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.

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.

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.

Meningiomas are the most common primary tumors of the central nervous system. Based on the 2021 WHO classification, they are classified into three grades reflecting recurrence risk and aggressiveness. However, the WHO’s histopathological criteria defining these grades are somewhat subjective. Together with reliable immunohistochemical proliferation indices, other molecular markers such as those studied with genome-wide epigenetics promise to revamp the current prognostic classification. In this study, 48 meningiomas of various grades were randomly included and explored for DNA methylation with the Infinium MethylationEPIC microarray over 850k CpG sites. We conducted differential and correlative analyses on grade and several proliferation indices and markers, such as mitotic index and Ki-67 or MCM6 immunohistochemistry. We also set up Cox proportional hazard models for extensive associations between CpG methylation and survival. We identified loci highly correlated with cell growth and a targeted methylation signature of regulatory regions persistently associated with proliferation, grade, and survival. Candidate genes under the control of these regions include SMC4, ESRRG, PAX6, DOK7, VAV2, OTX1, and PCDHA-PCDHB-PCDHG, i.e., the protocadherin gene clusters. This study highlights the crucial role played by epigenetic mechanisms in shaping dysregulated cellular proliferation and provides potential biomarkers bearing prognostic and therapeutic value for the clinical management of meningioma.

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.