November is Lung Cancer Awareness Month

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

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

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

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

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

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

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

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

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

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

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.

Type I Error

Scientific proof is rarely proof, but instead our best approximation. Beyond death and taxes, there are few certainties in life. That is why investigators rely so heavily on statistics.

Statistical analyses enable researchers to establish “levels” of certainty. Reported as “p-values,” these metrics offer the reader levels of statistical significance indicating that a given finding is not simply the result of chance. To wit, a p-value equal to 0.1 (1 in 10) means that the findings are 90 percent likely to be true with a 10 percent error. A p-value of 0.05 (1 in 20) tells the reader that the findings are 95 percent likely to be true. While a p-value equal to 0.01 (1 in 100) tells the reader that the results are 99 percent likely to be true. For an example in real time, we are just reporting a paper in the lung cancer literature that doubled the response rate for metastatic disease compared with the national standard. The results achieved statistical significance where p = 0.00015.  That is to say, that there is only 15 chances out of 100,000 that this finding is the result of chance.

Today, many laboratories offer tests that claim to select candidates for treatment. Almost all of these laboratories are conducting gene-based analysis. While there are no good prospective studies that prove that these genomic analyses accurately predict response, this has not prevented these companies from marketing their tests aggressively. Indeed, many insurers are covering these services despite the lack of proof.

So let’s examine why these tests may encounter difficulties now and in the future. The answer to put it succinctly is Type I errors. In the statistical literature, a Type I error occurs when a premise cannot be rejected.  The statistical term for this is to reject the “null” hypothesis. Type II errors occur when the null hypothesis is falsely rejected.

Example: The scientific community is asked to test the hypothesis that Up is Down. Dedicated investigators conduct exhaustive analyses to test this provocative hypothesis but cannot refute the premise that Up is Down. They are left with no alternative but to report according to their carefully conducted studies that Up is Down.

The unsuspecting recipient of this report takes it to their physician and demands to be treated based on the finding. The physician explains that, to his best recollection, Up is not Down.  Unfazed the patient, armed with this august laboratory’s result, demands to be treated accordingly. What is wrong with this scenario? Type I error.

The human genome is comprised of more than 23,000 genes: Splice variants, duplications, mutations, SNPs, non-coding DNA, small interfering RNAs and a wealth of downstream events, which make the interpretation of genomic data highly problematic. The fact that a laboratory can identify a gene does not confer a certainty that the gene or mutation or splice variant will confer an outcome. To put it simply, the input of possibilities overwhelms the capacity of the test to rule in or out, the answer.

Yes, we can measure the gene finding, and yes we have found some interesting mutations. But no we can’t reject the null hypothesis. Thus, other than a small number of discreet events for which the performance characteristics of these genomic analyses have been established and rigorously tested, Type I errors undermine and corrupt the predictions of even the best laboratories. You would think with all of the brainpower dedicated to contemporary genomic analyses that these smart guys would remember some basic statistics.

Empowering Patients Towards Personalized Cancer Care

We have one more guest blogger to introduce during Dr. Nagourney’s absence: Patricia Merwin. Pat just celebrated her fourth anniversary of wellness after receiving a diagnosis of metastatic lung cancer.

In July of 2011, I attended a local TEDx conference in Long Beach, CA where Dr. Robert Nagourney gave a compelling talk about the nature of his work and the future of cancer care. TED is a global organization with a mission to “share ideas worth spreading,” a very appropriate forum for Dr. Nagourney to share his insights into cancer and how to defeat it.

Just three months earlier, at another TEDx event in the Netherlands, Dave deBronkart also gave a talk about the future of cancer care.  Dave deBronkart, better known as “E-patient Dave,” was diagnosed in January 2007 with a rare and terminal kidney cancer.  Given a dismal prognosis, Dave refused to cede his life to “standard care.”  Instead, he turned to a group of fellow patients online and found the information that eventually led to a treatment that saved his life. Dave deBronkart has since become a prolific online patient advocate and an internationally renowned speaker on the subject of patient empowerment and participatory medicine.

Like e-Patient Dave, I was given a “dismal prognosis” when I was diagnosed in 2008 with advanced metastatic lung cancer.  I too refused to cede my life to the standard protocol of the day. But it was not my health care providers who led me to Dr. Nagourney, it was a close friend.  Empowered with the knowledge that it was possible to improve my odds for survival, I chose functional profile testing (EVA-PCD®) to help determine my personalized treatment plan. It was a wise, informed decision resulting in the best possible outcome.  I have since become an online patient advocate, spreading the word to thousands of other patients so that they can become knowledgeable about this important test that could save their lives.

