In Cancer – If It Seems Too Good to Be True, It Probably Is

The panoply of genomic tests that have become available for the selection of chemotherapy drugs and targeted agents continues to grow. Laboratories across the United States are using gene platforms to assess what they believe to be driver mutations and then identify potential treatments.

Among the earliest entrants into the field and one of the largest groups, offers a service that examines patient’s tumors for both traditional chemotherapy and targeted agents. This lab service was aggressively marketed under the claim that it was “evidence-based.” A closer examination of the “evidence” however, revealed tangential references and cell-line data but little if any prospective clinical outcomes and positive and negative predictive accuracies.

I have observed this group over the last several years and have been underwhelmed by the predictive validity of their methodologies. Dazzled by the science however, clinical oncologists began sending samples in droves, incurring high costs for these laboratory services of questionable utility.

In an earlier blog, I had described some of the problems associated with these broad brush genomic analyses. Among the greatest shortcomings are Type 1 errors.  These are the identification of the signals (or analytes) that may not predict a given outcome. They occur as signal-to-noise ratios become increasingly unfavorable when large unsupervised data sets are distilled down to recommendations, without anyone taking the time to prospectively correlate those predictions with patient outcomes.

Few of these companies have actually conducted trials to prove their predictive values. This did not prevent these laboratories from offering their “evidence-based” results.

In April of 2013, the federal government indicted the largest purveyor of these techniques.  While the court case goes forward, it is not surprising that aggressively marketed, yet clinically unsubstantiated methodologies ran afoul of legal standards.

A friend and former professor at Harvard Business School once told me that there are two reasons why start-ups fail.  The first are those companies that “can do it, but can’t sell it.”  The other types are companies that “can sell it, but can’t do it.”  It seems that in the field of cancer molecular biology, companies that can sell it, but can’t do it, are on the march.

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.

Cancer Treatment – A Husband’s View

Gary Brutsch

Guest blogger – Gary Brutsch

Dr. Nagourney is currently attending an international conference where he is an invited speaker. During his absence we will have guest bloggers sharing their views on chemosensitivity testing and the EVA-PCD® assay. Our first guest is Gary Brustch.

Five years ago, my wife of otherwise good health was diagnosed with Stage IV uterine cancer. Following a surgical “solution,” we commenced our search for the next best alternative to just waiting for the disease to take its course.

We settled on a protocol supervised by a major cancer treatment center in Texas. For a total of six months, my wife, Tina, was treated with a combination of chemotherapies. During this treatment we continued to look for medical care that was more scientific-based.

At the conclusion of their protocol, we were notified that the course of treatment had not been successful. At this time Tina’s cancer marker numbers were approaching 800. Two days after this notification we decided that our final option was to contact Robert Nagourney, MD, at Rational Therapeutics in Long Beach, CA.

Our decision was based on the belief that his tumor sensitivity based chemo architecture was probably a more effective method to treat her tumor growth.

After obtaining a tumor sample from Tina and subjecting it to a laboratory process (assay testing), Dr. Nagourney prescribed a specific chemotherapy cocktail for her treatment. After one month of supervised treatment, Tina’s cancer marker number was under one hundred.

We are now into our fourth year of maintenance supervised by Dr. Nagourney. Our united opinion seems to say that, as health challenged individuals we must demand that caregivers treat our health challenges on a focused, individual basis.

We cannot accept that one category of chemotherapy is good for all.

Why Oncologists Don’t Like In Vitro Chemosensitivity Tests

In human experience, the level of disappointment is directly proportional to the level of expectation. When, for example, the world was apprised of the successful development of cold fusion, a breakthrough of historic proportions, the expectations could not have been greater. Cold fusion, the capacity to harness the sun’s power without the heat and radiation, was so appealing that people rushed into a field about which they understood little. Those who remember this episode during the 1990s will recall the shock and dismay of the scientists and investors who rushed to sponsor and support this venture only to be left out in the cold when the data came in.

