Session: 651. Myeloma: Biology and Pathophysiology, excluding Therapy: Poster III
Hematology Disease Topics & Pathways:
multiple myeloma, Diseases, biopsy, Biological Processes, Technology and Procedures, Plasma Cell Disorders, Lymphoid Malignancies, genomics, genetic profiling, Clinically relevant, molecular testing, NGS, WGS
Multiple Myeloma (MM) is a plasma cell (PC) disorder characterized by the presence of multiple lytic lesions at the time of diagnosis. Bone marrow (BM) aspirates are commonly used to define the characteristics and the size of the myeloma clone, a practice limited by constraints, such as sampling frequency and a partial representation of the entire tumour bulk. Recently, cell-free DNA (cfDNA) has been proven to resume the heterogeneity of spatially distributed clones. However, the potential of cfDNA to track the evolutionary dynamics and the heterogeneity of MM, possibly anticipating the emergence of therapy resistant residual cells, remains to be confirmed.
To assess the potential of cfDNA analysis at diagnosis and during follow-up in mimicking the genomic background of a single-site BM aspirate and to define the integration of this approach with imaging to evaluate the extent of bone involvement.
Patients and Methods
A total of 58 patients (pts) were screened at baseline and during follow-up with 18F-FDG PET/CT and NMR, and molecularly assessed by Ultra Low Pass-Whole Genome Sequencing (ULP-WGS), including: 2 SMM, 58 Newly Diagnosed MM (NDMM), and 18 follow-up time-points (i.e. + 3 months [m] post-induction therapy). For each pts, ULP-WGS was used to characterize both the neoplastic PC clone from BM (gDNA) and the cfDNA from peripheral blood. BM CD138+ PCs were isolated with CD138 microbeads. A range of 1 to 10 ng of both gDNA and cfDNA was used to obtain libraries, which were sequenced in an Illumina NextSeq 500. Data were analysed by ichorCNA (Adalsteisson et al., 2017) and Clonality R packages (Ostrovnaya et al., 2011).
The ULP-WGS was feasible in all patients, both in gDNA and cfDNA, with a median coverage of 0,5X (range 0,1-2,3X). By employing the probabilistic ichorCNA algorithm, we determined the tumour fraction (TF) of each sample. As expected, the cfDNA TF at diagnosis was significantly lower as compared to gDNA TF [median (M) TF: 3.0%vs.74.4%, respectively]. Nevertheless, high cfDNA TF levels (29/58 pts = 50%, cfDNA TF values range: 3.0-40.6%) correlates with high gDNA TF levels (M gDNA TF: 84%, range: 5.9-95.2%). This observation was further confirmed by a significant correlation between cfDNA TF and the BM plasma cells clone, as evaluated by flow cytometry, highlighting a linearity throughout disease dynamics[from SMM to MM to +3m post-induction (cfDNA TF vs. % CD138/CD38 BM cells: 1.5 vs 1.0; 3.0 vs. 2.3; 1.2 vs. <.01; p: 0.008)], possibly reflecting the BM tumor burden fluctuations.
Imaging data demonstrated that pts with high cfDNA TF featured more frequently evidence of extramedullary disease (EMD), had a higher number of PET lesions and a more active tumour metabolism, as compared to pts with low TF (EMD 5/29=17% vs. 1/29=3.4%; M n. PET lesions: 8 vs. 2; SUVmax: 12.9 vs. 3.9). Similarly, bone damage, as detected by NMR, was more evident in pts with high cfDNA TF (M n. focal lesions: 6 vs. 1). More interestingly, after 3 cycles of induction therapy, imaging and cfDNA TF levels were concordant; indeed, in those cases where an FDG activity and few focal lesions still persist (4/10=40%: SUVmax 5.8; >2 PET lesions), cfDNA TF was still detectable as well (>1 TF), thus corroborating a possible role for cfDNA in the disease monitoring.
Finally, genomic profiles comparison between cfDNA and BM showed an overall concordance of the copy number alterations (CNAs) profile in most patients (19/22; 86.4%) (fig.1). However, three patients (3/22; 13.6%) displayed a different genomic profile in cfDNA, as compared to BM: in two of them (gcf19, gcf29) genomic profiles were almost superimposable, even though with specific CNAs acquisitions and/or losses in cfDNA (e.g. del1p). Conversely, a third pts (gcf4), cfDNA showed a private CNAs profile, not mirroring the BM clone. Clonality algorithm further confirmed the observed discrepancies between gDNA and cfDNA, by assigning a probabilistic index to the two distinct genomic profiles (likelihood ratio:>5x10e3).
cfDNA can resume the genomic complexity of BM clones. Although only few cases showed genomic evidence of spatial heterogeneity, in pts with high cfDNA TF, imaging data overall suggested a propensity to a metastatic spread of the disease. Future studies will be addressed to exploit the use of cfDNA in disease monitoring, possibly identifying an ideal time-point of residual disease detection.
Disclosures: Zamagni: Celgene Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Speakers Bureau; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Speakers Bureau; Takeda: Honoraria, Other: Travel, Accommodations, Expenses, Speakers Bureau; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Speakers Bureau. Tacchetti: Janssen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Amgen: Honoraria; Takeda: Honoraria; AbbVie: Honoraria; Oncopeptides: Honoraria. Cavo: Jannsen, BMS, Celgene, Sanofi, GlaxoSmithKline, Takeda, Amgen, Oncopeptides, AbbVie, Karyopharm, Adaptive: Consultancy, Honoraria.
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