Analysis of thousands of individual cells in multiple myeloma patients allows for a much more precise diagnosis — distinguishing asymptomatic, early-stage patients from those with full-blown disease — and may guide treatment choices toward a more personalized approach, a study shows.
The study, “Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma,” was published in Nature Medicine.
Multiple myeloma occurs when the cells that make antibodies — called plasma cells — start dividing out of control, eventually leading to disease. Although there have been significant improvements in treatment in recent years, many therapies still aren’t curative, and most patients relapse.
Researchers here hoped that, by gaining a clearer understanding of the exact changes that occur in cancerous plasma cells, compared with normal ones, specific patients can be better treated and diagnosed.
The team used a technique called single-cell RNA sequencing. As the name implies, this technique sequences the RNA of cells — the intermediate molecules that carry information from genes to produce proteins — which gives researchers clues about what genes are being activated.
Single-cell RNA sequencing applies this technology at the level of individual cells. So, rather than, for example, taking a piece of tumor and sequencing all the RNA in it — which can have many problems, such as the accidental inclusion of normal cells — this technique allows researchers to investigate cancer on a per-cell basis.
The researchers collected samples from 11 healthy controls and 29 patients with various stages of multiple myeloma, including asymptomatic early disease and minimal disease post-treatment.
By analyzing thousands of individual cells from the healthy controls, the researchers determined there is little variability in the global RNA sequences — also called the transcriptome — of plasma cells; that is, even though the cells are not identical, almost all of them share the same general program.
However, cancerous plasma cells were markedly different, and there was a lot of variability between patients and even between the cancerous cells within the same patient. Despite this, the researchers were able to group cells into different “clusters” based on the cancerous program they appeared to be using — for example, many cells had abnormal expression of the CCND1 gene, which is known to be a driver of disease in multiple myeloma.
This method could also detect very rare cancer cells in blood samples from patients with asymptomatic or residual disease. This suggests that this technique may help clinicians make early and accurate diagnoses of multiple myeloma. It also indicates that the disease might be monitored with simple blood draws, without the need for invasive bone marrow analysis.
“This study introduces [single cell RNA sequencing] as a key technology for precise molecular profiling of individuals with myeloma at various stages of the disease and facilitates the design of new and molecularly informed diagnosis and treatment strategies,” the researchers concluded.
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