Armed with a deeper understanding of tumor biology, insurers develop treatment algorithms to combat one of the most dreaded diseases
Cancer is one of the most fearful, and justly so, one of the most dreadful diseases to which the human family is liable.” So writes John C. Gunn, MD, in his 1864 book Gunn’s New Domestic Physician: Home Book of Health. In the minds of most people, things have not really changed much in the past 145 years.
Cancer is still one of the most dreaded diseases. Perhaps one of the reasons is that cancer is amazingly complex, involving profound changes in the basic genome and changes of cellular machinery that control cell reproduction, differentiation, and death.
From a medical perspective, the basic question is: How does a normal cell become cancerous? Is it sequential? Is it cumulative? What are the steps? Do they have to occur in a specific order? Can we define them? Can we find commonality among different types of cancer from different organs or are they separate and distinct? Why do not all cells become cancerous? Are there cellular mechanisms that somehow attempt to prevent these changes and, if so, why do they fail?
All of the attempts to answer these questions and the accompanying rhetoric have perhaps drowned out what is starting to become a rather sharply focused theory of the molecular basis of cancer. The most boiled-down concept of cancer is that there are genes that suppress the development of cancer and genes that promote the character traits of cancer. Derangements of either or both can lead to the development of cancer.
Yet this basic concept is too simple. Six fundamental changes may be required for a cell to turn cancerous. An article written in Cell by Douglas Hanahan and Robert Weinberg in January 2000, “The Hallmarks of Cancer,” outlined what appears to be the simplest conceptual model. They suggested that “the vast catalog of cancer cell genotypes is a manifestation of six essential alterations in cell physiology that collectively dictate malignant growth.”
- Self-sufficiency in growth signals
- Insensitivity to growth-inhibitory signals (also termed antigrowth signals)
- Evasion of programmed cell death (apoptosis)
- Limitless replicative potential
- Sustained angiogenesis (self ordering of a blood supply)
- Tissue invasion and metastasis
Each of these alterations allows the cell to overcome the natural defense mechanisms of cancer prevention. Every cell has at least one and, in most cases, a number of genes that control each of the six functions. Our cells actually have processes that attempt to prevent these six characteristics from becoming activated. Sometimes a protective process is not present at birth, but in most cases the changes appear to be acquired changes to the genome that appear after birth — changes induced by diet, radiation, or toxins. The changes can be either in the control mechanism of a gene or damage to the actual gene itself.
The result is that the brakes attempting to stop tumorigenesis are broken and the accelerator is stuck. In addition, the willingness of the tumor to listen to surrounding cells is shut off and the tumor orders its own blood supply.
Predicting tumor behavior
One of the current challenges is to use this knowledge to predict how tumors will act and how they will respond to chemotherapy. The overall response rate to chemotherapeutic drugs is in the 25–30 percent response range, so knowing the tumor susceptibility should advance clinical outcomes.
For example, several years ago Genomic Health developed Oncotype Dx, a gene expression assay for breast cancer. This test looks at 21 genes for an overall picture of how a breast cancer tumor will act over time, based on tumor bank samples of patients enrolled in already completed, randomized controlled trials.
Several organizations have established Oncotype Dx as part of their recommended guidelines for the treatment of node negative, estrogen receptor positive breast cancer. This test has crossed the hurdle of acceptability and is now widely being used by oncologists.
In early 2010 a second cancer, stage II colon cancer, may find itself in the cross hairs of genomic testing.
Genomic Health is well on its way to developing and quantifying the clinical benefits of quantitative tumor biology in a test termed the Oncyotype Dx colon-cancer test and risk score. Its gene validation study was based on an analysis of tissue samples from more than 1,800 patients with colon cancer and looked at 760 candidate genes to determine the target genes responsible for tumor aggressiveness and chemotherapy response.
A clinical validation study in about 1,500 patients was recently reported at the 2009 ASCO meeting to clinically validate the gene discovery findings. Half of the patients had chemotherapy and half received surgical treatment alone.
Following these patients for more than six years, the study found that 44 percent had a three-year risk of recurrence of just 12 percent, which is considered a low risk. The high risk group (26 percent) had a risk of recurrence at three years of 26 percent. Thus, the assay is capable of discerning those patients that are low/high risk and, based on the risk/benefit for the patient, the physician can individualize the treatment plan.
Although the test did not meet its secondary endpoint of being able to predict which patients might benefit from chemotherapy, the Oncotype Dx colon cancer test and risk score should offer important information to both cancer patients and their physicians. The new test should be available early next year.
The immense amount of work being done in genomics will soon bear more fruit. Are health plans prepared to handle the level of science and the analysis of the evidence needed to manage this area? Are they establishing and maintaining contact with cutting edge companies that are developing the science that will rapidly lead to a personalized approach? Are they willing to use their bully pulpit to drive these changes into the world of clinical medicine? Will they start to track the use of these tests and the resultant patient and physician behavior and outcomes?
These questions are in the forefront of an exciting new frontier of understanding quantitative tumor biology and applying the knowledge of tumor biology and drug responsiveness to what might be described as the “sweet spot” for payers — using the right cancer drug for the right patient at the right time.