Genomic Features Associated With Higher Risk of Progression in Smoldering Myeloma

In an interview with Targeted Oncology, Mark W. Bustoros, MD, discussed the findings from the study evaluating the genomic predictors of progression in patients with SMM and how these findings will impact treatment decisions for these patients in the future.

Mark W. Bustoros, MD

According to data from a multicenter study of 214 patients with smoldering multiple myeloma (SMM), certain genomic features may put patients at a higher risk for early disease progression. By detecting these genomic predictors earlier in the clinic, these features can help inform treatment decisions in this patient population.

The study evaluated patients across multiple centers in the United States, the United Kingdom, and Europe to detect mutations and genomic alterations that are enriched in patients with SMM who progress at a faster pace than others. Some of these genomic features includeNRASand KRASmutations, as well as MEK alterations and others.

Results from this study showed that patients with SMM harboring these genomic features had a shorter time to progression compared with patients that did not have these mutations or alterations. This study is the first to demonstrate that the biology of the disease matters in patients with MM.

“We are very focused on translating this to the clinic as fast as we can. In the end, we want this to have an impact on our management for patients with SMM,” said Mark W. Bustoros, MD. “We are planning some validation cohorts to expand our findings and validate these data more.”

In an interview withTargeted Oncology, Bustoros, Dana-Farber Cancer Institute, and Harvard Medical School, discussed the findings from the study evaluating the genomic predictors of progression in patients with SMM and how these findings will impact treatment decisions for these patients in the future.

TARGETED ONCOLOGY: What was the rationale for this study?

Bustoros:Our study was focusing on patients with SMM, and it’s a multicenter study for 214 patients with SMM. Our objective and goal were to understand the genomic landscape and mutation landscape for SMM and see if this heterogeneous group of patients have the same molecular profile or not. Moreover, we also wanted to translate this to the clinic by adding fine genomic predictors of progression from SMM to overt myeloma where patients haveknown organ damage symptoms. That was the goal of our study.

TARGETED ONCOLOGY: What were the findings from this study?

Bustoros:As I mentioned, [this study evaluated] 214 patients from multiple centers in the United States, Europe, and the United Kingdom. Sequencing was done at the lab at Dana-Farber and Getz Lab at the Broad Institute. We found that certain mutations and genomic alterations are enriched in patients who progressed faster than others.These genomic alterations were mainlyRASmutations, such as NRASor KRAS, and MEK alterations, which is a non-oncogene in cancer generally, as well as DNA repair, specifically theTP53mutation or deletion of this gene.

Patients who harbored any of these genomic alterations had a shorter time to progression to full-blown myeloma compared to others who did not have these mutations. For the first time, this shows that the biology of the disease matters. These were untreated patients, so we were able to track the natural history of progression of these patients to see the effect of each mutation or genomic alteration on how patients will behave later on in their disease course.

TARGETED ONCOLOGY: Do you have a hypothesis as to why this result was observed?

Bustoros:We know that the main primary events in MM are either the copy number alterations (CNAs), which means chromosomal gains or deletions, or the translocations which are present in 45% of patients. We found CNAs were most common and present in almost 87% of the patients with SMM. We think the first drivers were either CNAs or translocations, then these other markers I mentioned like theRASmutation, TP53mutations/deletions or later events that occurred at a certain time and gave the tumor cells a more proliferative capacity to grow more and start to propagate more symptoms.

That is our hypothesis because in the end, they were not present in all patients. They were present in almost just 40% of patients, meaning 60% of patients did not have these high-risk genomic features but they progressed at a much slower rate compared to the ones that had these mutations.

TARGETED ONCOLOGY: How could these findings inform current treatment decisions for patients?

Bustoros:Our findings inform current management and treatment approaches for SMM in multiple ways. We first constructed these 3 high-risk genomic features I mentioned and that we applied on our cohort to see if these genetic alterations would better identify and stratify patients with the current clinical model that just depends on the clinical markers like bone marrow infiltration or free light chain (FLC) ratio.

We found that patients who had any of the high-risk genomic features were having a shorter time to progression compared to the ones that were, for example, high-risk according to the clinical model only, which means this can improve on the current clinical models that we have and use in the clinic. This will give us a more precise and accurate identification of patients who will be at high-risk of progression.

We found the same thing in patients who are high-risk by the clinical model and intermediate-risk by the clinical model. Whoever in these groups had a mutation or any of the high-risk genomic features had a much faster time to progression compared to the ones from the same group that didn’t have these mutations.

TARGETED ONCOLOGY: How can SMM genomics improve the efficiency of risk stratification?

Bustoros:The genomic profiling can improve the SMM stratification by incorporating these panels that can now be used in the clinical setting. By finding these genes in bigger and bigger cohorts, we can know from the beginning when a patient presents with SMM that it can be part of the baseline workup. We can see if, for example, they have any of these high-risk genomic features, and then we can know from the beginning that this patient would have a different disease course compared to others who do not have these [high-risk features]. This is where the prediction happens because tumor markers like tumor burden, bone marrow infiltration, or FLC ratio are good and helpful in assessing the risk of progression in patients. However, if a patient presents with 50% bone marrow infiltration, no one would argue that this patient would progress fast, but maybe the thing we need to add is even if a patient presents with 20% or less bone marrow infiltration but have some of these other high-risk genomic features, then we can know from the beginning that this patient would have a high-risk of disease progression. If we are going to offer treatment, we have to treat them differently than others who do not have that.

TARGETED ONCOLOGY: How might genomic profiling improve our current methods of treating patients with SMM?

Bustoros:I showed the data on how we compared, by survival analysis, the time to progression in high-, intermediate-, and low-risk patients by the clinical model only and by the clinical model and the genomic model as well. We saw that the genomic model improved precision and accuracy of identifying high-risk patients, and any of the patients who had any of the high-risk genomic features like MEK alterations,RASmutations, or TP53mutations or deletions were having a significantly shorter time to progression in a variant or multi-variant analysis compared to patients who did not have these mutations.

TARGETED ONCOLOGY: Did any of these findings surprise you?

Bustoros:As I mentioned, we have CNAs in almost 87% of patients with SMM in our cohort. We did an analysis to see the significant arm level chromosomal deletions or gains, and also the whole deletions because when we are doing exome sequencing, we are seeing the DNA on a very high resolution compared to what we see the current iFISH test that we do in the clinic. We saw some novel copy number deletions or gains that we didn’t study in detail before. This is 1 of the things that we are now doing to see how these CNAs would impact the disease course and progression. We have also seen that the Abl signature, which is a pattern of mutations, was enriched in patients who progressed compared to patients who didn’t progress. This will give us more understandingofthe biology of the disease and how it starts from the beginning and progresses over time.

TARGETED ONCOLOGY: What are the next steps for this research?

Bustoros:We are very focused on translating this to the clinic as fast as we can. In the end, we want this to have an impact on our management for patients with SMM. We are planning some validation cohorts to expand our findings and validate these data more. We are also trying to analyze the gene expression profile of these patients based on RNA sequencing and compare it to their DNA mutations to see how it compares and what are the important pathways implicated in disease progression and also in the disease development. These are early-stage patients with MM, so we can get a lot of inside understanding of how disease occurs and progresses.

TARGETED ONCOLOGY: Is there anything else you would like to note on this research?

Bustoros: