KarMMa Study: Immune Profiling in CAR-T Therapy for Myeloma | Bruno Paiva, PhD | #ASH24

I’m Paiva from the University of Navarra in Pamplona, Spain. And at this ASH, we are presenting data on immune profiling before, throughout, and after anti-BCMA CAR-T therapy for relapsed refractory myeloma patients. More specifically, patients were enrolled in the KarMMa study and received Ide-cel.

We believe this is important data because knowledge about determinants of response and resistance to CAR-T therapy in myeloma are still at the very beginning. We know that antigen escape is important, but it's not a universal mechanism of resistance. And we also know that depth of response is important, but it fails to predict what will happen at the individual patient level, particularly among MRD negative patients. There are many that unfortunately relapse early on.

And of course, the hypothesis was that the patient immune status was an important factor to predict who will benefit the most from anti-BCMA CAR-T therapy. First, we start by identifying that patient immune status was different according to the number of prior lines of therapy; T cells were more exhausted in patients with five or more previous lines of therapy. And we also found that a more exhausted phenotype was seen in those patients with advanced staging.

And it was possible to develop an immune response called baseline. It was associated with significant different PFS. Now regarding the CAR-T product, we showed that the percentage of CAR-T cells at peak expansion around one month after infusion was prognostic. We also found that the CD4/CD8 ratio was prognostic, but we found that deep CAR-T cell phenotyping, much more comprehensive than just the percentage or the CD4 to CD8 ratio, was much more prognostic in terms of PFS.

And importantly, we showed that a CAR-T immune risk score was able to stratify patients that were MRD negative, also, at month one. PFS was completely different within MRD negative patients. If a favorable risk score based on CAR-T cell phenotypes or unfavorable, which was associated with significantly fewer PFS, and finally, we showed that even though CAR-T cells are persisting only for a short period of time, the CAR-T expansion and profound tumor reduction were associated with endogenous modifications.

During the first year, mainly T and NK cell subsets were being modified in terms of percentages throughout the first year of treatment, and this is again associated with the strong CAR-T cell expansion. Broadly, cytokine production and endogenous anti-tumor response. And again, we showed that at late stages, six and 12 months after the infusion, again, a patient immune risk score was able to stratify.

And this points out, I believe, hopefully to the value of active immune surveillance after CAR-T infusion, peak expansion, and disappearance. And all this may be able to stratify patients that, because of immune surveillance, will enjoy longer PFS. All by contrast, there is immune escape, and relapse will occur in a short period of time.

It's being investigated worldwide. There are different technologies, some more sophisticated or some more expensive, others less sophisticated but more cost-efficient. The one we typically use is flow cytometry. Flow cytometry will be on the side of less resolution, less sophistication. It's single-cell technology, but an older one. The advantage is that it's worldwide available and it's used for many different clinical purposes.

Therefore, if we are able to benchmark immune biomarkers that could be monitored using flow cytometry, this could be applicable around the world to all the patients, and that will be a key advantage. Unfortunately, benchmarking immune biomarkers is much more difficult when compared to genetic markers or, for example, MRD or even more recently, circulating tumor cells. I think the reason is because the technology, there are a lot of heterogeneities regarding technology on one side.

On the other side, the patient immune status is a reflection of many different factors, not only sensitivity or resistance to treatment, but it's also a reflection of tumor burden in contact with tumor. It's also a reflection of aging, inflammation, other diseases, medication for the other diseases. And I think these are a lot of confounding factors that make it more of a challenge to identify and standardize immune biomarkers.

The solution is big data and international collaboration. I think that the immune status of everyone is completely changing. It depends on a lot of internal and external factors. This is important because one of the areas that we and other groups are investigating is whether or not, for example, the peripheral blood is representative of the immune composition in the marrow. We believe it is.

And this is very important because being blood, it's minimally invasive. And you can monitor frequently, which is not possible using the marrow. And then leverage on scenarios that introduce profound changes in the immune composition. One scenario, obviously, is high-dose therapy, followed by autologous stem cell transplantation. To some extent, this is clear. And we have the data. It’s clearly modifying the immune composition. It's replenishing with new immune cells.

Probably the fitness is higher. And we all believe it. Probably this is an important time point to introduce some of these new immunotherapies. And achieve even better outcomes, and ideally with shorter treatment duration.