P860: circulating multiple myeloma cells (cmmcs) as prognostic factor and minimal residual disease marker in mm and smouldering mm patients

Ilaria Vigliotta, Vincenza Solli,Silvia Armuzzi, Ajsi Kanapari, Arlo Poletti,Barbara Taurisano, Ignazia Pistis,Enrica Borsi,Gaia Mazzocchetti,Marina Martello,Ilaria Rizzello,Lucia Pantani,Giulia Marzocchi,Nicoletta Testoni,Elena Zamagni, Mario Terracciano, Valentina Del Monaco, Marianna Garonzi, Nicolò Manaresi,Michèle Cavo,Carolina Terragna

HemaSphere(2023)

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摘要
Topic: 13. Myeloma and other monoclonal gammopathies - Biology & Translational Research Background: Bone marrow (BM) aspirate is considered the gold standard source of information for Multiple Myeloma (MM) diagnosis, prognosis and minimal residual disease (MRD) monitoring; however, liquid biopsy (LB) has emerged as a promising non-invasive alternative, providing also information on spatial and temporal heterogeneity. Despite the growing interest in LB, to date there is still no validated standard method for its employment in MM. Aims: The aim of this study was to analyze circulating MM cells (CMMCs) isolated from peripheral blood (PB) of pts affected by MM and Smouldering MM (SMM), using the CELLSEARCH system® (Menarini Silicon Biosystem), to correlate CMMCs count with pts’ prognosis and to assess the CMMCs dynamics throughout the disease course, to evaluate whether variations of the CMMCs count might predict disease progression. Methods: Overall, the study included 55 MM and 7 SMM pts, treated with conventional regimens in the daily clinical practice. For each pt, both BM aspirate and PB sample were analysed at diagnosis. For a selected set of pts (59), PB samples were also collected every 3 months (ms), to monitor disease progression. The pts’ median follow-up was 24 ms. In 4 pts, single cell (sc) genomic analysis was also performed, with Ampli1™ WGA and LowPass on CMMCs isolated by DEPArray®, to compare Copy Number Alterations (CNAs) profile of CMMCs with BM plasma cells (PC). Results: To date, 23 PB samples (16 from MM and 7 from SMM pts) have been analysed at diagnosis and 219 samples at subsequent time-points. The median count of CMMCs at diagnosis was 343.5 (range 1 – 39940) and 102 (range 2 – 2463) for MM and SMM pts, respectively. Correlated with the risk stratification scores (ISS and R-ISS), high CMMC levels were detected in high-risk pts (pvalue=0.083) and in pts showing higher BM-PCs amount (pvalue=0.034). Throughout the first 6 ms of monitoring, 53 samples were analysed and a median of 2 CMMCs were enumerated (range 0-5432); on the contrary, in the following 18 ms the analysis of 82 samples highlighted that no CMMCs could be detected in most pts (range 0-897); finally, between 18 and 38 ms of treatment, a median of 1 CMMC was measured in 84 analyzed samples (range 0-59). The role of CMMCs as marker of disease dynamics during MM pts’ treatment was supported by the correlation between the median CMMCs count evaluated in the first 6 ms, 6-18 ms, and 18-38 ms, and MRD measurements performed by Next Generation Sequencing and serum M component concentration. Finally, to study the CMMCs genomic landscape, 4 MM pts were analyzed by sc Ultra Low Pass-Whole Genome Sequencing. CMMCs CNAs profile mirrored the BM-CD138+ one, suggesting that CMMCs genomic architecture might resume the BM clone’s characteristics. Notably, in 1 case, the highly heterogeneous BM CNAs architecture was unraveled only by the sc CMMCs analysis, by returning a clear picture of the BM PCs’ sub-clonal composition. In 3 out of 4 patients, CMMCs with main-ploidy at 4 suggested whole-genome doubling events. Summary/Conclusion: Although the analyzed pts’ cohort was small, it was possible to identify correlation between CMMCs levels and β2microglobulin and M component concentrations, BM disease burden, PCs subtype, CNA profiles and other risk stratification factors, stressing their potential role both as prognostic and as predictive marker in MM and SMM pts. Moreover, CMMCs showed a dynamic comparable with MRD measurements and M component levels during post-treatment monitoring and SMM progression, confirming their potential role as minimal disease biomarkers. Thanks to: AIRC19-IG22059, BolognAILONLUS, RC 000599/22 Keywords: Multiple myeloma, liquid biopsy, Smoldering, Plasma cells
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circulating multiple myeloma cells,multiple myeloma,prognostic factor,residual disease marker
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