The Emperor of All Maladies’ New Clothes

Ken Burn’s series “The Emperor of All Maladies” from Siddhartha Mukherjee’s book of the same title ppbs logorovides an interesting and informative historical perspective on mankind’s efforts to confront cancer as a disease.

Beginning with ancient references to human malignancy, the series goes on to explore radical surgery and the earliest use of radiation but really gains traction in the mid-20th century with the discovery of the first chemotherapy drugs. While the nitrogen mustard derivatives were being studied under a veil of military secrecy, Dr. Sidney Farber in Boston explored the B-vitamin analogue, aminopterin, for the treatment of childhood leukemia. (You can read more about this in my book Outliving Cancer.)

Through the ensuing decades, seemingly stunning victories ultimately fell in crushing defeats, while the promise of single agents, then multi-drug combinations, followed by dose-intensive therapies, and finally bone marrow transplantation yielded few cures but delivered ever increasing toxicities. Clifton Leaf, a cancer survivor himself who created a stir with his controversial 2003 Fortune Magazine article entitled “Why We Are Losing the War on Cancer and How to Win It” described his own disappointment with the slow pace of progress.

Screen shot Emperor of All MaladiesThe last episode examined our growing understanding of human genomics and segued by interviews with Richard Klausner, former director of the National Cancer Institute; and Harold Varmus, the current NCI director; to Michael Bishop, Eric Lander and Francis Collins who luxuriated in the clinical potential of human genomics and the coming era of big science.

The final part was an interview with Steven Rosenberg, one of the earliest pioneers in immunotherapy and Carl June whose groundbreaking work with chimeric antigen receptor T-cells is among the most recent applications of this important field.

The take-home message would seem to be that despite the fits and starts we are now at the dawn of a new age of big science, big data and genomic breakthroughs. What was missing however was an examination of where we had gone wrong. It would seem that the third rail for this community is an honest assessment of how a small coterie of investigators who championed only certain ways of thinking over all others commandeered all the money, grants, publications, chairmanships and public attention, while patients were left to confront a disease from which survival has changed very little, at ever increasing costs and toxicities.

Another thing that came through was the very human side of cancer as a disease and the kindness and emotional support that family members and parents provided to those afflicted. I couldn’t help but feel that these individuals had been cheated: cheated of the lives of their family members, cheated of the resources that could have pursued other options and cheated of the well-being that these poisonous and dose-intensive regimens rained upon them in their last days.

As science has become the new religion and scientists the new gurus, one message that resonated was that many of these gurus were false prophets. They are too self-absorbed to question their own dogmatic belief systems in dose-intensity or multi-agent combinations, all of which fell painfully by the way side as the next therapeutic fad emerged. Will our current love affair with the gene prove to be little more than the most current example of self-congratulatory science conducted in the echo chamber of modern academia?

Victories against cancer will be won incrementally. Each patient must be addressed as an individual, unique in their biology and unique in their response probability. No gene profile, heat map, DNA sequence or transcriptomic profile has answered the questions that every patient asks; “What treatment is best for me?” Dr. Mukherjee himself used the analogy of the blind men and the elephant. Unfortunately, there was little discussion of how much that parable may apply to our current scientific paradigms.

It is time for patients to demand better and refuse to participate in cookie-cutter protocols.
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Physicians should become more familiar with the fundamentals of physiology and biochemistry to better understand the principles of cancer prevention at the level of diet and lifestyle.

Finally, while we wait with bated breath, for the arrival of glorious gene profiles widely touted as the future answer to all of cancer’s most vexing questions, patients should throw off the yoke of one-size-fits-all approaches and demand laboratory platforms, such as the EVA-PCD assay, that are available today to make better use of existing treatments.

In Cancer Research: An Awakening?

In 2005, as the Iraq War reached a low point with casualties mounting and public support dwindling, Sunni tribesman in the Anbar Province arose to confront the enemy. Joining together as an ad hoc army these fighters turned the tide of the war and achieved victories in the face of what had appeared at the time, to be overwhelming odds.