Since the earliest introduction of chemotherapy, the ability to select active treatments before having to administer them to patients has been the holy grail of oncologic investigation. During the 1950s and 60s, chemotherapy treatments were punishing. Drugs like nitrogen mustard were administered without the benefit of modern anti-emetics and cancer patients suffered every minute. The nausea was extreme, the bone marrow suppression dramatic and the benefits – marginal at best. With the introduction of cisplatin in the pre Zofran/Kytril era, patients experienced a heretofore unimaginable level of nausea and vomiting. Each passing day medical oncologists wondered why they couldn’t use the same techniques that had proven so useful in microbiology (bacterial culture and sensitivity) to select chemotherapy.

And then it happened. In June of 1978, the New England Journal of Medicine (NEJM) published a study involving a small series of patients whose tumors responded to drugs selected by in vitro (laboratory) chemosensitivity. Eureka! Everyone, everywhere wanted to do clonogenic (human tumor stem cell) assays. Scientists traveled to Tucson to learn the methodology. Commercial laboratories were established to offer the service. It was a new era of cancer medicine. Finally, cancer patients could benefit from effective drugs and avoid ineffective ones. At least, it appeared that way in 1978.

Five years later, the NEJM published an update of more than 8,000 patients who had been studied by clonogenic assay. It seemed that with all the hype and hoopla, this teeny, tiny little detail had been overlooked: the clonogenic assay didn’t work. Like air rushing out of a punctured tire, the field collapsed on itself. No one ever wanted to hear about using human tumor cancer cells to predict response to chemotherapy – not ever!

In the midst of this, a seminal paper was published in the British Journal of Cancer in 1972 that described the phenomenon of apoptosis, a form of programmed cell death.  All at once it became evident exactly why the clonogenic assay didn’t work. By re-examining the basic tenets of cancer chemosensitivity testing, a new generation of assays were developed that used drug induced programmed cell death, not growth inhibition. Cancer didn’t grow too much, it died too little. And these tests proved it.

Immediately, the predictive validity improved. Every time the assays were put to the test, they met the challenge. From leukemia and lymphoma to lung, breast, ovarian, and even melanoma, cancer patients who received drugs found active in the test tube did better than cancer patients who received drugs that looked inactive. Eureka! A new era of cancer therapy was born. Or so it seemed.

I was one of those naive investigators who believed that because these tests worked, they would be embraced by the oncology community. I presented my first observations in the 1980s, using the test to develop a curative therapy for a rare form of leukemia. Then we used this laboratory platform to pioneer drug combinations that, today, are used all over the world. We brought the work to the national cooperative groups, conducted studies and published the observations. It didn’t matter. Because the clonogenic assay hadn’t worked, regardless of its evident deficiencies, no one wanted to talk about the field ever again.

In 1600, Giordano Bruno was burned at the stake for suggesting that the universe contained other planetary systems. In 1634, Galileo Galilei was excommunicated for promoting the heliocentric model of the solar system. Centuries later, Ignaz Semmelweis, MD, was committed to an insane asylum after he (correctly) suggested that puerperal sepsis was caused by bacterial contamination. A century later, the discoverers of helicobacter (the cause of peptic ulcer disease) were forced to suffer the slings and arrows of ignoble academic fortune until they were vindicated through the efforts of a small coterie of enlightened colleagues.

Innovations are not suffered lightly by those who prosper under established norms. To disrupt the standard of care is to invite the wrath of academia. The 2004 Technology Assessment published by Blue Cross/Blue Shield and ASCO in the Journal of Oncology and ASCO’s update seven years later, reflect little more than an established paradigm attempting to escape irrelevance.

Cancer chemosensitivity tests work exactly according to their well-established performance characteristics of sensitivity and specificity. They consistently provide superior response and, in many cases, time to progression and even survival. They can improve outcomes, reduce costs, accelerate research and eliminate futile care. If the academic community is so intent to put these assays to the test, then why have they repeatedly failed to support the innumerable efforts that our colleagues have made over the past two decades to fairly evaluate them in prospective randomized trials? It is time for patients to ask exactly why it is that their physicians do not use them and to demand that these physicians provide data, not hearsay, to support their arguments.