According to Dr. Nagourney, “Every system performs exactly as it was designed to perform. The current system of medical oncology provides adequate care for the average patient. There is little room for true, individualized care, for it disrupts the norm.”  But every patient with cancer has the same objective. To find the treatment that will work for “me.”  With a system skewed toward averages and away from the individual, the path to personalized medicine must be to empower the person with the most at stake – the patient. Dr. Nagourney says, “Today’s patient must become his or her own best advocate.”

More and more, patients are turning to online forums and other patient groups, not just for support, but to seek and share the latest news and information about treatments, side effects, tests, etc. If two heads are better than one, then thousands of engaged patients should, at the very least, provide good food for thought, “ideas worth spreading.”

Dr. Nagourney believes that “it’s in the online trenches where the real, personal war of cancer is being waged.  The old paradigm, that knowledge runs downhill from academics to practitioners to patients is being turned upside down as empowerment goes from the bottom up, not just from the top down.”  I’m sure e-Patient Dave would agree, along with countless other e-patients like him.

If It is Too Good to Be True . . .

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

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

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

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

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

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

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

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

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

The Molecular Origins of Lung Cancer

I had the luxury of attending the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; Biology, Therapy and Personalized Medicine held in San Diego earlier this month. I say luxury, for as my schedule closes in on me and I sometimes find myself working 13-hour days, it can be difficult to take even a couple of days away to attend meetings. But this conference was too good to pass up (hats off to Marge Foti and all the AACR staff for all their great work).

This symposium organized by David Carbone and Roy Herbst, brought together a broad spectrum of sophisticated scientists and international investigators, as well as community members and fundraising organizations who had the opportunity to present a special session on patient advocacy.

The meeting began with a keynote address examining microRNAs and lung cancer presented by Frank Slack from Yale University. He examined the growing recognition that lung cancer arises not only from gene mutations but also from small fragments of RNA that can up- or down-regulate normal genes in abnormal ways. This was the topic of discussion for many subsequent presentations.

As an aside, many of the readers will know that I am generally underwhelmed by genomic analyses for the prediction of cancer response. The fact that normal genes can function abnormally under the control of these small RNA sequences is just one more example of the genotype–phenotype dichotomy that cannot be adequately examined on static contemporary genomic platforms.

Many presentations examined the molecular biology of lung cancer with important distinctions being drawn between adenocarcinoma and squamous cell carcinomas. While adenocarcinomas reveal a growing number of targets – EGFR, ALK, ROS, RAS, and others – all the subject of small molecule inhibitors; squamous cell carcinomas provide fewer opportunities for the use of these classes of drugs.

One of the interesting discussions was the frequent mutation of LKB1 in lung cancers. Work going back several years by John Minna, a pioneer in this field, identified changes in this metabolic regulator as a common finding in lung malignancies.

Additional presentations examined chemoprevention, molecular pathology, new mechanisms to categorize lung cancer subtypes, and a very interesting discussion of field cancerization. In a particularly interesting analysis, Ignacio Wistuba from M.D. Anderson, showed that molecular changes in the surface epithelium of the lung bronchioles recapitulated the molecular biology of the final tumor in a step-wise manner, inversely related to the distance to the tumor. That is, starting at the main bronchi, one or two mutational changes were detected. Moving closer to the site of the tumor, additional mutations were accumulated. Finally arriving at the site of the established malignancy, all of the constituent mutations associated with this particular cancer became manifest; a saltatory slide into cancer presumably associated with exposure to carcinogens.

Among the other exciting presentations were updates on redox-based approaches to cancer presented by Kenneth Tew and Garth Powis.

Jeff Engelman presented an update on a new class of agents that target the RAS pathway. This is ongoing work that he and his group have reported on over the last several years. We have been engaged in related work using an MEK/ERK inhibitor similar to the compound that Dr. Englemen reported on at this meeting. It is exciting indeed to see early clinical results with this class of compounds, for we have identified many patients who might benefit from this pathways’ inhibition. We wait with great anticipation for FDA approval of these compounds so that our patients currently being identified as candidates in the laboratory may soon receive these treatments.

