Cancer Patients, Genetic Testing and Clinical Outcomes

Two years ago in this blog, I described a young man with an aggressive non-small cell lung cancer. Following his diagnosis he was screened for EGFR mutation (the target of Erlotinib [Tarceva]) and ALK gene rearrangement (the target of Crizotinib [Xalkori]). Found negative for both, his options were limited to chemotherapy.

When I met the patient, a PleurX catheter had already been inserted to remove fluid that was rapidly re-accumulating in his right chest. This provided access to cancer-laden fluid and offered an excellent opportunity for EVA-PCD® laboratory analysis.

The results showed the expected resistance to Erlotinib (for which no mutation was found) but very high activity for Crizotinib. When he returned for follow-up we repeated a second analysis. The results were identical. One possibility was that the patient carried a second mutation sensitive to this class of drugs, like ROS-1 or MET, both targets of Crizotinib. However, at the time, MET and ROS-1 gene testing was not readily available. I referred the patient to a colleague who was conducting Crizotinib trials. Fluid was re-aspirated and submitted to a different reference lab for genomic analysis. The finding: The original laboratory test had been erroneous. The patient was indeed, ALK gene rearranged.

After a course of chemotherapy, he qualified for and responded beautifully to single-agent Crizotinib. In my blog, I examined how our functional profile more closely approximated the patient’s biology (phenotype) over the genomic profile (genotype). However appealing these genomic tests may be, they can only identify potential targets for therapy that may or may not be relevant to a patient’s ultimate clinical response.

A year later, a female patient with a mucinous adenocarcinoma presented with brain metastases. An EVA-PCD analysis revealed relative chemotherapy resistance and no activity for Erlotinib (Tarceva). She was found EGFR non-mutated. Unfortunately, there was insufficient tissue for the EVA-PCD to test Crizotinib.

During subsequent Cyber-Knife treatment for her brain metastases, a specimen of tumor showed the ALK gene rearrangement and the patient started Crizotinib. She responded promptly.

At the one-year point, signs of progression appeared in the opposite lung, but while she continued to experience good response in the original sites, a repeat biopsy was performed. This time the EVA-PCD functional profile revealed no activity for Crizotinib, but identified activity for the combination of Platinum and Vinorelbine. We combined these two drugs with the Crizotinib and she remained in remission for an additional year. Low blood counts forced us to withhold chemotherapy and her disease progressed. She was referred to a clinical trial with a second-generation ALK inhibitor. By the second month, her disease had progressed rapidly.

Cancerous cells from a bronchoscopic biopsy were submitted for analysis. The finding: No ALK gene mutation. Instead her tumor carried a MET mutation. The patient now rapidly progressing will require immediate therapy, but what?  Fortunately, a small sample of fluid aspirated from the lung provided adequate cells for analysis. The results are striking since they confirm persistent activity for Crizotinib. The patient has now been re-challenged with Crizotinib and we await clinical follow-up.

Taken together, these cases offer interesting insights. The first reflects the medical community’s preternatural faith in genomics. We, as a society, have so completely accepted the accuracy and predictive validity of genetic tests, that no one seems willing to scrutinize the data for its ultimate accuracy. This may not be serving our patients well, as both these cases exemplify. An error that missed the ALK gene re-arrangement in the first patient almost cost this young man his life, despite our protestations. Then, an error in this woman’s analysis serendipitously led to her response to the right drug for the wrong reason, her gene results notwithstanding

We forget at our peril, that all tests are fallible. Clinicians must recognize that highly sophisticated analyses using the most advanced technologies still function within the infinitely complex confines of human biology. The crosstalk, redundancy and promiscuity of human cellular circuitry remain demonstrably more complex than our best artificial neural networks. Genomic analyses and companion diagnostics now dictate who can and who cannot receive drugs, but as can be seen here, these wonders of modern science are not perfect predictors. They have the potential to deprive patients of life-saving treatment while subjecting others to drugs with little chance of benefit. Physicians must remember to be artful as we apply the science of our trade.

