PURPOSE Multiple myeloma (MM) is characterized by copy number abnormalities (CNAs), some of which influence patient outcomes and are sometimes observed only at relapse(s), suggesting their acquisition during tumor evolution. However, the presence of micro-subclones may be missed in bulk analyses. Here, we use single-cell genomics to determine how often these high-risk events are missed at diagnosis and selected at relapse. MATERIALS AND METHODS We analyzed 81 patients with plasma cell dyscrasias using single-cell CNA sequencing. Sixty-six patients were selected at diagnosis, nine at first relapse, and six in presymptomatic stages. A total of 956 newly diagnosed patients with MM and patients with first relapse MM have been identified retrospectively with required cytogenetic data to evaluate enrichment of CNA risk events and survival impact. RESULTS A total of 52,176 MM cells were analyzed. Seventy-four patients (91%) had 2-16 subclones. Among these patients, 28.7% had a subclone with high-risk features (del(17p), del(1p32), and 1q gain) at diagnosis. In a patient with a subclonal 1q gain at diagnosis, we analyzed the diagnosis, postinduction, and first relapse samples, which showed a rise of the high-risk 1q gain subclone (16%, 70%, and 92%, respectively). In our clinical database, we found that the 1q gain frequency increased from 30.2% at diagnosis to 43.6% at relapse (odds ratio, 1.78; 95% CI, 1.58 to 2.00). We subsequently performed survival analyses, which showed that the progression-free and overall survival curves were superimposable between patients who had the 1q gain from diagnosis and those who seemingly acquired it at relapse. This strongly suggests that many patients had 1q gains at diagnosis in microclones that were missed by bulk analyses. CONCLUSION These data suggest that identifying these scarce aggressive cells may necessitate more aggressive treatment as early as diagnosis to prevent them from becoming the dominant clone.
Multiple myeloma (MM) is a hematological malignancy characterized by the accumulation of tumor plasma cells (PCs) in the bone marrow (BM). Despite considerable advances in terms of treatment, patients’ prognosis is still very heterogeneous. Cytogenetics and minimal residual disease both have a major impact on prognosis. However, they do not explain all the heterogeneity seen in the outcomes. Their limitations are the result of the emergence of minor subclones missed at diagnosis, detected by sensible methods such as single-cell analysis, but also the non-exploration in the routine practice of the spatial heterogeneity between different clones according to the focal lesions. Moreover, biochemical parameters and cytogenetics do not reflect the whole complexity of MM. Gene expression is influenced by a tight collaboration between cytogenetic events and epigenetic regulation. The microenvironment also has an important impact on the development and the progression of the disease. Some of these determinants have been described as independent prognostic factors and could be used to more accurately predict patient prognosis and response to treatment.
Primary plasma cell leukemia (pPCL) is an aggressive form of multiple myeloma (MM) that has not benefited from recent therapeutic advances in the field. Because very rare and heterogeneous, it remains poorly understood at the molecular level. To address this issue, we performed DNA and RNA sequencing of sorted plasma cells from a large cohort of 90 newly diagnosed pPCL, and compared to MM. We observed that pPCL presents a specific genomic landscape with a high prevalence of t(11;14) (about half) and high-risk genomic features such as del(17p), gain 1q, del(1p32). In addition, pPCL displays a specific transcriptome when compared to MM. We then aimed at specifically characterize pPCL with t(11;14). We observed that this sub-entity displayed significantly fewer adverse cytogenetic abnormalities. This translated into better overall survival when compared to pPCL without t(11;14) (39.2 months vs 17.9 months, p=0.002). Finally, pPCL with t(11;14) displayed a specific transcriptome, including differential expression of BCL2 family members. This study is the largest series of patients with pPCL reported so far.
