Selecting Therapies for Cancer Patients: Past, Present, and Future
Clifford Reid, PhD
We are in the middle of a revolution in DNA sequencing, which has ushered in the era of precision medicine in cancer. Unfortunately, the impact of precision medicine has been quite limited, reaching only about 15% of cancer patients, and benefitting only about 6% (SCIENCE, 27 APRIL 2018 • VOL 360 ISSUE 6387). An analysis of how therapies are selected for cancer patients helps explain the current challenges of precision medicine and points to a promising future for personalizing cancer therapies.
The Past: Population Medicine
Since the inception of the modern FDA in 1938, drug development companies have followed a rigorous procedure for achieving FDA approval for new cancer drugs. They have selected groups of patients with similar cancers (such as breast cancer or lung cancer) and conducted “randomized controlled trials” (RCTs) that provided clear clinical evidence of the safety and efficacy of their drugs for the chosen groups of patients. Once approved, these drugs were given to new cancer patients with the same cancers as the patients in the RCTs.
Using this methodology, the FDA has approved over 400 cancer drugs over the last 75+ years. Unfortunately, a common and disappointing characteristic of these drugs was that they worked for only a minority of cancer patients, and most drugs that initially worked stopped working after a relatively short period of time, ranging from a few months to a few years. Despite the large number of new cancer drugs, cancer mortality in the US grew from 1938 to 1985, when the reduction in smoking caused cancer deaths to start to decline.
The Present: Precision Medicine
The revolution in DNA sequencing, which started in the late 1990s, ushered in the era of precision medicine. The purpose of precision medicine is to develop cancer drugs that target DNA mutations present in cancer cells but absent in normal cells, thereby killing the cancer without harming the patient. These drugs are known as “targeted therapies.”
Developers of targeted therapies were required to follow the same rigorous procedure for achieving FDA approval as the previous generation of non-targeted therapies. They selected groups of patients with similar cancer gene mutations (such BRAF or EGFR gene mutations) and conducted randomized controlled trials that provided clear clinical evidence of the safety and efficacy of their targeted drugs for the chosen groups of patients. Once approved, these drugs were given to new cancer patients with the same cancer gene mutations as the patients in the RCTs.
Using this methodology, the FDA has approved 84 targeted cancer drugs over the past two decades. One of these drugs, Gleevec (also called imatinib), has worked miraculously for chronic myeloid leukemia patients who have a certain gene mutation (“BCR-ABL”). But to the surprise and disappointment of the precision medicine community, almost all other targeted therapies share two characteristics:
- Like the earlier generation of non-targeted therapies, they work for only a minority of cancer patients, even though these patients have the mutations that the therapies target, and drugs that initially work typically stop working after a relatively short period of time, ranging from a few months to a few years.
- Most targeted therapies occasionally work for patients who do NOT have the targeted mutation. There is clearly something we do not understand about how these targeted therapies work.
The cancer community initially named this approach to developing targeted therapies “personalized medicine,” but came to realize that grouping patients by cancer gene mutations was not personalized, it was simply a better form of population medicine that more precisely targeted populations of patients who shared one genetic characteristic. This approach was aptly renamed “precision medicine.”
In addition to enabling the development of targeted therapies, the revolution in DNA sequencing led to a new discovery that explains much of the disappointing similarity in the effectiveness of the earlier non-targeted therapies and the new targeted therapies:
Cancers are heterogeneous.
If you have cancer, you probably do not have one type of cancer. You most likely have five or more genetically distinct cancers (JG Lohr et al, Cancer Cell. 2014 January 13; 25(1): 91–101). This explains why a single therapy — targeted or not — typically fails to eradicate a patient’s cancer. It very well may wipe out one of the five or more cancers, which then leaves room for the other cancers to grow.
If each cancer patient has a unique mixture of multiple different cancers, and that mixture is changing over time and in response to selective pressures from therapies that are effective against some but not all of the different cancers, how can we develop effective personalized therapies for each cancer patient?
The Future: Personalized Medicine
There are two emerging paradigms for developing personalized therapies for each cancer patient. The first modifies each patients T-cells (their cancer-killing immune cells) to target their unique cancers. These “immunotherapies” have achieved some spectacular early results (reminiscent of Gleevec in the early years of targeted therapies), but have encountered major barriers to widespread adoption, including extreme toxicity and prohibitively high costs of creating a custom therapy for each patient.
The second emerging paradigm of personized medicine for cancer uses a very old and low-tech method to find a combination of therapies that target each of the multiple types of cancers in each patient:
Trial and error.
Of course, trying the dozens of targeted therapies and hundreds of non-targeted therapies in each patient is not practical: the drugs are far too toxic, it would take much too long (decades) to try them all, and it would be prohibitively expensive.
The solution is to try the drugs OUTSIDE the patient rather than INSIDE the patient. That is, instead of administering the drugs to a patient, remove some of the cancer cells from the patient and apply the drugs to these removed (“ex vivo”) cancer cells. We can then try hundreds of drugs (in very small quantities) against hundreds of small collections of cancer cells. This approach completely eliminates toxicity, dramatically reduces the cost (because we only need enough drug to treat a few cells, not a whole person), and only takes a couple of days.
Cancer researchers have tried and failed for many years to create a reliable ex vivo cancer drug effectiveness test. Fortunately, recent advances in live-cell laboratory procedures and measurement tools have made this trial and error approach possible.
In addition to being safe, inexpensive, and fast, this trial and error approach has some other powerful properties. First, it can adapt to a patient’s changing cancer. If you have an aggressive cancer, you may need five drugs this year, and a different five drugs next year, and still another different five drugs the year after that, as your cancer continues to change. Fortunately, we have over 500 FDA-approved cancer drugs, and while they may be individually ineffective against heterogeneous cancers, in the right combinations they may prove to be highly effective.
Second, we can develop effective combinations of therapies without fully understanding how our cancer drugs work and why different cancers respond to them. The more we have learned about cancer, the more we realize how much we still don’t know. Trial and error outside the patient enables us to overcome this lack of knowledge and find drug combinations that work for patients with heterogeneous cancers today, long before we have completely understood the complex biology of cancer and the complex effects of our cancer drugs.
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