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. 2022 Jul 12;10(7):1674.
doi: 10.3390/biomedicines10071674.

Tracking Clonal Evolution of Multiple Myeloma Using Targeted Next-Generation DNA Sequencing

Affiliations

Tracking Clonal Evolution of Multiple Myeloma Using Targeted Next-Generation DNA Sequencing

Aleksander Salomon-Perzyński et al. Biomedicines. .

Abstract

Clonal evolution drives treatment failure in multiple myeloma (MM). Here, we used a custom 372-gene panel to track genetic changes occurring during MM progression at different stages of the disease. A tumor-only targeted next-generation DNA sequencing was performed on 69 samples sequentially collected from 30 MM patients. The MAPK/ERK pathway was mostly affected with KRAS mutated in 47% of patients. Acquisition and loss of mutations were observed in 63% and 37% of patients, respectively. Four different patterns of mutation evolution were found: branching-, mutation acquisition-, mutation loss- and a stable mutational pathway. Better response to anti-myeloma therapy was more frequently observed in patients who followed the mutation loss-compared to the mutation acquisition pathway. More than two-thirds of patients had druggable genes mutated (including cases of heavily pre-treated disease). Only 7% of patients had a stable copy number variants profile. Consequently, a redistribution in stages according to R-ISS between the first and paired samples (R-ISS″) was seen. The higher the R-ISS″, the higher the risk of MM progression and death. We provided new insights into the genetics of MM evolution, especially in heavily pre-treated patients. Additionally, we confirmed that redefining R-ISS at MM relapse is of high clinical value.

Keywords: clonal evolution; multiple myeloma; next-generation sequencing.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The functional categorization of all mutant genes.
Figure 2
Figure 2
The proportions of multiple myeloma patients bearing mutations in genes involved in a particular cellular process.
Figure 3
Figure 3
Evolution of single-nucleotide variants during multiple myeloma progression based on the next-generation sequencing data from the first and paired samples. Description: A—patients who presented a branching evolution with mutations lost and gained during multiple myeloma progression; B—patients who only acquired new mutations during multiple myeloma progression; C—patients who only lost mutations during multiple myeloma progression; D—patients with stable mutations during multiple myeloma progression.
Figure 4
Figure 4
Evolution of copy number variants during multiple myeloma progression based on the next-generation sequencing data from the first and paired samples. Description: A—patients who presented a branching evolution of single-nucleotide variants with mutations lost and gained during multiple myeloma progression; B—patients who only acquired new single-nucleotide variants during multiple myeloma progression; C—patients who only lost single-nucleotide variants during multiple myeloma progression; D—patients with a stable profile of single-nucleotide variants during multiple myeloma progression.
Figure 5
Figure 5
Kaplan–Meier survival curves for (a) PFS, (b) OS after the paired sample collection (OS″) and (c) OS after the first sample collection (OS′) according to the R-ISS″ (assessed at the time of the paired sample collection). The comparison of survival groups was assessed by log rank test (p values).
Figure 5
Figure 5
Kaplan–Meier survival curves for (a) PFS, (b) OS after the paired sample collection (OS″) and (c) OS after the first sample collection (OS′) according to the R-ISS″ (assessed at the time of the paired sample collection). The comparison of survival groups was assessed by log rank test (p values).

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