Cytogenetics abnormalities (CA) are known to be the preponderant prognostic factor in multiple myeloma (MM). Our team has recently developed a prognostic score based on 6 CA, where del(1p32) appears to be the second worst abnormality after del(17p). The aim of this study was to confirm the adverse impact of 1p32 deletion on newly-diagnosed multiple myeloma (NDMM) patients. Among 2551 NDMM patients, 11% were harboring del(1p32). Their overall survival (OS) was significantly inferior compared to patients without del(1p32) (median OS: 49 months vs. 124 months). Likewise, progression-free survival was significantly shorter. More importantly, biallelic del(1p32) conferred a dramatically poorer prognosis than a monoallelic del(1p32) (median OS: 25 months vs. 60 months). As expected, the OS of del(1p32) patients significantly decreased when this abnormality was associated with other high-risk CA (del(17p), t(4;14) or gain(1q)). In the multivariate analysis, del(1p32) appeared as a negative prognostic factor; after adjustment for age and treatment, the risk of progression was 1.3 times higher among patients harboring del(1p32), and the risk of death was 1.9 times higher. At the dawn of risk-adapted treatment strategies, we have confirmed the adverse impact of del(1p32) in MM and the relevance of its assessment at diagnosis.
Myeloma therapeutic strategies have been adapted to patients’ age and comorbidities for a long time. However, although cytogenetics and clinical presentations (plasmablastic cytology; extramedullary disease) are major prognostic factors, until recently, all patients received the same treatment whatever their initial risk. No strong evidence allows us to use a personalized treatment according to one cytogenetic abnormality in newly diagnosed myeloma. Retrospective studies showed a benefit of a double autologous transplant in high-risk cytogenetics according to the International Myeloma Working Group definition (t(4;14), t(14;16) or del(17p)). Moreover, this definition has to be updated since other independent abnormalities, namely gain 1q, del(1p32), and trisomies 5 or 21, as well as TP53 mutations, are also prognostic. Another very strong predictive tool is the response to treatment assessed by the evaluation of minimal residual disease (MRD). We are convinced that the time has come to use it to adapt the strategy to a dynamic risk. Many trials are ongoing to answer many questions: when and how should we adapt the therapy, its intensity and duration. Nevertheless, we also have to take into account the clinical outcome for one patient, especially adverse events affecting his or her quality of life and his or her preferences for continuous/fixed duration treatment.
In the era of personalized treatment in multiple myeloma, high-risk patients must be accurately defined. The International Myeloma Working Group recommends using the Revised International Staging System (R-ISS) to identify high-risk patients. The main purpose of our work was to explore the heterogeneity of outcome among R-ISS stage II patients assessing the impact of ISS, chromosomal abnormalities (CA) and LDH level in this subgroup. Data were issued from 1,343 newly diagnosed myeloma patients up to 65 years, enrolled in 3 clinical trials implemented by the Intergroupe Francophone du Myelome. All patients were eligible to an intensive treatment. Patients R-ISS stage II but ISS stage I had 1.6 times more risk of death than patients R-ISS stage I (adjusted HR 1.6; 95% CI, 1.1 to 2.2; P = .01) and patients R-ISS stage II but ISS stage III had a better overall survival than patients R-ISS stage III (adjusted HR 0.7; 95% CI, 0.4 to 0.9, P = .02). However, among patients classified in R-ISS II, ISS stage and CA (del(17p) and t(4;14)) were still relevant prognostic factors for death. Dividing R-ISS stage II into 3 subgroups: ISS I with standard risk CA, ISS II or III with standard risk CA and, high risk CA patients, median overall survivals were respectively not reached, 112 and 71 months (P < 0.001). In conclusion, stratification of patients in the R-ISS stage II group can be improved by taking into account CA and ISS. However, this does not improve predictive performance of survival models.