Faster than the Speed of Light

Last week, scientists at CERN, the European particle physics laboratory located outside Geneva, Switzerland, conducted an experiment, the results of which now challenge one of the most fundamental principles of modern physics. I speak of Albert Einstein’s 1905 declaration that the speed of light is an absolute and that nothing in the universe could travel faster.

E = MC2, the principle under which nuclear energy and weapons have been developed, as well as all of the corollaries of the theory of relativity were called into question when a series of sub atomic particles, known as neutrinos traveled from Switzerland to Italy at a speed that was 1/60 of a billionth of a second faster than the speed of light. What has followed has been a flurry of interest by departments of physics all over the world. Confronted with this new finding, these investigators will diligently seek to reproduce or refute the findings.

This was not the first time that someone challenged the primacy of Einstein’s 1905 theory. Indeed, during the 1930s, for largely political and anti-Semitic reasons, the Nazi party attempted to disprove Einstein. Yet, all of the political meanderings, personal vendettas and intellectual jealousy could not unseat Einstein’s guiding principle. That is, until objective evidence in the form of the CERN experiments came to the fore.

Science — however lofty — and scientists — however highly regarded — dwell in the same realm as all the rest of us mere mortals. Their biases and preconceived notions often cloud their vision. Comfortable with a given paradigm, they hold unyieldingly to its principles until they are forced, however unwillingly, to relinquish their belief systems in favor of a new understanding. I write of this in the context of laboratory-based therapeutics – a field of scientific investigation that has provided firm evidence of predictive validity. These technologies have improved response, time to progression and survival for patients with leukemia, ovarian, breast and lung cancers, as well as melanoma and other advanced malignancies. Thousands of peer-reviewed published experiences have established the merit of human tumor primary cultures for the prediction of response. Investigations into the newest classes of targeted therapies are providing new insights into their use and combinatorial potential.

Yet,  while the physicists of the world will now rise to the challenge of data, the medical oncologists and their academic counterparts refuse to accept the unimpeachable evidence that supports  the validity of assay-directed therapy. Perhaps if our patients were treated at CERN in Geneva,  their good outcomes would receive the attention they so richly deserve.

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.

Recurrent Small Cell Cancer of the Lung: A Therapeutic Challenge

I recall as a junior medical oncology Fellow, one of my senior Fellows describing small cell cancer of the lung as “leukemia of the lung.” The reason he used this description was because leukemia is among the most rapidly progressive and aggressive forms of cancer.

Arising in the bone marrow, an afflicted patient’s white blood cell count can double every day, a remarkable achievement when one considers the hundreds of billions of cells involved. What this doctor meant was that the lung cancer of small cell type (also known as oat cell), grew so rapidly that in untreated patients, survival can be measured in weeks to months. With the discovery of effective chemotherapy this disease became a comparatively easy mark for the treating oncologist. Ironically, where it was the worst form of lung cancer during the 70s, by the 1990s it was the best form to have. Most patients responded to treatment and some lived years. The problem is, treating patients who recur.

For unknown reasons this otherwise chemosensitive disease has a tendency to recur with a vengeance. Attempts to control recurrent disease with second line therapies have characteristically been unsuccessful. Drug combinations that are generally quite active in the first line setting, are almost universally inactive in second line use.

As a result, recurrent small cell lung cancer is tantamount to a death sentence.

Two months ago, a slender woman arrived at Rational Therapeutics carrying a biopsy kit and a bottle filled with straw-colored fluid. She explained that her husband had recurrent small cell lung cancer and his surgeon had inserted a chest tube. He then provided us with both biopsy material and fluid. She went on to say that she herself was a laboratory scientist and was familiar with laboratory techniques.

We processed the specimen, which provided amble cells for analysis. Not surprisingly, the tumor was resistant to many (most) of the drugs tested. However, the class of drugs known as alkylating agents revealed persistent activity. More importantly, the combination of an alkylating agent and topotican revealed activity and synergy.

Having published a paper on this topic several years ago, (Nagourney et al, British Journal of Cancer 2003) I was quite familiar with this combination. Referencing work by investigators at Yale University, using the combination of cytoxan and topotican, I provided my recommendation to a colleague who administered this combination with a very tolerable weekly dose schedule.

The patient responded immediately. So much so, that between cycle one and cycle two he took a vacation to San Diego with his wife.  Further response was documented following cycle two.  Most gratifying has been the very limited amount of toxicity in the treatment itself.