Chemosensitivity Testing – What It Is and What It Isn’t

Several weeks ago I was consulted by a young man regarding the management of his heavily pre-treated, widely metastatic rectal carcinoma. Upon review of his records, it was evident that under the care of both community and academic oncologists he had already received most of the active drugs for his diagnosis. Although his liver involvement could easily provide tissue for analysis, I discouraged his pursuit of an assay. Despite this, he and his wife continued to pursue the option.

As I sat across from the patient, with his complicated treatment history in hand, I was forced to admit that he looked the picture of health. Wearing a pork pie hat rakishly tilted over his forehead, I could see few outward signs of the disease that ravaged his body. After a lengthy give and take, I offered to submit his CT scans to our gastrointestinal surgeon for his opinion on the ease with which a biopsy could be obtained. I then dropped a note to the patient’s local oncologist, an accomplished physician who I respected and admired for his practicality and patient advocacy.

A week later, I received a call from the patient’s physician. Though cordial, he was puzzled by my willingness to pursue a biopsy on this heavily treated individual. I explained to him that I was actually not highly motivated to pursue this biopsy, but instead had responded to the patient’s urging me to consider the option. I agreed with the physician that the conventional therapy options were limited but noted that several available drugs might yet have a role in his management including signal transduction inhibitors.

I further explained that some patients develop a process of collateral sensitivity, whereby resistance to one class of drugs (platins, for example) can enhance the efficacy of other class of drugs (such as, antimetabolite) Furthermore, patients may fail a drug, then be treated with several other classes of agents, only then a year of two later, manifest sensitivity to the original drug.

Our conversation then took a surprising turn. First, he told me of his attendance at a dinner meeting, some 25 years earlier, where Dan Von Hoff, MD, had described his experiences with the clonogenic assay. He went on to tell me how that technique had been proven unsuccessful finding a very limited role in the elimination of “inactive” drugs with no capacity to identify “active “drugs. He finished by explaining that these shortcomings were the reason why our studies would be unlikely to provide useful information.

I found myself grasping for a handle on the moment. Here was a colleague, and collaborator, who had heard me speak on the topic a dozen times. I had personally intervened and identified active treatments for several of his patients, treatments that he would have never considered without me. He had invited me to speak at his medical center and spoke glowingly of my skills. And yet, he had no real understanding of what I do. It made me pause and wonder whether the patients and physicians with whom I interact on a daily basis understand the principles of our work. For clarity, in particular for those who may be new to my work, I provide a brief overview.

1.    Cancer patients are highly individual in their response to chemotherapies. This is why each patient must be tested to select the most effective drug regimen.

2.    Today we realize that cancer doesn’t grow too much it dies too little. This is why older growth-based assays didn’t work and why cell-death-based assays do.

3.    Cancer must be tested in their native state with the stromal, vascular and inflammatory elements intact. This is why we use microspheroids isolated directly from patients and do not grow or subculture our specimens.

4.    Predictions of response are not based on arbitrary drug concentrations but instead reflect the careful calibration of in vitro findings against patient outcomes – the all-important clinical database.

5.    We do not conduct drug resistance assays. We conduct drug sensitivity assays. These drug sensitivity assays have been shown statistically significantly to correlate with response, time to progression and survival.

6.    We do not conduct genomic analyses for there are no genomic platforms available today that are capable of reproducing the complexity, cross-talk, redundancy or promiscuity of human tumor biology.

7.    Tumors manifest plasticity that requires iterative studies. Large biopsies and sometimes multiple biopsies must be done to construct effective treatment programs.

8.    With chemotherapy, very often more is not better.

9.    New drugs are not always better drugs.

10.   And finally, cancer drugs do not know what diseases they were invented for.
While we could continue to enumerate the principles that guide our practice, one of the more important principles is humility. Medicine is a humbling experience and cancer medicine even more so. Patients often know more than their doctors give them credit for. Failing to incorporate a patient’s input, experience and wishes into the treatment programs that we design, limits our capacity to provide them the best outcome.

With regard to my colleague who seemed so utterly unfamiliar with these concepts, indeed for a large swath of the oncologic community as a whole, I am reminded of the saying “There’s none so blind as those who will not see.”