Background In the era of personalized treatment in multiple myeloma, high-risk (HR) patients must be defined accurately more than ever. The International Myeloma Working Group (IMWG) recommends to use the Revised International Staging System (R-ISS) to identify HR patients. This score combines ISS, abnormal serum LDH level and 3 high risk chromosomal abnormalities (CA): del(17p), t(4;14) and t(14;16). However, with the advent of new tools in genomics, assessing only 3 abnormalities seems to be limited. Moreover, LDH level is impacted by various medical conditions; its relevance in the score is questionable. Aims The main purpose of our work was to assess the R-ISS on a multi-center cohort of transplant-eligible patients (1180 patients). To our knowledge, this is the first large scale study in Europe. Methods Data were collected from NDMM patients enrolled in 3 clinical trials implemented by the Intergroupe Francophone du Myélome. All patients were eligible to an intensive treatment. The overall survival (OS) and progression-free survival (PFS) curves were estimated using the Kaplan-Meier method and compared using the stratified log-rank test. The hazard ratio (HR) for progression or death were estimated by a multivariate Cox regression analysis adjusted for age, sex and therapy. Discrimination was assessed by the Harrell's concordance index (C-index) which estimates the proportion of all pairs of patients in whom prediction and outcome are concordant and takes values from 0.5 (no discrimination) to 1.0 (perfect discrimination). Results Altogether, 1180 patients with MM were analysed. Median age of our cohort was 58 years. The majority of patients (78%) received an intensive treatment followed by an autologous stem-cell transplantation (ASCT). Median follow-up was 94 months for OS. Forty-three percent of patients had ISS stage I, 39% had ISS stage II and 18% had ISS stage III. In the multivariable Cox model, the risk of death was increased for ISS stage II versus I (HR, 1.8; P < 0.001), as well for R-ISS stage III versus I (HR, 2.1; P < 0.001). Thirty percent of patients had R-ISS stage I, 62% had R-ISS stage II and 8% had R-ISS stage III. In the multivariable Cox model, the risk of death was 1.8 times higher for R-ISS stage II versus I and 3.0 times higher for R-ISS stage III versus I. Then we compared patients between their couple ISS/R-ISS. Thirty-one percent of the patients from ISS I were upgraded in R-ISS II; 55% of ISS III patients were reclassified in R-ISS II. Patients from the ISS I/R-ISS II couple didn't have a higher risk of progression (HR, 1.02; P = 0.893) or death (HR, 1.36; P = 0.115) than patients in the ISS I/R-ISS I subgroup. We also focused on the patients classified in R-ISS stage II (736 patients). We compared several subgroups: high risk CA (defined by R-ISS) versus standard risk, del(17p) vs. no del(17p), t(4;14) vs. no t(4;14) and high LDH vs. normal LDH. In the multivariable Cox model for OS, the risk of death was increased for patients with del(17p) (HR, 2.14; P < 0.001), t(4;14) (HR, 2.06; P < 0.001) and any of the high risk CA (HR, 2.15; P < 0.001). Conversely, high LDH didn't have an impact neither on PFS (HR, 1.10; P = 0.333) nor OS (HR, 1.09; P = 0.540). Finally, we assessed the performance of the different prognostic models for discriminating patients who progressed from those who didn't (PFS) and patients who died from those who survived (OS) with the Harrell's C-index. The C-index for the R-ISS was the same than the ISS one for both PFS (0.56) and OS (0.61). R-ISS didn't give an additional prognostic value to the ISS. For every models, C-index were the same with or without LDH level; a LDH level upper than the upper limit of normal range didn't bring predictive gain on PFS or OS. C-index was better when we assessed each criteria of the R-ISS independently; this system presents the advantage of considering different prognostic weights and also different associations. Conclusion Our study confirms a significant difference for both PFS and OS between R-ISS stages I, II and III, but importantly, we show that the discriminatory ability of the R-ISS, assessed by the Harrell C-index, is equivalent to the ISS. Moreover, patients in stage R-ISS II have different prognosis depending on their cytogenetic while LDH level doesn't give any difference. Combining ISS, high risk CA and LDH level in only 3 categories induces a loss in the prognosis assessment. A model which assesses all the parameters in an independent way would be better. Figure 1 Disclosures Perrot: Amgen, BMS/Celgene, Janssen, Sanofi, Takeda: Consultancy, Honoraria, Research Funding.
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