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Improving patient outcomes is top of mind for investigators at John Theurer Cancer Center in Hackensack, New Jersey.
Improving patient outcomes is top of mind for investigators at John Theurer Cancer Center in Hackensack, New Jersey. In spring 2021, the center announced that the on-site laboratory, Key Genomics, would open access to precision medicine, including testing with genomic profiling, to patients treated on site and by physicians within Regional Cancer Care Associates.1 The laboratory is part of a collaboration with Genomic Testing Cooperative in Irvine, California, which has developed DNA and RNA profiling assays that can be leveraged by physicians to perform molecular profiling of all solid tumors and hematologic cancers.
The Key Genomics laboratory has arrived at a time when personalized treatment decisions are driving patient care across tumor types. As patients progress on standard treatment regimens, the availability of genomic information has been pivotal to providing patients with treatments that offer the best outcomes.
“Right now, we have to use the data that is available to us with some of these newer broader [panels],” said Andrew Ip, MD, MS, chief of the Outcomes and Value Care Division and member of the Division of Lymphoma at John Theurer Cancer Center at Hackensack University Medical Center. “The commercial tests are very targeted and they may focus on the PD-L1 or EGFR mutations, for example, in non–small cell lung cancer, but they may still be missing the bigger picture for a patient and that may include other markers.” In an interview with OncologyLive®, Ip discusses practical applications for the wide range of information provided by broader next-generation sequencing and the challenges that come with an overload of information.
It’s a very interesting topic to discuss because I think most people understand what personalized medicine is, but basically, it’s just tailoring the treatment toward the individual patient. And I think the field of cancer, especially, has focused on tailoring treatment to the individual patient. We’re looking at very targeted drugs, [which require a] very specific test, as you had mentioned. I think that is probably because immunotherapy is the hottest wave of therapy for nearly 10 years at this point and we rely, at least right now, on markers such as PD-L1 expression, the major target for a lot of checkpoint inhibitors.
[However,] it’s just 1 marker. We know that a tumor or cancer is made up of many, many different interactions from the immune milieu or the immune cells that are around the cancer, the tumor microenvironment. Thatcould involve different protein interactions or the epigenetic environment that could lead to some of these different proteins [being expressed].
That’s where we’re headed now: We’re trying to expand beyond a one-marker-fits-all [approach]. These markers will be a magic shoe that fits [a certain patient] and will predict outcomes or predict response to a drug. But it’s going to take more than that because we know there are so many other different measurable markers that we can now look for with different technologies that are available to us.
At John Theurer we are interested in pushing the field forward, looking at [this information from] more of a research perspective to try and discover newer biomarkers or newer combinations of therapies that would show a better response based on [results of] the testing we run. That includes more targeted genomic mutation panels. We work with a company called the Genomic Testing Cooperative [and] we have an in-house laboratory now. For me, specifically as a lymphoma specialist, I can test for up to 400 targeted molecular mutations as well as chromosome [abnormalities] to [assess] the structural alterationson the chromosomes, which can be detected as well.
We can look at things such as cell-free DNA [and] cell-free RNA sequencing, and monitor patients for detection of these potential cancer signatures or cancer biomarkers. It is a very fascinating field because there are ways that we don’t know yet on how a patient will respond [based on this information].
Another big thing at Hackensack [Meridian Health] and the cancer center is that we have a very strong, scientific bench looking at the microbiome. That has really hit the news lately as investigators can predict response or predict relapse of different cancer types just by looking at the stool environment, which is interesting because no one would have thought about that 20 years ago, but it makes a lot of sense because every gastrointestinal tract has its own microbiome or bacterial signature.
That plays a huge interaction with the amount of inflammation a patient may have in their body, their immune status—how their body will monitor, detect, or destroy circulating cancer cells that are remaining. This is important for [patients with] stomach or colon cancers, but also could affect those who require bone marrow transplant. Investigators are using the microbiome to predict GVHD [graft-vs-host disease], which is just this phenomenon of the bone marrow transplant attacking the patient.
We’re looking to leverage that quality data with the genomic or clinical and pathologic data that we have available at our cancer center. Specifically, for my field, but for any oncologist, we want to know how do we predict response and prevent relapse? Both are very important clinical questions and it’s critically important for us because patients with lymphoma, especially those with chronic indolent lymphoma, could go through 5 or 6 different types of treatment that are now approved. Because it is a chronic illness, they could live many years even decades with chronic lymphoma.
We are trying to figure out how do you sequence the right drug therapies? We’re left with the NCCN [National Comprehensive Cancer Network] guidelines. You could do any number of the 10 [recommended] options, but they do not give us a clear way to sequence. That’s a huge question for some of the diseases I treat in lymphoma. For example, we have a large multiple myeloma group at John Theurer and, in addition to the myeloma investigators across the country and the world, we are trying to look at the available combination drugs for multiple myeloma and sort out how to correctly sequence them.
Lastly, I’ll say that with a lot of these newer biomarker monitoring or detection tools, measurable residual disease or MRD detection comes into play. By using liquid biopsies or targeted genomic mutation testing for the patients who are maybe precancerous or at high risk of developing cancer, can you predict whether they will develop cancer?
That’s huge. Many individuals may have at least 1 risk for cancer—whether it’s a family member who received a diagnosis or some kind of environmental exposure—individuals want to know if they will develop breast or lung cancer in their life. Answering those questions is part of our vision or goal with the data we are trying to leverage.
On the same spectrum for patients who are cured, or 5 years out, or maybe just finished their treatment and they’re in remission—how can we improve their outcomes in the time after they have completed their treatment? That may include using data from their socioeconomic background or their physical wellness or metabolic risk factors, such as obesity. All these factors affect a patient’s survivorship spectrum.
We’re also looking to prevent cardiovascular risk later in their life from their treatments or prevent cancer from coming back as well. There are late toxicities from our treatments. The post-cancer treatment spectrum is an untapped field.
It is easy to address the disadvantages of too much data at a clinician’s fingertips. In 2020, there were over 60 cancer drug approvals. That number is going to keep growing. Just looking at the number of drugs that are available for a community oncologist, there are hundreds of possible options, not to mention the combinations. As the possibilities start to exponentially grow, it becomes more and more difficult for a smaller practice or community-based oncology practice to keep up with all of these new drugs.
On top of that you have conferences with new updates or published journal articles, and these can encompass many different types of information, not just randomized clinical trial data, but new information on genomic mutations or different molecular targets. These data really stretch an oncologist’s mind because these are targets that the general oncologist may not have thought of or only learned in medical school many, many years ago.
Now you have to really understand it and learn it, because if you are going to prescribe certain agents, you have to know what they are doing; you have to be educated. The quantity of data can be a really big disadvantage. Looking for the quality of the data can be hard as well because there are so many sources of information that must be vetted.
There are advantages. You could look at the flip side, which is that the more options that are available for your patient, the better the outcome can be. You have more lines of therapies you could integrate into the rotation if they fail or progress after 1 or 2 or 3 prior lines. You could choose targeted drugs to tailor a patient’s treatment. All that information helps and I think it’s better for the patient. It’s just a disadvantage for the treating team because they have to synthesize and ingest all of that information.