I am reminded of this by an article in The Wall Street Journal by Peter Huber and Paul Howard of the Manhattan Institute that examined the bureaucracy of drug development. It raised the question: Are new cancer treatments failures or is the process by which they are approved a failure? They describe “exceptional responders” defined as patients who show unexpected benefits from drug treatments. Using molecular profiles, they opine, scientists will unravel the mysteries of these individuals and usher in an era of personalized medicine. Thus, rigid protocols that use drugs based upon tumor type e.g. lung vs. colon fail because they do not incorporate the features that make each patient unique – an awakening.

The example cited is from Memorial Sloan-Kettering where a patient with bladder cancer had an unexpected response to the drug Everolimus (approved for kidney cancer). Subsequent deep sequencing identified a genetic signature associated with sensitivity to this drug. While it is a nice story, I already knew it very well because it had been repeated many times before and would in the past have been dismissed as an “anecdote.” It is precisely because of its rarity that it has been repeated so many times.

The WSJ analysis strikes a familiar chord. For decades, we have decried the failure of rigid clinical trials that underestimate a patient’s unique biology yet cost millions, even billions of dollars, while denying worthy candidates new treatments under stultifying disease-specific designs.

Well Tray Closeup2 smallWe pioneered phenotypic (functional) analyses (the EVA-PCD platform) to examine whole cell models as we explored drug response profiles, novel combinations and new targets. It is regrettable that these WSJ authors, having raised such important issues, then stumble into the same tantalizing trap of molecular diagnostics, and call for bigger, better, faster genomic analyses.

Cancer patients need to receive treatments that work. They do not particularly care why or how they work, just that they work. These authors seem to perpetuate the myth that we must first understand why a patient responds before we can treat them. Nothing could be further from the truth.

Alexander Fleming knew little about bacterial cell wall physiology when he discovered penicillin in 1928, and William Withering knew nothing about the role of muscle enzymes in congestive heart failure when he discovered digoxin extracts in 1785. Would anyone argue that we should have waited decades, even centuries to apply manifestly effective therapies to patients because we did not have the “genes sequenced?’

We may be witness to an awakening in cancer drug development. It may be that a new understanding of individualized patient response will someday provide better outcomes, but platforms with the proven capacity to connect patients to available treatments should be promoted and applied today.

A New Use for One of the Oldest “New” Drugs

With the profusion of new targeted agents entering the clinical arena, a report from the American Society of Hematology bears consideration.

The trial known as the SORAML trial enrolled 276 patients with newly diagnosed acute myelogenous leukemia. The patients were between the ages of 18 and 60. All patients received a standard chemotherapy regimen. The patients were then randomized to receive Sorafenib or placebo. Patients on the Sorafenib arm then remained on a maintenance therapy for twelve months.

While the achievement of complete remission was almost identical between the two arms at 59% and 60%, the event free survival demonstrably favored the Sorafenib group at 20.5 months versus 9.2 months. At three years of follow-up 40% of the Sorafenib group were well with only 22% of the placebo group still in remission. This corresponds to a three-year relapse free survival of 38% for placebo and 56% for Sorafenib (P=0.017).

The results are of interest on several levels.
1.    Sorafenib a multitargeted tyrosine kinase inhibitor was approved in December 2005 for the treatment of renal cell carcinoma. This makes Sorafenib one of the first targeted agents to achieve FDA approval.

2.     Sorafenib has many modes of action and it is not entirely clear which of its functions were responsible for the superior survival in this AML study.

3.    Sorafenib’s approval reflects a rather convoluted and interesting history. When first developed the drug was designed to target the oncogene B-Raf. As a result the drug was introduced into early clinical trials for the treatment of advanced melanoma, a disease known to be associated with B-Raf mutation. As the drug proved ineffective, it appeared unlikely to gain FDA approval. That is, until it showed cross reactivity with VEGF pathway associated with tumor cell vascularity. A successful trial published in the New England Journal of Medicine then led to the approval.

Now, nine years later this old new drug has gained new life. This time in acute myelogenous leukemia.

The term “dirty drug” refers to agents that target many kinases at the same time. Sorafenib is an example of a “dirty drug.” However it is Sorafenib’s “dirty drug” quality that led first to its approval and most likely now leads to its application in AML. This reflects the fact that Sorafenib may be inhibiting B-Raf signaling associated with the common mutation in Ras upstream of B-Raf or it may reflect Flt3 a secondary activity associated with Sorafenib.

