The traditional method of minimal residual disease detection in myeloma, which is when we look for a very small amount of myeloma cells, maybe there’s only a handful of cells left in the patient, is actually by counting cells. So the main thing that we do is multiparameter flow cytometry. Essentially we take a whole bunch of cells from the patient’s bone marrow and we tag them with all sorts of things that change colour, for example when we shoot a laser at them, based on what the outside of those cells look like. Then we run them through a machine and then if we see cells that look like what we’d expect cancer cells to look like we say that patient has x many cancer cells, or this proportion of cancer cells.

We’ve advanced to more inference-based methods. So, for example, a relatively new method is called adaptive ClonoSEQ where we sequence the DNA of the immunoglobulin region. So that’s the part of the DNA which will make proteins to signal that that is a cancer cell, for example, if it matches the sequence that we’d expect the cancer cell to have.

Now, cell-free DNA is an even further inference because we’re no longer looking directly at the bone marrow cells, we’re actually looking at the peripheral blood, which is all the blood that’s circulating around our body, for any kind of hint that the cancer is there. So the method that we focus on is looking at mutations - you can imagine like a needle in a haystack. So, traditionally, when we look for specific targets of a cancer, like the DNA matching that specific pattern which we’d expect the protein to look like on the cell, it’s only one major area that we’re looking at. But what we do is a little bit different. We first take the tumour cells at diagnosis which the patient is getting anyway and we get thousands of mutations from that data because we use whole genome. Now we have 10,000 targets that we could be looking for. We then take blood after a patient has been treated, when we’re monitoring them, and if we find those mutations in the blood that’s a way of inferring that there’s still some cancer cells left.

What are the main technical challenges associated with using cfDNA WGS for MRD detection in multiple myeloma?

The first main challenge is that we’re not dealing with the tumour directly. So the tumour is all the way tucked in the bone marrow. But we don’t want to go directly to the bone marrow because that’s really invasive. You can imagine a huge needle coming in to the back of a patient’s pelvis; it’s a procedure that has to be done typically in a hospital with a medium-sized team. A patient if they live far away from a centre, they may not want to drive there. And also it’s painful. So let’s say that this is something that we’d want to do every three months to monitor a patient – that’s not really feasible.

So the easy way is let’s just take their blood like a normal blood draw. But then the technical challenge begins that this isn’t a tumour, maybe 1% or even less than 1% of all the DNA in the blood is even coming from the tumour. Because all of the organs of the body are shedding DNA into the bloodstream. Then, even if we find mutations how do we know that those mutations with those changes in the DNA, which would suggest to us that there’s disease present, is even coming from the cancer? Because maybe it’s just a random change that has nothing to do with the cancer, or what we’d call CHIP – clonal haematopoiesis of indeterminate potential – which is also very common in myeloma.

But we’re working to solve these challenges. First off by applying really good mutation filtering techniques to the original mutation. So our method – we get the original mutations from the bone marrow at diagnosis and then we track those mutations over time in the blood. By looking at things, for example, like the quality of the DNA at that area, how much DNA was there and also how long or short the DNA was in the blood that has those mutations, we can better filter if the mutation is a real or a likely cancer-associated mutation or something random like CHIP, which isn’t useful for our monitoring purposes.

How does the use of cfDNA WGS for MRD detection impact clinical decision-making and treatment strategies for multiple myeloma patients?

Our goal is that cell-free DNA MRD detection can be something that is regularly used in the clinic. For instance, maybe every three months the patient can get their blood done, we can get a test score based on that, based on if they found these cancer-associated features like mutations in the blood, and then the clinician can decide if they want to change up the patient’s treatment strategy.

Now, it’s important that this is very early stage data so before any of this could be done on a large scale we’d need a clinical trial that would validate that this technology is improving patient outcomes. But the ultimate goal is that in our preliminary cohort of about 12 sites in Canada, we’re working on a study, it’s called the M4 study – Multiple Myeloma Molecular Monitoring. So about a dozen sites across Canada we’re doing the initial test. So we’re giving patients this test and the other traditional test.

So far preliminary results show good correlation with those tests and actually the ability to see even more positives in our method than those traditional tests. The reason we think that is is because we’re able to capture all of the DNA in a tumour and not just the region directly where the needle is going in. That’s just a general limitation of traditional bone marrow aspirates – we’re pulling up cells but we’re only getting the cells around the area where the needle was. So let’s say that there was another tumour clone that was on the other side of the pelvis, that might be missed.

So right now we’re working out the quirks in our initial test set and the goal is that ultimately there will be a bigger study and we’ll see, based on the results of that study, if this is something that improves patient outcomes. Then this will be another test that clinicians can order for their patients that will be less invasive. So if a patient doesn’t want a big needle, they can just get a normal blood draw, easier to access so they won’t have to drive into a large centre, and, ideally once the whole bioinformatics or the analysis process is optimised, something that we could get to a patient very quickly, like within a matter of days.

Looking ahead, what are the potential advancements or improvements in cfDNA WGS technology that could further enhance its utility in MRD detection?

There are many areas where I believe that we can improve this test. First and foremost is not looking only at mutations. So what’s interesting is the DNA that we get in the blood is not the same amount of DNA everywhere. So let’s say that I take the DNA and then I map it to where it falls in the genome, which chromosome it falls on. I won’t see the same amount, I’ll see some areas with a lot of DNA and some areas with a little bit of DNA. The reason is because the DNA that’s protected by a nucleosome, which is this protein that the DNA wraps around in the blood, I end up seeing more of that because it’s less degraded, there are less things trying to break it down.

Now, the way that we can use this to improve MRD is there are places in the DNA which we know that the DNA has more or less nucleosomes, or those proteins protecting it, uniquely in myeloma and not in healthy samples. That’s done through another technology called ATAC-Seq. But because we know those regions, we can look at those specific sites and see if we see a lot or a little bit of DNA to infer if the chromatin, which is the structure of the DNA with those proteins, resembles what we’d expect it to look like in myeloma.

On top of that, we can also look at things like copy number changes, so did the patient gain a chromosome arm, for example. All of this data together, in addition to even other things like what does the DNA look like at the end of the fragments that we see, it’s called end motifs, can help us build a more robust model to give us even greater accuracy when we’re deciding if DNA from a patient’s blood is likely coming from a multiple myeloma tumour or is just healthy DNA.

I’m always happy to collaborate with other centres so if you’re watching this from a centre and you’d be interested in learning more about our cell-free DNA technology I’d be happy to get in touch so please feel free to reach out.