PURPOSEThe existence of patients with multiple myeloma (MM) and light-chain (AL) amyloidosis who present with a monoclonal gammopathy of undetermined significance (MGUS)-like phenotype has been hypothesized, but methods to identify this subgroup are not standardized and its clinical significance is not properly validated.PATIENTS AND METHODSAn algorithm to identify patients having MGUS-like phenotype was developed on the basis of the percentages of total bone marrow (BM) plasma cells (PC) and of clonal PC within the BM PC compartment, determined at diagnosis using flow cytometry in 548 patients with MGUS and 2,011 patients with active MM. The clinical significance of the algorithm was tested and validated in 488 patients with smoldering MM, 3,870 patients with active MM and 211 patients with AL amyloidosis.RESULTSPatients with smoldering MM with MGUS-like phenotype showed significantly lower rates of disease progression (4.5% and 0% at 2 years in two independent series). There were no statistically significant differences in time to progression between treatment versus observation in these patients. In active newly diagnosed MM, MGUS-like phenotype retained independent prognostic value in multivariate analyses of progression-free survival (PFS; hazard ratio [HR], 0.49; P = .001) and overall survival (OS; HR, 0.56; P = .039), together with International Staging System, lactate dehydrogenase, cytogenetic risk, transplant eligibility, and complete remission status. Transplant-eligible patients with active MM with MGUS-like phenotype showed PFS and OS rates at 5 years of 79% and 96%, respectively. In this subgroup, there were no differences in PFS and OS according to complete remission and measurable residual disease status. Application of the algorithm in two independent series of patients with AL predicted for different survival.CONCLUSIONWe developed an open-access algorithm for the identification of MGUS-like patients with distinct clinical outcomes. This phenotypic classification could become part of the diagnostic workup of MM and AL amyloidosis.

Clonal evolution in acute myeloid leukemia (AML) originates long before diagnosis and is a dynamic process that may affect survival. However, it remains uninvestigated during routine diagnostic workups. We hypothesized that the mutational status of bone marrow dysplastic cells and leukemic blasts, analyzed at the onset of AML using integrated multidimensional flow cytometry (MFC) immunophenotyping and fluorescence-activated cell sorting (FACS) with next-generation sequencing (NGS), could reconstruct leukemogenesis. Dysplastic cells were detected by MFC in 285 of 348 (82%) newly diagnosed patients with AML. Presence of dysplasia according to MFC and World Health Organization criteria had no prognostic value in older adults. NGS of dysplastic cells and blasts isolated at diagnosis identified 3 evolutionary patterns: stable (n= 12 of 21), branching (n= 4 of 21), and clonal evolution (n= 5 of 21). In patients achieving complete response (CR), integrated MFC and FACS with NGS showed persistent measurable residual disease (MRD) in phenotypically normal cell types, as well as the acquisition of genetic traits associated with treatment resistance. Furthermore, whole-exome sequencing of dysplastic and leukemic cells at diagnosis and of MRD uncovered different clonal involvement in dysplastic myelo-erythropoiesis, leukemic transformation, and chemoresistance. Altogether, we showed that it is possible to reconstruct leukemogenesis in 80% of patients with newly diagnosed AML, using techniques other than single-cell multiomics.

PURPOSE Patients with multiple myeloma (MM) may show patchy bone marrow (BM) infiltration and extramedullary disease. Notwithstanding, quantification of plasma cells (PCs) continues to be performed in BM since the clinical translation of circulating tumor cells (CTCs) remains undefined. PATIENTS AND METHODS CTCs were measured in peripheral blood (PB) of 374 patients with newly diagnosed MM enrolled in the GEM2012MENOS65 and GEM2014MAIN trials. Treatment included bortezomib, lenalidomide, and dexamethasone induction followed by autologous transplant, consolidation, and maintenance. Next-generation flow cytometry was used to evaluate CTCs in PB at diagnosis and measurable residual disease (MRD) in BM throughout treatment. RESULTS CTCs were detected in 92% (344 of 374) of patients with newly diagnosed MM. The correlation between the percentages of CTCs and BM PCs was modest. Increasing logarithmic percentages of CTCs were associated with inferior progression-free survival (PFS). A cutoff of 0.01% CTCs showed an independent prognostic value (hazard ratio: 2.02; 95% CI, 1.3 to 3.1; P = .001) in multivariable PFS analysis including the International Staging System, lactate dehydrogenase levels, and cytogenetics. The combination of the four prognostic factors significantly improved risk stratification. Outcomes according to the percentage of CTCs and depth of response to treatment showed that patients with undetectable CTCs had exceptional PFS regardless of complete remission and MRD status. In all other cases with detectable CTCs, only achieving MRD negativity (and not complete remission) demonstrated a statistically significant increase in PFS. CONCLUSION Evaluation of CTCs in PB outperformed quantification of BM PCs. The detection of >= 0.01% CTCs could be a new risk factor in novel staging systems for patients with transplant-eligible MM.

