Precision Medicine: Identifying Actionable Biomarkers

Video

Transcript: Benjamin P. Levy, MD: I think it’s important to sort out the differences between NTRK fusions versus mutations versus amplifications, piggybacking on what we’re talking about with our NGS [next-generation sequencing] reports, which are going to report all this out. Phil, do you want to briefly talk about what is really predictive when you see these on the report? What are we looking for?

Philip Agop Philip, MD, PhD, FRCP: It’s very simple. Based on what we know of the biology, based on preclinical data, and also from the patient experience, the fusions are the ones we really are interested in. There are point mutations you see, usually in the kinase domain of the protein. But those don’t really appear to be affecting the biology and don’t seem to be affected by the treatment. The amplification, which is, again, very rare—there’s no evidence for that to really make it a target for treatment.

So for the practitioner, they must be looking for the fusions. These are the ones that really matter, in terms of what we’re discussing today, in terms of treatment and interventions.

Benjamin P. Levy, MD: Has anyone seen, when they’ve ordered the NGS panel and are trying to interpret the results, these mutations—not the fusion, but either an amplification or a mutation? I’ve seen this twice now.

John L. Marshall, MD: And in IHC [immunohistochemistry] too. There are all sorts of ways it comes out.

Marcia S. Brose, MD, PhD: I get referred patients all the time who have NTRK. Actually, point mutations are probably the most common.

Benjamin P. Levy, MD: They are.

Marcia S. Brose, MD, PhD: And running a center for rare cancers, anytime anybody has an NTRK point mutation, they all call me up. I’ve learned to actually ask them to send me their report before I make a whole bunch of appointments. But again, that sophistication—there’s a lot of education that needs to get out there to the people who are ordering these tests so they can make sure that they can explain; and also, to work with the company who’s doing the testing.

When we were first doing the trials and this became clear, that it was going to be positive, the conversation was also, “Let’s work with the people who are doing the testing, so that when they give you that list of all the drugs that might work, put, ‘Do not use these drugs for a point mutation.’ ” And so there’s a lot of coordination that has to go into making everything consistent across the education and the information that actually gets to the patient.

Mark Agulnik, MD: The drug is still on the list.

Marcia S. Brose, MD, PhD: I know.

Mark Agulnik, MD: Last week I received it and, again, it talked all about…

Benjamin P. Levy, MD: So you received a report, Mark, that said “NTRK point mutation?”

Mark Agulnik, MD: The amplification. And in the report, it talked all about larotrectinib.

Benjamin P. Levy, MD: Yeah. Even as a guy who dabbles in the field of targeted medicine and targeted oncology, 6 months ago—right when the publication came out—I did get an NGS report that showed an NTRK point mutation. I thought I got the golden ticket. I’m still learning about the actual aberration that’s predicted to these drugs. I called Dr Alexander Drilon [of Memorial Sloan Kettering Cancer Center], and I said, “I have a patient for you.” And he’s like, “Point mutations don’t matter.”

Mark Agulnik, MD: A big disappointment.

Benjamin P. Levy, MD: A big disappointment, I know. I’m glad I didn’t share the information with the patient. I was trying to read through all of it.

John L. Marshall, MD: Ed and I have talked a lot about this—about companies that we’re partnering with that are doing a lot of this profiling. It’s really important that they maintain the highest level of science. They don’t always. Sometimes the science changes and there’s some evolution. And from their angle of things, they want to be valuable in the marketplace. And so they kind of keep score of how many actionable items are on their list, and if they’re gray…. So we have to be very careful. It falls to us to interpret it.

The sort of equation I like is when that radiologist on your CT [computed tomography] scan finds something, and they say, “recommend MRI.” We all have enough judgment to know whether we really need to do that MRI [magnetic resonance imaging] or not. I think we need to be at the level to be able to interpret these things ourselves and not rely on these reports that come in the mail.

Marcia S. Brose, MD, PhD: But I will say, having had 1 of the patients with a point mutation on the trial, it doesn’t do anybody any good, the company included, to have those patients treated. Then all of a sudden, this wonderful drug with this 50% response rate will get a bad name very fast. So I do think there’s a reason for everybody to be on the same page.

John L. Marshall, MD: I’ll bet you the insurance companies know the difference between a point mutation.

Marcia S. Brose, MD, PhD: Well, if they don’t, they’re learning it really fast.

Mark Agulnik, MD: I would argue they would if they need to. Before the drug is released, they should have 1 of these reports.

Marcia S. Brose, MD, PhD: The problem is the guidelines are about 10 years behind any publication and FDA approval. I work with that every day.

Edward S. Kim, MD: I think it’s important. Again, we all hate looking at these reports. We like the data that come, but we don’t like them as well, because they’re very confusing. But I’m glad that people are doing them. I’m glad I’m hearing that a person is referring someone to you who finds anything with TRK in it or whatnot, because a) that means people are actually doing it. You can’t find anything unless you do it. We had this phenomenon in lung cancer years ago in which the doctors would come up and say, “Well, I’ve never seen a ROS1.” I said, “Are you testing for ROS1?” You know, it’s like the lottery. You’re not going to win the lottery if you don’t play it. I’m not telling people to go play the lottery. But you’re not going to find a TRK. You’re not going to find a ROS1 unless you’re doing the testing. So I’m glad people are doing the testing. I’m glad it’s easy. But just as you all said, it’s on us to hold these companies accountable for what’s on their reports, and then also help educate the less specialized folks. We all feel very less specialized up here, which is kind of ironic because this is a very new and complex area. And so we’re all in the same situation here.

Philip Agop Philip, MD, PhD, FRCP: But for a community oncologist, to remember this detail of the difference between mutation, amplification. People like it because HER2 /neu [human epidermal growth factor receptor 2] amplification….There’s something there. Again, they’re very hardworking people, and they have to deal with so much information.

John L. Marshall, MD: Well, look at the tests that evolved over the years, right? We think to ourselves, “Oh, we did that test in 2016, 2017. It’s in the chart. I know where it is.” The point is, those tests didn’t measure this. And so we also have to keep up with what tests we sent. What was its status at the time? How broad was that testing? We think we did it already. It was everything we knew. It turns out that it changes over time.

Benjamin P. Levy, MD: Which just tells us how fast we’re moving. I mean, 6 months ago or a year ago, maybe some of the tests you were doing are now out of date.

Transcript Edited for Clarity

Related Videos
Sangeeta Goswami, MD, PhD, of The University of Texas MD Anderson Cancer Center
Pasi A. Jänne, MD, PhD, discusses an exploratory analysis from the FLAURA2 trial of osimertinib plus chemotherapy in treatment-naive, EGFR-mutant NSCLC.
Andrew Ip, MD
Arya Amini, MD
Adrianna Masters, MD, PhD,
Chul Kim, MD, MPH
Andrew Ip, MD
In this final episode of OncChats: Assessing the Promise of AI in Oncology, Toufic A. Kachaamy, MD, and Douglas Flora, MD, LSSBB, FACCC, discuss a roadmap of artificial intelligence (AI) advances in the next 5 to 10 years.
In this eighth episode of OncChats: Assessing the Promise of AI in Oncology, Toufic A. Kachaamy, MD, and Douglas Flora, MD, LSSBB, FACCC, explain how artificial intelligence tools are being developed to match the right patient to the right drug on the right clinical trial.