The Unfulfilled Promise of Genomic Analysis

In the March 8 issue of the New England Journal of Medicine, investigators from London, England, reported disturbing news regarding the predictive validity and clinical applicability of human tumor genomic analysis for the selection of chemotherapeutic agents.

As part of an ongoing clinical trial in patients with metastatic renal cell carcinoma (the E-PREDICT) these investigators had the opportunity to conduct biopsies upon metastatic lesions and then compare their genomic profiles with those of the primary tumors. Their findings are highly instructive, though not terribly unexpected. Using exon-capture they identified numerous mutations, insertions and deletions. Sanger sequencing was used to validate mutations. When they compared biopsy specimens taken from the kidney they found significant heterogeneity from one region to the next.

Similar degrees of heterogeneity were observed when they compared these primary lesions with the metastatic sites of spread. The investigators inferred a branched evolution where tumors evolved into clones, some spreading to distant sites, while others manifested different features within the primary tumor themselves. Interestingly, when primary sites were matched with metastases that arose from that site, there was greater consanguinity between the primary and met than between one primary site and another primary site in the same kidney. Another way of looking at this is that your grandchildren look more like you, than your neighbor.

Tracking additional mutations, these investigators found unexpected changes that involved histone methyltransferase, histone d-methyltransferase and the phosphatase and tensin homolog (PTEN). These findings were perhaps among the most interesting of the entire paper for they support the principal of phenotypic convergence, whereby similar genomic changes arise by Darwinian selection. This, despite the observed phenotypes arising from precursors with different genomic heritages. This fundamental observation suggests that cancers do not arise from genetic mutation, but instead select advantageous mutations for their survival and success.

The accompanying editorial by Dr. Dan Longo makes several points worth noting.  First he states that “DNA is not the whole story.” This should be familiar to those who follow my blogs, as I have said the same on many occasions.  In his discussion, Dr Longo then references Albert Einstein, who said “Things should be made as simple as possible, but not simpler.” Touché.

I appreciate and applaud Dr. Longo’s comments for they echo our sentiments completely. This article is only the most recent example of a growing litany of observations that call into question molecular biologist’s preternatural fixation on genomic analyses. Human biology is not simple and malignantly transformed cells more complex still. Investigators who insist upon using genomic platforms to force disorderly cells into artificially ordered sub-categories, have once again been forced to admit that these oversimplifications fail to provide the needed insights for the advancement of cancer therapeutics. Those laboratories and corporations that offer “high price” genomic analyses for the selection of chemotherapy drugs should read this and related articles carefully as these reports portend a troubling future for their current business model.

Looking Beyond the Academic Walls for Cancer Care

At the recent Society for Integrative Oncology meeting in Cleveland, Ohio, I had the opportunity as an invited lecturer, to sit in on many informative presentations. As I listened to these investigators, who have developed clinical therapy programs combining traditional chemotherapies with dietary, lifestyle and herbal remedies, I felt a sense of shared frustration. Here, after all, were dedicated therapists using available non-toxic interventions to improve outcomes, yet the major academic centers continue to turn a blind eye to their contributions. Instead they are required to meet stringent research criteria that those within conventional therapy might be unable to meet.

I then realized that cancer patients must step outside the confines of usual and customary referral patterns and treatment programs to obtain the best outcome for themselves. I was favorably impressed by the dedication of the many investigators and feel convinced that the application of natural products, supportive measures, dietary and lifestyle modifications, and the judicious use of chemotherapeutics will indeed lead the way to a better future in oncology.

As I often say to my patients, “No one is more interested in saving your life than you.”

Why Some Patients Refuse Chemotherapy – And Why Some of Them Shouldn’t

In the June 13, 2011, issue of Time magazine, Ruth Davis Konigsberg described cancer patients who refuse to take potentially lifesaving therapy. Her article, titled “The Refuseniks – why some cancer patients reject their doctor’s advice,” examined the rationale applied by patients who decline chemotherapy. Many of these patients are rational, articulate, intelligent and capable individuals. While there are those who by virtue of religious belief, underlying depression, or loss of loved ones, decline interventions, many of these patients make compelling arguments in favor of their decisions.