Indeed B-Raf and Flt3 may not be upregulated in every patient, but could serve a function of permissive activity granting an additional survival signal to the AML cells as they go through induction therapy. These subtleties of drug effect may escape genomic analysis as the true “target” may not be mutated, upregulated or amplified. No doubt the investigators in this study will conduct gene sequencing to determine whether there is a driver mutation associated with the advantage reported in this clinical study. What will be intriguing is to determine whether that advantage is an abnormal gene functioning within these cancerous cells or possibly a normal gene functioning abnormally in these cancer cells. More to come.

Toward A 100% Response Rate in Human Cancer

Oncologists confront numerous hurdles as they attempt to apply the new cancer prognostic and predictive tests. Among them are the complexities of gene arrays that introduce practicing physicians to an entirely new lexicon of terms like “splice variant, gene-rearrangement, amplification and SNP.”

Althougcancer for dummiesh these phrases may roll of the tongue of the average molecular biologists (mostly PhDs), they are foreign and opaque to the average oncologist (mostly MDs). To address this communication shortfall laboratory service providers provide written addenda (some quite verbose) to clarify and illuminate the material. Some institutions have taken to convening “molecular tumor boards” where physicians most adept at genomics serve as “translators.” Increasingly, organizations like ASCO offer symposia on modern gene science to the rank and file, a sort of Cancer Genomics for Dummies. If we continue down this path, oncologists may soon know more but understand less than any other medical sub-specialists.

However well intended these educational efforts may be, none of them are prepared to address the more fundamental question: How well do genomic profiles actually predict response? This broader issue lays bare our tendency to confuse data with results and big data with big results. To wit, we must remember that our DNA, originally provided to each of us in the form of a single cell (the fertilized ovum) carries all of the genetic information that makes us, us. From the hair follicles on our heads to the acid secreting cells in our stomach, every cell in our body carries exactly the same genetic data neatly scripted onto our nuclear hard-drives.
What makes this all work, however, isn’t the DNA on the hard drive, but instead the software that judiciously extracts exactly what it needs, exactly when it needs it. It’s this next level of complexity that makes us who we are. While it is true that you can’t grow hair or secrete stomach acid without the requisite DNA, simply having that DNA does not mean you will grow hair or make acid. Our growing reliance upon informatics has created a “forest for the trees” scenario, focusing our gaze upon nearby details at the expense of larger trends and insights.

What is desperately needed is a better approximation of the next level of complexity. In biology that moves us from the genotype (informatics) to the phenotype (function). To achieve this, our group now regularly combines genomic, transcriptomic or proteomic information with functional analyses. This enables us to interrogate whether the presence or absence of a gene, transcript or protein will actually confer that behavior or response at the system level.

I firmly believe that the future of cancer therapeutics will combine genomic, transcriptomic and/or proteomic analyses with functional (phenotypic) analyses.

Recent experiences come to mind. A charming patient in her 50s underwent a genomic analysis that identified a PI3K mutation. She sought an opinion. We conducted an EVA-PCD assay on biopsied tissue that confirmed sensitivity to the drugs that target PI3K. Armed with this information, we administered Everolimus at a fraction of the normal dose. The response was prompt and dramatic with resolution of liver function abnormalities, normalization of her performance status and a quick return to normal activities. A related case occurred in a young man with metastatic colorectal cancer. He had received conventional chemotherapies but at approximately two years out, his disease again began to progress.

A biopsy revealed that despite prior exposure to Cetuximab (the antibody against EGFR) there was persistent activity for the small molecule inhibitor, Erlotinib. Consistent with prior work that we had reported years earlier, we combined Cetuximab with Erlotinib, and the patient responded immediately.

Each of these patients reflects the intelligent application of available technologies. Rather than treat individuals based on the presence of a target, we can now treat based on the presence of a response. The identification of targets and confirmation of response has the potential to achieve ever higher levels of clinical benefit. It may ultimately be possible to find effective treatments for every patient if we employ multi-dimensional analyses that incorporate the results of both genomic and phenotypic platforms.

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.

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.

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.

The Angelina Jolie Effect

stock-photo-16854195-premiere-of-sony-pictures-salt-arrivalsAngelina Jolie’s willingness to bravely publish her saga, as she confronts the risk of a nefarious form of cancer, has focused international attention upon the phenomenon of genetic predisposition to cancer.

