The president’s proposed Precision Medicine Initiative, as mentioned in his recent State of the Union address suggests it’s probably time to get ready for some changes in our daily routines as health professionals.
I’m not talking about the incredible information that has already been produced by researchers examining the human genome. Nor am I referring to the work that is going on in major cancer centers and elsewhere exploring how to better match patients with genomic analyses of their cancers, for example.
And I am not talking about the advances in targeted therapies associated with diagnostic tests that can help guide the treatment of patients with a variety of cancers including but not limited to lung and breast cancers as examples.
No, I am asking whether we are prepared to usher in the new era of medical practice where genomic analyses in one form or another will be a part of our everyday medical practice. It’s not just about cancer, my friends. It will be coming to a primary care practice near you probably sooner than you realize — but it is coming.
For this discussion, I am going to stay within my comfort zone of cancer diagnosis, prognosis, and treatment. There are certainly many more experts than I who could expound on this topic not only in cancer care, but many other disease states that we are all familiar with. And primary care health professionals should not take comfort that this is a game in someone else’s (the specialists) ballpark. Patients are going to bring their gene analyses to you to help sort out what it means, and whether they are really at risk for the myriad of diseases that will show up in these profiles.
My concern is how we are going to adapt to the explosion in knowledge, treatment, and predictive strategies that is clearly in its very early stages of evolution. Our professional lives are already brimming to the top with expectations and demands. Genomic-guided health care is not going to make that burden any easier.
I could start at the top: too few of us are very comfortable with genomics and the science. We have a lot to learn, and we really need to pay attention. Otherwise, our science will quickly outstrip our ability to apply that science, although some believe that has already happened.
So where are we headed, using cancer as an example?
A couple of months ago I attended a meeting where a leading genetic researcher made a plea for simplified access to more cancer tissue for genetic analysis. Given our technologies, that is already happening in some parts of the country but is certainly not routine and is considered experimental, for the most part.
There are practical limitations to be sure, not the least of which is how we are going to pay for it and how can we get a uniform and easy way for patients to agree to allow the tissue to be accessed for research purposes. The researcher asked the audience a question: “Who wouldn’t check the box?” His answer to his own question? “Who wouldn’t?” After all, we are moving from the era of microscopic diagnosis of cancer to at a minimum supplementing that information with genomic studies, and perhaps creating a whole new diagnostic paradigm.
Let’s assume that such a mechanism was in place. As many of you know, we are doing more cancer diagnoses through needle biopsies. It seems like our surgical and radiology colleagues can put a needle almost anywhere. But that doesn’t give us much tissue, does it? And it seems that everyone wants a piece of it.
The reality is that there isn’t much to go around to do everything we need to do or would like to do. (Not to mention the “science” limitation that sampling one part of a cancer may miss a mutation elsewhere. But for now let’s not let that fact interfere with our hypothetical discussion or that metastatic deposits may have a different genetic signature.)
So now we have our tissue. Next step is doing a genome-wide analysis. The technology is either available or will soon be readily available to do this routinely, at a reasonably low cost. But it is still today primarily a research effort and the cost has to be covered. It is a lot of money, and someone will have to pay for it.
Once we have the analysis, we need to create a library of like samples, which has its own costs, not the least of which are analytics and storage. And this will produce lots of data where essentially the important signal has to be separated from the background noise.
Let’s fast forward to the future — that could be sooner than you think. We have solved the problems above, and every cancer patient and health care team providing care to those patients has the capability to accomplish these goals. That in itself would be incredible, so let’s remember this is, after all, a hypothetical discussion.
Now we have the data, we have the analytics, we have the science to tell us whether a patient has a particular mutation that dictates what treatment their cancer may benefit from, and even more futuristic whether their cancer is aggressive or not, with a high degree of probability. Let’s also assume that science has provided us with the ability to determine whether that particular mutation “expresses” itself clinically, or is only a matter of passing interest without impact on an individual’s cancer treatment or prognosis.
The next step is we need to get that information quickly and accurately to the treating physician in a manner that she or he can understand relatively easily. Then we need to match the information with existing therapies that may be useful in that patient. That, of course, assumes that we have performed the appropriate clinical trials or have the relevant experience and data that might come from the futuristic EHR that will tell us about the practical experience of patients similarly positioned, gaining that information from wherever it may reside around the country (another futuristic thought, given the logistical and privacy issues that we are working through as I write this).
We need to remember the experience oncologists faced many years ago with the drug cetuximab in metastatic colorectal cancer: just because we think a mutation might be related to a particular mutation doesn’t make it so. (When the drug was released, the FDA approved package insert said that an EGFR mutation predicted a higher probability of a beneficial response. Experience demonstrated that not to be the case. In fact, it was another mutation — KRAS — that eventually took the dubious honors.)
And, of course, as mentioned earlier, our systems of care really need to be able to provide feedback to a centralized system that will help us analyze whether this very complicated scenario really improved the outcomes for our patients.
There is another intriguing part to this brave new world of cancer care: will our future systems — including the much bemoaned EHRs — help us find patients “where they live” when we have a new drug that requires a clinical trial? Will we be able to take the genomic analysis of their cancer — now hypothetically done routinely in or by the local community hospital and entered into their patient record in this view of the future — and make it accessible to others when they find a new target worthy of consideration?
Experts are now talking about our analyses rendering every cancer a rare cancer with its own unique fingerprint. We are already in a situation where we know that the large majority of druggable targets don’t have a currently available drug. But that is going to change, if we can make the economics and the translational process work better as envisioned by collaborations such as CanceRX.
So, in this scenario, when a new drug comes along, it certainly would speed up the process if we have a more systematic way of finding the relevant patients and figure out how we can get them into a clinical trial, even if they decide they don’t want to leave their treatment team in their hometown, where they are probably more comfortable than they would be in a major cancer center. (We already have first steps in that process through the LungMAP initiative, which is focused on finding patients with recurrent squamous cell cancer of the lung. That program is not only valuable in its own right. It is in fact a possible blueprint for the future of cancer and medical care, a start on a much longer and more complex journey.)
So here we are: huge potential, but many barriers and limited resources. We are really talking about a fundamental change in the orientation of how we make treatment decisions for cancer patients. And as I mentioned earlier, it isn’t just about cancer.Pharmacogenomics is another example of how we need to understand how to apply this burgeoning knowledge of how different drugs have different impacts in different patients.
And on top of all of this, we still have to figure out how we are going to give the everyday, bread and butter care that our patients expect and deserve. We need to figure out how they are going to best handle the financial and psychological issues they face. We need to figure out how to best manage their symptoms though effective delivery of palliative care. And we have to figure out how to pay for all the “gee whiz” technology that is at our fingertips.
Daunting? Perhaps. But this is where we are headed.
Oh, and one more thing: we could make all these investments and find they may be for naught. I have heard some of the immunotherapy folks make great claims that their incredible science will turn many patients and their immune systems into long term cancer fighting/scavenging machines.
Maybe that’s true, and maybe it could make targeted therapies less relevant. But the past is prologue to the future and the past suggests that such high expectations may not be completely fulfilled (although currently they have much promise). And there is also the belief among some (many?) that it is going to be a combination of targeted and immune approaches to cancer care that will literally win the day. Only time — and high quality clinical research — will give us the answers we need.
As some of us with a bit of gray hair have learned, sometimes the hard way: never say never. The only question is whether all of us together are going to make the commitments we need to make to bring the future enabled by genomics closer to the present.
There is no time like the present to start the discussion and explore the promise. We still have a very long road to travel and it’s time we got started on the journey.