When we examine the basis of these patients’ therapeutic nihilism, much of it reflects the uncertainty of benefit combined with the certainty of toxicity. What these patients articulate is the fundamental dilemma confronted by cancer patients, what we might describe as their logical assessment of “return on investment.”

Everything in life is based on probabilities. Will your husband or wife be true? Will you have a boy or a girl? Will you live to see retirement? Will your nest egg be adequate? Cancer medicine is no different.

Will the treatment I’m being offered extend my life long enough to be worth the short- and medium-term toxicities that I will certainly suffer?

While I cannot address this question with regard to surgery or radiation, I feel uniquely qualified to do so in the context of chemotherapy. What, after all, is a chemosensitivity assay? When correctly performed, it is a laboratory test that dichotomizes groups of patients with average likelihoods of response (e.g. 20%, 30%, 40%, etc.) into those who are more or less likely to respond based on the results. On average, a patient found sensitive in vitro has a twofold improvement in response, while those found resistant have a demonstrably lower likelihood of benefit. We have now shown this to be true in breast, ovarian, and non-small cell lung cancers, as well as melanoma, childhood and adult leukemias, and other diseases.

To address the misgivings of the Refuseniks, we might ask the following question: Would you take a treatment that provided a 30 percent likelihood of benefit? How about a 40 percent? 50 percent? 60 percent? 70 percent? Or 80 percent? While many might decline the pleasure of chemotherapy at a 20-30 percent response rate, a much larger number would look favorably upon a 70 percent response rate. On the flipside, a patient offered a treatment with a 50 percent likelihood of benefit (on average), who by virtue of a lab study realizes that their true response rate is closer to 19 percent (based on resistance in vitro), might very logically (and defensibly) decline treatment. These real life examples reflect the established performance characteristics of our laboratory tests (Nagourney, RA. Ex vivo programmed cell death and the prediction of response to chemotherapy. Current Treatment Options in Oncology 2006, 7:103-110.).

Rather than bemoan the uncertainties of treatment outcome, shouldn’t we, as clinical oncologists, be addressing these patients’ very real misgivings with data and objective information? I, for one, believe so.

The False Economy of Genomic Analyses

We are witness to a revolution in cancer therapeutics. Targeted therapies, named for their capacity to target specific tumor related features, are being developed and marketed at a rapid pace. Yet with an objective response rate of 10 percent (Von Hoff et al JCO, Nov 2011) reported for a gene array/IHC platform that attempted to select drugs for individual patients we have a long way to go before these tests will have meaningful clinical applications.

So, let’s examine the more established, accurate and validated methodologies currently in use for patients with advanced non-small cell lung cancer. I speak of patients with EGFR mutations for which erlotinib (Tarceva®) is an approved therapy and those with ALK gene rearrangements for which the drug crizotinib (Xalkori®) has recently been approved.

The incidence of ALK gene rearrangement within patients with non-small cell lung cancer is in the range of 2–4 percent, while EGFR mutations are found in approximately 15 percent. These are largely mutually exclusive events. So, let’s do a “back of the napkin” analysis and cost out these tests in a real life scenario.

One hundred patients are diagnosed with non-small cell lung cancer.
•    Their physicians order ALK gene rearrangement     $1,500
•    And EGFR mutation analysis     $1,900
•    The costs associated $1,500 + $1,900 x 100 people =    $340,000
Remember, that only 4 percent will be positive for ALK and 15 percent positive for EGFR. And that about 80 percent of the ALK positive patients respond to crizotinib and about 70 percent of the EGFR positive patients respond to erlotinib.

So, let’s do the math.

We get three crizotinib responses and 11 erlotinib responses: 3 + 11 = 14 responders.
Resulting in a cost per correctly identified patient =     $24,285

Now, let’s compare this with an ex-vivo analysis of programmed cell death.

Remember, the Rational Therapeutics panel of 16+ drugs and combinations tests both cytotoxic drugs and targeted therapies. In our soon to be published lung cancer study, the overall response rate was 65 percent. So what does the EVA/PCD approach cost?

