. These tests have worked reasonably well in EGFR mutated and ALK gene rearranged in lung cancer, but even here response rates and response durations have been less dramatic. However, they have not worked very well at all for the vast majority of cancers that do not carry specific and well-characterized targets. These cancers reflect polygenic phenomena and are not defined by a single gene or protein expression.

Functional platforms look at cellular response to injury at the systems level and measure the end result of drug exposure to gauge the likelihood of a clinical response. Our focus on cell biology allows us to determine whether a drug or combination induces programmed cell death. After all, regardless of what gene elements are operational, it is the ultimate eradication of the cancer clone (its loss of viability) that results in clinical response.

As we reported in a recent paper in non-small cell lung cancer, patients who revealed the most sensitive ex-vivo profile to erlotinib (Tarceva) lived far longer than the general clinical experience for those patients who were selected for erlotinib by EGFr mutation analysis alone. Some of these patients are alive at 5, even 9 years since diagnosis.

We live in a technocracy where process has taken precedence over results. We are enamored with complex scientific technologies sometimes at the expense of simple answers. A metallurgist, familiar with every last detail of the alloys used in a Boeing 747 wouldn’t necessarily be your first choice for pilot. A skilled pathologist, intimately familiar with the most detailed intricacies of human diagnostics would not likely be your preferred surgeon for cardiac bypass.

Cancer diagnosis and cancer treatment are two distinctly different disciplines. While we use the ER (estrogen receptor) status in breast cancer to select treatment, few oncologists would select Tamoxifen for their NSCLC patients even though many NSCLC patients express ER in their tissue. ER + NSCLC does not respond to tamoxifen and V600E BRAF mutated (+) colon cancer patients do not respond to vemurafenib, the very drug that works so well in BRAF V600E (+) melanoma.

Cancer is contextual and responses are not solely predicated upon the presence or absence of a gene element alone. We must use a broader brush when we paint the likeness of our patients in the laboratory, one that encompasses the vicissitudes of human biology in all of its complexities.

Where I took issue with the report, however, was its “evidence-based” moniker.  The evidentiary manuscripts cited to support the drug recommendations, with titles like “Overexpression of COX-2 in celecoxib-resistant breast cancer cell lines” provided little evidence that a (+) COX-2 finding by IHC on this patient’s biopsy specimen would offer any real hope of response. It seemed that with all of the really interesting science going on here, no one had taken the time to do the hard work to figure out whether any of these observations had a basis in reality. The failure of ERCC1 expression in lung cancer to correlate with response and survival or the Duke University debacle with gene profiling in NSCLC are just the most recent examples of how “lovely theories can be spoiled by a little fact.”

As we and our colleagues in cell profiling have actually taken the time to correlate predictions with clinical outcomes we have shown a 2.04 fold higher objective response rate (p 0.001) and significantly improved 1-year survival (p=0.02). (Apfel, C. et al Proc ASCO, 2013). To the contrary, it is of interest to examine the comparatively scant published literature on genomic and IHC profiling for drug selection under similar circumstances. While one group reported an underwhelming objective response rate of 10 percent in their study, (Von Hoff, J Clin Oncol 2010) a more recent study is even more illuminating. A Spanish group used genomic profiling in 254 colon cancer patients to select candidates for gene-targeted agents (KRAS/BRAF/PI3K/PTEN/MET) and provided therapy for 82. They reported a significantly shorter time to progression for targeted treatments compared with conventional therapies 7.9 vs 16.3 week (P<0.001) and an overall objective response rate of 1.2 percent, yes that’s 1.2% (1/82).

Human tumor biology is many things, but simple is not one of them. Reductionist thinking is not providing the insights that our patients desperately need. While we await the arrival of a perfect test for the prediction of response to cancer therapy, perhaps we as physicians and our patients should use a good one, one that works.

Of Prostate Cancer, Glucose, Metabolism and Metformin

A study conducted by Canadian investigators and reported in the September 1, 2013 issue of the Journal of Clinical Oncology examined the impact of Metformin use on mortality in men with diabetes and prostate cancer (Margel D. Urbach DR., Lipscombe LL, Metformin Use and All-Cause and Prostate Cancer-Specific Mortality Among Men with Diabetes, Journal of Clinical Oncology, volume 31, #25, pgs 3069-3075, 2013). The investigators examined 3837 patient with a median age of 75 years. They conducted a retrospective analysis examining the Ontario Province heath care records. The intent was to examine duration of exposure to Metformin as a diabetes management in patients with prostate cancer to assess the impact on all-cause and prostate cancer-specific mortality.

The results are impressive and instructive. There was a significant decrease in the risk of prostate cancer-specific and all-cause mortality, which related to the dose and duration of exposure to Metformin. The adjusted hazard ratio for the study of 0.76 indicates that there is a 24% reduction in mortality for prostate cancer-specific events with the use of Metformin. This study was not perfect, as it was retrospective, there was no randomization and it was impossible to control for all other variables such as exercise, smoking history and clinical parameters of prostate cancer. Nonetheless, there is a clear and important trend toward reduced prostate cancer and even overall mortality. This is but one of a series of clinical studies that have examined the impact of Metformin upon not only prostate cancer but also breast cancer. Much of this work was originally pioneered by Dr. Michael Pollack from McGill University in Montreal.