ASCO Update: Personalized Cancer Care – Our Contributions

ASCO logo

As part of our ongoing blog postings we like to include recent presentations and publications. On July 9, I described our ASCO presentation exploring crizotinib, “Functional Profiling Leads to Identification of Accurate Genomic Findings.

To conclude the review of our other presentations from that meeting, here is a brief summary of our work.

The first of the two was our international collaboration in personalized medicine for the treatment of advanced and drug-refractory cancers: “Clinical application of human tumor primary culture analyses.” The study reviewed the results of 67 patients from institutions across Brazil.

Tumor samples were transported by overnight courier to California for drug response profiling. A broad array of tumors were included. The overall success rate provided actionable results in 62 of 67 patients (92 percent). More than 75 percent of the studies provided results for between 8 and 16 drugs and combinations with a median of 12 reported. Several strikingly good responses were observed, including novel combinations identified in the laboratory. This study confirms the feasibility of international collaboration and reflects the globalization of medical care delivery.

The final study published by ASCO was also a collaborative effort with SageMedic of Larkspur, CA, The Ludwig Maximilians University Munich, Germany and the Weisenthal Cancer Group. The study was a meta-analyses that examined the sensitivity and specificity of human tumor primary culture studies and the efficacy of drug therapies selected, based on laboratory findings. In aggregate there were 28 retrospective and 15 prospective trials included.

The overall sensitivity was 0.92 (95 percent C.I. 0.89 – 0.95), and specificity of 0.72 (95 percent C.I. 0.67 – 0.77) with an area under the curve for the ROC of 0.893 (SE = 0.023, p < 0.001). When clinical outcomes were examined, it revealed a two-fold improvement for assay-guided therapy for standard of care (odds ratio 2.04, 95 percent C.I. 1.62 – 2.57, p <  0.001). Finally, the one-year survival rate for assay-guided therapy proved superior (OR 1.44, 95% C.I. 1.06 – 1.95, p= 0.02).

As can be seen from this well conducted meta-analysis, there is a wealth of evidence to support the use of human tumor primary cultures for the selection of chemotherapy.

Functional Profiling Leads to Identification of Accurate Genomic Findings

The 2013 American Society of Clinical Oncology annual meeting, held May 31 – June 1, in Chicago, afforded the opportunity to report three studies.

Crizotinib (Xalkori) Mechanism of Action

Crizotinib (Xalkori)
Mechanism of Action

The first, “An examination of crizotinib activity in human tumor primary culture micro-spheroids isolated from patients with advanced non-small cell lung cancer,” reports our experience using the EVA-PCD platform to examine the drug crizotinib. This small molecule originally developed as an inhibitor of the oncogenic pathway MET, was later found to be highly active in a subset of cancer patients who carried a novel gene rearrangement for anaplastic lymphoma kinase (ALK). It was this observation that lead to the drug (sold under the name Xalkori) being approved for the treatment of advanced ALK positive lung cancer. The subsequent observation that this same drug inhibited yet another gene target known as ROS-1 found in a subset of lung cancer patients, has led to its use in this patient population.

Our exploration of crizotinib activity identified a series of patients who received the drug and responded dramatically. This included both ALK positive and ROS-1 positive patients. One patient however, appeared highly sensitive to the drug in our studies, but was found negative for the ALK gene rearrangement by genomic analysis. We repeated our functional analysis only to the find again, the same high degree of crizotinib sensitivity. I felt confident the patient should receive crizotinib, but at the time the drug was not yet commercially available and he didn’t qualify for the protocols, as he was ALK negative.

I scoured the country looking for a way to get the patient treated with crizotinib. From Sloan Kettering to UCLA, no one could help. And then, in collaboration with my abstract co-author Ignatius Ou from UC Irvine, we decided to repeat the ALK analysis. That proved to be a very good idea. For the patient was indeed positive for ALK gene rearrangement by second analysis and subsequently responded beautifully to a treatment for which he would not otherwise qualify. Once again, phenotype trumped genotype. (The complete story of this patient can be found in Chapter 19 of Outliving Cancer.)