Again one hundred patients are diagnosed with non-small cell lung cancer.
•    Their physicians order an EVA-PCD analysis    $4,000
•    The costs associated: $4,000 x 100 people =    $400,000
•    With 65 percent of patients responding, this
constitutes a cost per correctly identified patient =     $6,154

Thus, we are one quarter the cost and capable of testing eight times as many options. More to the point, this analysis, however crude, reflects only the costs of selecting drugs and not the costs of administering drugs. While, each of those patients selected for therapy using the molecular profiles will receive an extraordinarily expensive drug, many of the patients who enjoy prolonged benefit using EVA/PCD receive comparatively inexpensive chemotherapeutics.

Furthermore, those patients who test negative for ALK and EGFR are left to the same guesswork that, to date has provided responses in the range of 30 percent and survivals in the range of 12 months.

While the logic of this argument seems to have escaped many, it is interesting to note how quickly organizations like ASCO have embraced the expensive and comparatively inefficient tests. Yet ASCO has continued to argue against our more cost-effective and broad-based techniques.

No wonder we call our group Rational Therapeutics.

Are New Cancer Drugs Always Better?

Few cancers instill a greater sense of fear in the medical oncologist that metastatic renal cell carcinoma, the most common form of which is known as clear cell cancer. This type of kidney cancer — driven by a mutation in a gene know as VHL — spreads rapidly, metastasizes to almost any and all organs and historically responded to almost no therapies. The development of Interleukin-2 (IL-2) in the 1980s offered a glimmer of hope. Yet, even this breakthrough ultimately yielded complete and durable responses in a mere 10 percent of patients.

By focusing on the hyper-vascular nature of this disease, investigators then developed a second line of defense that attacked the blood supply of these cancers. Following the introduction of Avastin, a number of small molecule VEGF inhibitors were introduced. Most recently, a class of drugs known as mTOR inhibitors gained popularity by providing objective responses and showing evidence of improved survival.

But what happens when all the really “hot new drugs” fail to provide benefit?

This was a question I confronted in a charming, 68-year-old neurologist who traveled to visit me from Stanford University where he received highly appropriate, yet unfortunately ineffective therapy. The patient presented in July 2010 with rapidly progressive kidney cancer that had overtaken his lungs. He was started on oral Sutent (the treatment of choice). His management was complicated by a hemolytic anemia. When I met the patient in October, I was concerned that he could not survive long enough to take on another treatment, no matter how effective it might ultimately prove to be.

As a physician, he beseeched me to study his tumor in the hope of finding any therapy to salvage him from his rapidly deteriorating course. A small biopsy was obtained with the help of one of our surgical colleagues. The results were striking — no evidence of activity for sorafenib, sunitinib (Sutent), nor the Rapalogs (Rapamycin derivatives). In one fell swoop, all of the newest therapies were swept aside with little likelihood of benefit. Despite the established literature, this patient was clearly sensitive to chemotherapeutics. It was evident to me that the treatment outline, a combination of three drugs, could provide meaningful clinical benefit if the patient could tolerate even the most modest associated side effects. With the kind cooperation of the treating physician in Northern California, our recipe was followed to a T.

The treating oncologist pulled no punches in his description of this patient’s prognosis. Nonetheless, he kindly assisted in the management of the treatment we described. While the cancer-related hemolytic anemia raged, and the patient fought for air, the treatments were delivered. Too ill to leave the hospital, his entire first course of therapy was delivered on an inpatient basis.

For several weeks, we anticipated the worst. And then, a phone call from a chipper-sounding patient. Breathing comfortable, his chest x-ray had cleared, his anemia had resolved and he was being readied for discharge. A short time later, an abdominal ultrasound revealed measurable improvement in the kidney cancer, further confirming objective response.

The patient, now home, could not be happier. The excellent outcome is as gratifying as it is unexpected. There is no question that no one else would have given this treatment. And there is further no question that the patient would not be alive today had he not received it. There are many lessons to be learned from this experience. Among them, that every patient deserves the opportunity to get better; that laboratory analyses can identify unexpected options for patients, even with the worst malignancies; that new drugs aren’t always better drugs; and finally, that nothing succeeds like success.