Genomic Profiling in High-Risk Smoldering Myeloma | Benjamin Diamond, MD | ASH 2023

So, hi, my name is Benjamin Diamond. I work at the University of Miami. I'm an assistant professor. I work at the Myeloma Institute. And at this conference, what I'm presenting on is the genomic contextualization of treated high-risk moldering multiple myeloma. It's a little bit of a mouthful, but the idea basically is that there are a lot of trials that focus on trying to intervene upon high-risk moldering multiple myeloma because there's a very high chance that these patients will someday progress into having active disease, active multiple myeloma. And we really want to run these trials to prevent the progression, to end organ damage, or just to prevent the progression to active disease. And there's been studies that have been done over the past couple of years that have really shown that treatment for these patients can improve their outcomes in that regard. The question that we ask then is, is it truly that the disease biology at this point in time is more simple, it's easier to treat? Is it more susceptible to the therapies that we're offering, or is it just that we don't really know how to classify high-risk moldering multiple myeloma? And then the clinical risk scores that we're using to determine who truly has high risk might be a little bit inaccurate. And so what we've done here is combined two parallel clinical trials, one using KRD and Revlimid and one using elatuzum and Revlimid and dexamethasone. And we looked at the patients that were treated on these high-risk trials. We performed genomic sequencing, so for half the patients whole genome sequencing and for the other half the patients whole exome sequencing to try and really understand what were the genomic mechanisms that were driving this disease forward. And what we find is sort of unsurprisingly that the clinical risk scores were not very good at predicting who was going to have a poor outcome with these treatments. And really it was the genomic characteristics that were able to predict those things for us. What we saw then is that the patients that did exceedingly well, that had really good outcomes that didn't progress, that had prolonged freedom from disease and also really nice deep responses, were those that had extremely simple genomics. In other words, there weren't very many driver genes, there wasn't very much complexity in the genomes. These were patients that had very indolent looking disease. And the argument could be made that the clinical risk scores were sort of overclassifying them and sort of overestimating how high their risk was. And that sort of explains why their outcomes were so good in these trials. On the other hand though, you did see a subset of those patients that did have the complex genomics. Things that were big jumbling of their DNA, they had chromothripsis, they had very significant APOBEC mutational signatures and a lot of different driver genes. And these are the patients that actually didn't do so well with the planned interventions. The KRD and the ELO-RD were not really good enough to provide them with a long freedom from progression to myeloma. And so our argument is basically this, that the clinical risk scores that we currently have, they're reasonably good. But when it comes to putting patients on these trials, they're a little bit inaccurate and they include a very heterogeneous group of diseases. There are people that are really bound to have very aggressive myeloma sometime very soon and there are other people that might be best served by observation. And so we argue that when we perform genomic contextualization, we're able to more accurately figure out who really is in need of better interventions, who might need different interventions and who might be best served by observation. And we just advocate that moving forward when we perform these studies, that we're going to be using genomic contextualization, genomic profiling, rather than just the clinical risk scores by themselves.