A final patient in the series represented a particularly interesting application of functional analysis. The patient, a young woman with an extremely rare pediatric sarcoma, had failed to respond to multiple courses of intensive chemotherapy and her family was desperate. As she approached the end of her third year in high school, it looked unlikely that she would reach her senior year. A portion of her tumor was submitted for analysis. The results confirmed relative resistance to chemotherapeutics, many of which she had already received and failed, but showed exquisite sensitivity to crizotinib. Indeed, our inclusion of crizotinib in the analysis reflected our intense effort to identify any activity for this previously refractory patient.

We reported our findings to the pediatric oncologist and encouraged them to consider an ALK rearrangement analysis, despite this particular pathway not being on anyone’s radar prior to our study. The result – a positive gene rearrangement. This led to a successful petition to the drug company for the use of this agent for an off-label indication. The response was prompt and dramatic, and remains durable to this day, nearly a year later. Again, the phenotypic analysis guided us to the correct genomic finding.

Our other presentations at this year’s meetings will be reported in future blogs.

Gee (G719X) Whiz: Novel Mutations and Response to Targeted Therapies

In a recent online forum a patient described her experience using Tarceva as a therapy for an EGFR mutation negative lung cancer. For those of you familiar with the literature you will know that Lynch and Paez both described the sensitizing mutations that allow patients with certain adenocarcinoma to respond beautifully to the small molecule inhibitors.  The majority of these mutations are found in Exon 19 and Exon 21, within the EGFR domain. Response rates for the EGFR-TKI (gefitinib and erlotinib) clearly favor mutation positive patients. Depending upon the study, mutation positive patients have response rates from 53 – 100 percent, generally around 70 percent, while mutation negative response patients have a response rate of 0 – 25 percent, generally about 10 percent.

So why don’t all the mutation positive patients respond and conversely why do some mutation negative patients respond?

The story outlined in this online forum gives some insight. The individual in question carried a rare, and only recently recognized, Exon 18 mutation known as a G719X. This uncommon form of mutation had previously been unknown and few laboratories knew to test for it. Nonetheless, G719X positive patients respond to erlotinib and related agents. Indeed, there may be reason to believe that the more potent irreversible EGFR/HER2 dual inhibitor HKI-272, may be even more selective for this point mutation.

The excellent and durable response described by this individual, would not have been possible had the patient’s first physician followed the rules. That is, had her physician refused to give erlotinib to an (putatively) EGFR mutation negative patient she might well not be here to tell her story. More to the point, her good response (a clinical observation) led to the next level of investigation, namely the identification of this specific EGFR variant

The lessons from this experience are numerous. The first is that cancer biology is complex and, to paraphrase E.O. Wilson, was not put on earth for us to necessarily figure it out. The second, is that molecular biologists can only seek and identify that which they know about apriori.  To wit, if you don’t know about it (G719X) and you don’t have a test for it, and you don’t know to look for it, then it’s a virtual certainty that you aren’t going to find it.

The premise of our work at Rational Therapeutics is that the observation of a biological signal identifies a candidate for therapy whether we understand or recognize the target. Crizotinib was originally developed as a clinical therapy for patients who carried the CMET mutation. Serendipity led to the recognition that the responding subpopulation was actually carrying a heretofore-unrecognized ALK gene rearrangement. Sorafenib was originally evaluated for the treatment of BRAF mutation positive diseases. Yet it was the drug’s cross-reactivity with the VGEF tyrosine kinases that lead to its broad clinical applications. Each of these phenomena represents accidental successes. Were it not for the clinical observation of response in patients, the investigators conducting these trials would have been unlikely to make the discoveries that today provide such good clinical responses in others.

To put it quite simply, these patients and their disease entities educated the molecular biologists.

