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

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

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

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

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

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

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

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

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

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

The Information Disconnect

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

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

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

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

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

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

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

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

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

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

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

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

The 2013 Nobel Prize for Medicine and Physiology

2013 Nobel Prize artOn October 7, 2013, in Stockholm, Sweden, the Nobel Committee announced the winners of the Nobel Prize for Medicine and Physiology – two Americans and one German, all now located at institutions in the US. The discovery for which these three investigators share the prize involves their work over three decades studying the transport, packaging and trafficking of cellular proteins.

All cells must communicate and maintain their identity. To do so cells have developed intricate systems whereby neurotransmitters, proteins, hormones, and other species are encapsulated in small vesicles. These vesicles may be utilized to extrude materials into the extracellular domain or may store materials within the cell for later use. Working in model systems including yeast cells, these investigators showed the intricacy of cellular physiology associated with micro-vesicular function.

What makes these investigators’ work so interesting is that it is principally the study of cellular physiology, or what we call cell biology. While many breakthroughs and observations today reflect discoveries at the level of DNA, RNA and the genome, these investigators have pioneered protein kinetics and physiology. What is so exciting about this Nobel Prize is that it returns attention to the intricacies of cellular function at the level of phenotype. Protein biology represents the final common pathway from blueprint (DNA) to function. While genes that are detected within the nucleus (the purview of genomic analyses and many recent Nobel prizes) may or may not ultimately be expressed, depending upon splice variants, DNA methylation, histone acetylation, small interfering RNAs and non-coding DNAs among other phenomena, functional proteins are the active end-product and do very much exist.

We now recognize that cellular signaling, misfolded protein response, autophagy and apoptotic responses are tightly bound together. Among the most toxic phenomena for a cell is the misfolded protein signal, a signal that occurs far from the gene. This represents the target of the newest classes of drugs known as proteasome inhibitors and heat shock protein inhibitors, which function within the cytoplasm, not the nucleus.

It is exciting to imagine a day when physiologist, biochemist, enzymologist, physical chemist, and protein chemist regain their position as leaders in cancer research.

N.B: It should not go unmentioned that the EVA-PCD® assay offered by Rational Therapeutics is based on cellular function.

Of Prostate Cancer, Glucose, Metabolism and Metformin

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

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

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

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

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

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

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

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