The term BRCA, coined by investigators from Berkeley and Europe, described an inherited predisposition to cancer. Years of research came to fruition in the early 90s when geneticist Mary-Claire King and her collaborators recognized that patients who lacked DNA repair capacity tended to accumulate chromosomal damage that ultimately lead to cancer.

The BRCA genes (1 and 2) are part of the genomic fidelity system. Just like it sounds, these DNA repair enzymes maintain the “fidelity” or trueness of your makeup. Everyday our bodies are exposed to mutations. Radon in the atmosphere, carcinogens, even our dietary intake regularly injures our chromosomes. In response, we marshal defenses that recognize, remove and repair the damaged elements before they can be transmitted to the next generation of cells. When these BRCA genes are absent or silenced, the normal wear and tear goes unrepaired. Over a lifetime, this leads to a triggering mutation and cancer.

BRCA genes are like the Zamboni machines that clean up the ice in-between periods in a hockey game. Imagine what a Stanley cup game would be like if the ice was so dug up that the players took a tumble every time they skated toward the goal.

Ms. Jolie’s chromosomes are like the ice, but her Zamboni machine isn’t working.

So why would someone like Angelina Jolie get cancer? The reason why patients with the BRCA1 or 2 mutation get breast and ovarian cancer over other types of cancer remains somewhat of a mystery. But the reason that they get cancer at all is quiet clear. They accumulate damage they can’t repair.

That being the case, what happens when we introduce DNA damage intentionally? The answer is: patients with BRCA1 and BRCA2 respond to chemotherapy often quite dramatically. It is the very fact that cells cannot repair damage, which makes them hypersensitive to DNA damaging drugs like alkylators (cytoxan), platins (cisplatin and carboplatin) and ionizing radiation (x-rays). Indeed, tumors that carry DNA repair deficiencies are among the easiest to treat with conventional cytotoxics. Thus, the very reason that these patients develop cancers is the Achilles heel that makes their tumors drug sensitive.
Interestingly, BRCA1 and BRCA2 positive patients don’t only get breast and ovarian cancer; they can also develop melanoma, lymphoma and other tumors.

The importance of the BRCA discovery has been important on many levels. First and foremost it has enabled us to develop screening techniques to identify the at-risk populations that allows them to undertake preventative measures. Second, it has granted an insight into carcinogenesis and the concept of genomic fidelity. Third, it has provided new therapeutic options for these patients and all patients with cancers that have “BRCA-ness.”

Finally, it has opened up a field of investigation that connects cancer with other long-recognized disease states like the pediatric condition Fanconi’s anemia. It only reminds us again that cancer is but one part of a continuum of human diseases.

Yet Another Study Agrees: Functional Profiling Provides Insight

It was during the last weeks of December that a particularly interesting article crossed my desk. The study done by a group from Toronto, Canada, is entitled Variable Clonal Repopulation Dynamics Influence Chemotherapy Response in Colorectal Cancer. The study examined the proliferative capacity and drug sensitivity in colorectal cancer cells that were tracked using a process known as lentiviral lineage tracking. The investigators showed that despite serial passages, the cell populations remained stable from a genomic standpoint.

What was most interesting was the finding that these genomically related subpopulations became progressively more resistant to oxaliplatin after drug exposure, suggesting what they described as “inherent functional variability.”

As one of several investigators engaged in the field of functional profiling (EVA-PCD), I found the article both interesting and extremely consistent with our laboratory observations. First, cancer cells display biological differences that may reflect environmental (microenvironmental) influences, epigenetics and other drivers not readily identified at the DNA level.

Second, these investigators, using extremely sophisticated molecular techniques, found, as the lead investigator said, “We should not be putting our eggs exclusively in the genetics basket.” This quote from the lead investigator, John Dick, was particularly resonant.

As many of you who read my blogs know, a recurring theme in these pages is the need to broaden our scope and examine the protein, metabolic and functional characteristics of the cancer cells in their native state. Once again we find that as our most accomplished molecular brethren drill down to the bedrock of cancer biology, they are confronted by complexities and crosstalk that can only be effectively studied at the level of cell biology.

I wish all of readers of this blog a happy New Year, and look forward to a healthy and productive 2013.

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.