When we first identified lung cancer as a target for gefitinib, and began to administer the closely related erlotinib to lung cancer patients, neither Lynch nor Paez had identified the sensitizing EGFR mutations. That had absolutely no impact upon the excellent responses that we observed. It didn’t matter why it worked, but that it worked.  While the EGFR story has now been well-described, might we not use functional analytical platforms (functional profiling) to gain insights into the next, and the next generation of drugs and therapies that target pathways like MEK, ERK, SHH, FGFR, PI3K, etc., etc., etc. . . .

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.

Novel Cancer Treatments — Crizotinib

Recent reports have described the striking activity of a novel Pfizer compound known as Crizotinib. The compound is an inhibitor of an enzyme known as the anaplastic lymphoma kinase (ALK). In approximately 5 percent of non-small cell lung cancer patients, a specific mutation known as the EML4-ALK rearrangement results in activation of this gene and the development of cancer. In those patients who are found positive for this mutation, the response rate to the drug Crizotinib is 57 percent with a disease control rate of 87 percent at eight weeks.

Hailed as an unprecedented response rate by Anil Potti, MD, associate professor of medicine at Duke University, these results reflect the power of pre-selection of candidates for treatment. The drug is reasonably well tolerated and represents a true advance. Taken in context, however, these results are not superior to those that we recently reported using conventional chemotherapies pre-selected by functional analysis. Indeed, our results with a response rate of 62 percent, a time to progression of 9.5 months and a median overall survival of 20.3 months are actually better. More notably, our results were obtained with conventional chemotherapeutics, not novel compounds.

What is most striking about the Crizotinib results is the capacity of pre-selection to demonstrably improve response rates. Yet, these results only apply to a distinct minority of patients. The results that we reported at ASCO reflect the activity of chemotherapy applicable to the remaining 95 percent of NSCLC patients. It is also highly likely that functional analysis will select Crizotinib candidates as well, or better, than the mutational analysis utilized for patient selection in the study reported. For comparison, our response rates for erlotinib (Tarceva) as a single agent are superior to the response rates for patients selected based on EGFR mutational analysis. In addition, secondary mutations have already been identified that confer resistance to Crizotinib, which likely confound durable remissions for this and related drugs.

While I applaud the results of this interesting trial, my team and I feel it important that all lung cancer patients have the benefit of pre-selection. Whether they fit into the 5 percent described in this report, or the 95 percent covered in our clinical trial.

Targeted Therapies — The Next Chapter

Within this blog, we have intermittently reviewed the concept of targeted therapies. To reiterate, these are classes of drugs that target specific pathways considered tumorigenic. Among the pathways initially targeted were the epidermal growth factor receptor and the closely related HER2. Shortly after the introduction of EGFr and HER2 directed therapies came the development of drugs that target another critical pathway, mTOR.

Hundreds of compounds are now under development intended to more accurately hone in on the pathways of interest in patients’ tumors. Regrettably, the medical community continues to apply old clinical trial methods to this newest era of drugs. While the selective application of drugs like: Tarceva for EGFR mutants, Herceptin for HER2 over-expressers, and Crizotinib for EML4-ALK mutants, are much more effective in patients with these gene expressions, these are a select few examples of linear thinking that bore fruit.

That is, this gene is associated with this disease state and can be treated with this drug.

Many, if not most cancers will prove to be demonstrably more complicated. Genomic trials can only succeed if we first know the gene of interest and second know that its (over) expression alone is pathogenetic for the disease entity. Even meeting these conditions is likely to result in comparatively brief partial responses due to the crosstalk, redundancy and complexity of human tumor signaling pathways — the “targets” of these new drugs.

To address these complexities, functional analytic platforms that examine outcomes, not targets, are needed. This bottom-up approach has now enabled my team to explore the activity of novel compounds. When investigators develop interesting “small molecules,” we examine the disease specificity, combinatorial potential and sequence dependence of these compounds in short-term cultures to provide meaningful insights that can then be addressed on genomic and proteomic platforms. This reduces the time required to take these new agents from bench to bedside. We cannot solve tomorrow’s questions using yesterday’s mindsets