You are looking specifically at a mutation that’s involved with the oestrogen receptor modulation. Tell me what it is, what is the big issue that you were trying to focus in on here.
Oestrogen is a key driver of breast cancers, we’ve known that for more than a century. What we were trying to understand is how is it that cancers start to grow despite us lowering oestrogen levels. What we found was that there were mutations in the oestrogen receptor that made the receptor active, even without oestrogen present. Our clinical questions were how often do we see these mutations and, secondly, if a patient has these, how do they do, what are their outcomes?
Now this is the ESR mutations that you’re talking about and there’s more than one of them.
That’s right. There are several mutations, there are two that are particularly most common.
So what did you do in the study that you’ve now reported here in San Antonio?
What we did was we took samples from patients on a large clinical trial, the BOLERO-2 clinical trial, all of whom had oestrogen receptor positive metastatic breast cancer. We took samples from them and asked is there a mutation present? In this case we used plasma, something called cell free DNA, DNA that’s shed from the tumour into the blood stream, to look for mutations rather than looking at a tumour biopsy like is often done. We looked for those two common mutations and we asked if you had a mutation how did you do, if not how did you do?
What did you find?
We found that the mutations were actually quite common. 30% of the patients had one of these mutations and we found that the patients who had mutations didn’t live as long as those who did not have the mutation.
These were affecting the way the aromatase inhibitor works on that tumour then.
It’s a little bit hard to narrow it down exactly to how the aromatase inhibitor worked. It’s clear from the data in the lab that the mutations prevent the cancer from needing oestrogen so you would think that’s related to the aromatase inhibitor. In the clinic we just know that they didn’t live as long and we deduced that those are linked but we don’t actually prove it by this study.
So your findings were precisely what? That the mutations meant a negative effect on overall survival?
That’s right, that there was a negative effect on overall survival and that’s consistent with the idea that they are so-called resistant to further aromatase inhibitor. And everything in the lab would tell us that’s the case but I want to be cautious. The clinical data that we precisely looked at couldn’t definitively answer that question.
Now these patients had all had aromatase inhibitor therapy, did they have these mutations on initial biopsy?
That’s right. We didn’t do a longitudinal study where we looked at pre-treatment and on treatment to precisely answer that. In general when we and others have looked for these mutations they have nearly always been associated with prior exposure to aromatase inhibitor. All of the other studies that have been done in the untreated setting haven’t seen these mutations. Now, maybe if you do some really sophisticated technology you can find the needle in the haystack but so far people haven’t found them there.
So does this look as though AI treatment is helping the environment for these mutations to flourish?
The AI environment is selecting for these mutations to emerge when they do. I would be cautious in just saying that for many, many women the aromatase inhibitor is curing their cancer, treating their disease effectively. It’s just when we look in hindsight at those in whom the cancer did come back we’re finding these mutations.
Now what impact did these mutations have on the use of other therapies?
So that’s a very speculative part of our study. We looked at the outcomes of patients who went on to the everolimus treatment and we did see that one of the mutations benefitted from the addition of everolimus, the more common mutation, just as much as those who didn’t have the mutation. One other mutation, it didn’t seem to have as much of a benefit in those patients. But we are very cautious, that was just almost speculative work on a small subset of patients but we need to validate that, I think.
What could be the main clinical implications as we stand right now?
I think there are a couple of clinical implications. First, a lot of people are sending their patients for genomic testing to look for new therapies for clinical trials. This study would suggest that if you’re looking for a trial that’s going after these mutations, plasma is probably a good source to get it from. Often clinical trials are taking archival old tumour specimens and looking for mutations. Our study would suggest a blood test done right at the time of interest in, say, a new study is maybe the way to go. It’s very sensitive and easy to get and seems to pick up these alterations. So that’s one major implication because there are large studies looking at drugs specifically against these mutations.
So practically how might doctors be capable, potentially, of using this new information?
For right now there are no FDA approved genomic tests for breast cancer, when I say genomic, sequencing based tests yet because none of the therapies. But they are coming. There are therapies that are right there in phase III that are being looked at. So right now it’s mainly going to be in an investigational setting. There are actually products out there that you could obtain today, you could submit your plasma sample and get an analysis, but it’s not been fully validated so we’re cautious about recommending them.
Nevertheless it’s disturbing for doctors to know that there are factors impeding the benefit of the anti-oestrogen therapies they’re giving, however beneficial those are initially. In a nutshell, what should doctors be remembering about all of this from the evidence you’ve got so far?
What doctors should remember, first of all, is that most patients are benefitting from these therapies. But we all know, all of us who are treating these patients, that some of our patients quickly come off of these therapies and those are patients who we should be thinking about clinical trials for. If we can obtain these kinds of mutational analyses we can put them on the right trials and hopefully develop more targeted therapies.