My name is Ciara Freeman.
I work in the Department of Blood and Bone Marrow Transplant and Cellular Therapy at Moffitt Cancer Center in Tampa, Florida.
I'm here at the annual society meeting of the American Society of Hematology in San Diego.
The results that we have obtained looking at myeloma cells in patients prior to being treated with either a CAR-T cell therapy, which is a very novel therapy that we use, or bispecific therapy, both targeting the B-cell maturation antigen, which is a target on the surface of myeloma cells that we use commonly as immunotherapy targets.
So both for CAR-T therapy and for bispecific therapy.
And so what we did was, we took a cohort of patients where we had available material from their bone marrow cancer cells, plasma cells.
And we did whole genome sequencing on a large cohort of patients trying to understand.
Is there a way that we can identify those patients who are going to either have a great response to their CAR-T cell therapy and do very well?
And are there patients who are destined not to respond as well as we would like?
And what are those features that will confer resistance to therapy?
And we have some features clinically that we look at traditionally in patients, we think, who have higher risk of not doing as well.
Sometimes those are basic genetic features that we do routinely in clinical practice.
Some patients may be aware whether they have FISH alterations that confer high risk, whether that's an abnormality of chromosomes, where piece of material goes from one to another.
But these usually don't tell the whole story.
Neither does the presence of lots of disease in the bone marrow.
We also think that the presence of very inflamed stage.
So having high inflammatory markers before you have these treatments may confer resistance or the presence of myeloma that can live outside of the bone marrow.
So extra medullary disease.
So when we look at these clinical parameters they can sometimes tell us maybe these patients won't do well, but they're not as accurate in really identifying those patients who are destined to either do very well or to not do very well what we call to be refractory or have early progression.
And that's devastating for a patient because it's a big ordeal to come and do these therapies.
And what we want to do is to be smarter in our approach to identifying what's really going to work well for patients.
If they're going to do all this, we want them to have the best possible outcome.
And what we found was there are a number of genes that are altered.
And especially they kind of cluster together to form this high risk genetic profile.
And those patients do not fare as well.
And actually, when you adjust for those features, the other clinical things that we look for become less important that really you can identify those patients who are destined to fare badly on the basis of their genes before you even administer the treatment.
And I think that that's really exciting, really interesting.
And we're going to obviously build on this and grow this understanding to understand and develop models that can help us choose a therapy that's going to work the best possible way for patients.
The other thing we were able to identify is which patients have got no expression of that marker on the surface of their cells at all.
And those will never respond to that target.
So you're better off using a completely different approach for those particular patients.
It really supports this idea, 2024 now.
We've got all these tools in our toolbox.
We should be able to pick the right tool for the right patient based on their disease and make sure that they get the best possible outcome.
So this data is really supporting that approach.
And there's more to follow.
It's a really exciting time.
There are certain genetic changes that we found were associated with basically having lower expression of the target that the CARs or the bispecific go after.
And so there's a variety of ways that you could address that.
One would be, as you said, a combination strategy maybe where you have not just that one BCMA target, but maybe add in a different target that might be expressed in a different way.
The other thing you could do is you could have strategies where you upregulate that target in the face of lower expression levels.
And these are all strategies that are being investigated both in trial form and in the lab.
You know, are there ways that we can we can artificially force that cell to express more of the target of interest.
Now, obviously, if you've got complete loss of that target, then you're going to have to take a completely different approach.
And so I think that this is all a work in progress, and definitely more that we can build on to try and identify which are the patients who are going to do really well with single agent, which are the patients who might need two agents.
And what are those two agents, and which of the patients will need a completely different approach, targeting completely different molecule.
It is more than just biomarkers to some extent.
It's looking at the genomic makeup of the cancer cells and trying to understand how that biology will translate into how the cell behaves in the patient, how it responds to therapy.