The biguanide class of antidiabetic drugs, originates from the French lilac or goat's rue (Galega officinalis), a plant used in folk medicine for several centuries.  (Wikipedia)

The biguanide class of antidiabetic drugs, originates from the French lilac or goat’s rue (Galega officinalis). (Wikipedia)

Metformin and the closely related Phenformin are members of the class of drugs known as biguanides. While the exact mode of action of the biguanides is not fully understood, they are known to disrupt mitochondrial respiration at complex I. This upregulates an enzyme known as adenosine monophosphate kinase (AMPK) thereby altering energy metabolism within the cell and down regulating mTOR. In diabetics, this drives down blood glucose to control the disease. However, in cancer patients, a profound effect is observed that suppresses synthetic pathways necessary for energy metabolism, cellular survival and cellular proliferation. These effects appear responsible for the impact upon prostate cancer. Interestingly, these drugs are more effective in controlling already transformed cells and less effective in the prevention of cancer. This is consistent with the observation that malignantly transformed cells change their state of metabolism.

This article is interesting on many levels. The first and most obvious is that this relatively inexpensive and well-tolerated drug can have an impact on prostate cancer.

Secondly, these effects appear to cross the lines of different cancer types, such that breast cancer and other forms of cancer might also be successfully treated.

The third note of interest shows that even patients without diabetes can tolerate Metformin, suggesting this as an adjunct to many different treatments. Finally and most importantly this represents the new and important recognition that cancer is not a genomic disorder, but a metabolic disorder. Cancer may utilize normal genetic elements to its own advantage. AMP kinase, LKB1 and mTOR are not unique to cancer, but instead, are found in every cell. These normal proteins are simply altered in their function in malignantly transformed cells. Metformin is one of what will soon be a large number of metabolomic agents entering the clinical arena as cancer research moves from the nucleus to the mitochondrion.

Does Chemotherapy Work? Yes and No.

A doctor goes through many stages in the course of his or her career. Like Jacques’ famous soliloquy in Shakespeare’s “As you Like It,” the “Seven Ages of Man,” there are similar stages in oncologic practice.

In the beginning, fresh out of fellowship, you are sure that your treatments will have an important impact on every patient’s life. As you mature, you must accept the failures as you cling to your successes. Later still, even some of your best successes become failures. That is, patients who achieve complete remissions and return year after year for follow-up with no evidence of disease, suddenly present with, a pleural effusion, an enlarged liver or a new mass in their breast and the whole process begins again.

I met with just such a patient this week. Indeed when she arrived for an appointment, I only vaguely remembered her name. After all, it had been 13 years since we met. When she reintroduced herself I realized that I had studied her breast cancer and had found a very favorable profile for several chemotherapy drugs. As the patient resided in Orange County, CA, she went on to receive our recommended treatment under the care of one of my close colleagues, achieving an excellent response to neo-adjuvant therapy, followed by surgery, additional adjuvant chemotherapy, and radiation. Her decade long remission reflected the accuracy of the assay drug selection. She was a success story, just not a perfect success story. After all, her large tumor had melted away using the drugs we recommended and her 10 year disease-free interval was a victory for such an aggressive cancer.

A dying leukemia cell

A dying leukemia cell

So what went wrong? Nothing, or more likely, everything. Cancer chemotherapy drugs were designed to do one thing very well, stop cancer cells from dividing. They target DNA synthesis and utilization, damage the double helix or disrupt cell division at the level of mitosis. All of these assaults upon normal cellular physiology target proliferation. Our century long belief that cancer was a disease of cell growth had provided us a wealth of growth-inhibiting drugs. However, in the context of our modern understanding of cancer as a disease of abnormal cell survival (and the need to kill cells outright to achieve remissions), the fact that these drugs worked at all can now be viewed as little more than an accident. Despite chemotherapy’s impact on cell division, it is these drugs unintended capacity to injure cells in ways they cannot easily repair, (resulting in programmed cell death) that correlates with response. Cancer, as a disease, is relatively impervious to growth inhibition, but can in select patients be quite sensitive to lethal injury. While cancer drugs may have been devised as birth control devices, they work, when they do work at all, as bullets.

There is an old joke about aspirin for birth control. It seems that aspirin is an effective contraceptive. When you ask how this simple headache remedy might serve the purpose, the explanation is that an aspirin tablet held firmly between the knees of a young woman can prevent conception. The joke is emblematic of chemotherapy’s effect on cancer as a drug designed for one purpose, but can prove effective through some other unanticipated mechanism.

Chemotherapy does work. It just does not work in a manner reflective of its conceptualization or design. Not surprisingly it does not work very well and rarely provides curative outcomes. Furthermore, its efficacy comes at a high price in toxicity with that toxicity reflecting exactly what the chemotherapy drugs were designed to do; stop cells from growing.  It seems that the hair follicles, bone marrow, immune system, gastrointestinal mucosa and reproductive tissues are all highly proliferative cells in their own right. Not surprisingly, chemotherapy extracts a heavy price on these normal (proliferative) tissues. It is the cancer cells, relatively quiescent throughout much of their lives that escape the harmful effects.

As a medical oncologist in the modern era, I have recognized only too well the shortcomings of conventional cytotoxic drugs. It is for this reason that I use a laboratory platform to select the most effective drugs from among the many badly designed agents. Culling from the herd those few good drugs capable of inducing lethal injury these are the ones that the EVA-PCD assay selects for our patients. Applying this approach, we have doubled responses and prolonged survivals.

Over the past decade we have focused increasingly on the new signal transduction inhibitors and growth factor down regulators. If we can double the response rates and improve survivals using our laboratory assay to select among bad drugs, just imagine what our response rates will be when we apply this approach to good drugs.

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.