Reproducible expert-independent flow-cytometric criteria for the differential diagnoses between mature B-cell neoplasms are lacking. We developed an algorithm-driven classification for these lymphomas by flow cytometry and compared it to the WHO gold standard diagnosis. Overall, 662 samples from 662 patients representing 9 disease categories were analyzed at 9 laboratories using the previously published EuroFlow 5-tube-8-color B-cell chronic lymphoproliferative disease antibody panel. Expression levels of all 26 markers from the panel were plotted by B-cell entity to construct a univariate, fully standardized diagnostic reference library. For multivariate data analysis, we subsequently used canonical correlation analysis of 176 training cases to project the multidimensional space of all 26 immunophenotypic parameters into 36 2-dimensional plots for each possible pairwise differential diagnosis. Diagnostic boundaries were fitted according to the distribution of the immunophenotypes of a given differential diagnosis. A diagnostic algorithm based on these projections was developed and subsequently validated using 486 independent cases. Negative predictive values exceeding 92.1% were observed for all disease categories except for follicular lymphoma. Particularly high positive predictive values were returned in chronic lymphocytic leukemia (99.1%), hairy cell leukemia (97.2%), follicular lymphoma (97.2%), and mantle cell lymphoma (95.4%). Burkitt and CD101 diffuse large B-cell lymphomas were difficult to distinguish by the algorithm. A similar ambiguity was observed between marginal zone, lymphoplasmacytic, and CD102 diffuse large B-cell lymphomas. The specificity of the approach exceeded 98% for all entities. The univariate immunophenotypic library and the multivariate expert-independent diagnostic algorithm might contribute to increased reproducibility of future diagnostics in mature B-cell neoplasms.

Large-scale immune monitoring is becoming routinely used in clinical trials to identify determinants of treatment responsiveness, particularly to immunotherapies. Flow cytometry remains one of the most versatile and high throughput approaches for single cell analysis; however, manual interpretation of multidimensional data poses a challenge when attempting to capture full cellular diversity and provide reproducible results. We present FlowCT, a semi-automated workspace empowered to analyze large data sets. It includes pre-processing, normalization, multiple dimensionality reduction techniques, automated clustering, and predictive modeling tools. As a proof of concept, we used FlowCT to compare the T-cell compartment in bone marrow (BM) with peripheral blood (PB) from patients with smoldering multiple myeloma (SMM), identify minimally invasive immune biomarkers of progression from smoldering to active MM, define prognostic T-cell subsets in the BM of patients with active MM after treatment intensification, and assess the longitudinal effect of maintenance therapy in BM T cells. A total of 354 samples were analyzed and immune signatures predictive of malignant transformation were identified in 150 patients with SMM (hazard ratio [HR], 1.7; P < .001). We also determined progression-free survival (HR, 4.09; P < .0001) and overall survival (HR, 3.12; P 5 .047) in 100 patients with active MM. New data also emerged about stem cell memory T cells, the concordance between immune profiles in BM and PB, and the immunomodulatory effect of maintenance therapy. FlowCT is a new open-source computational approach that can be readily implemented by research laboratories to perform quality control, analyze high-dimensional data, unveil cellular diversity, and objectively identify biomarkers in large immune monitoring studies. These trials were registered at www. clinicaltrials.gov as #NCT01916252 and #NCT02406144.

Simple Summary Flow cytometry allows detailed characterization of large numbers of cells and plays an important role in the diagnosis of acute myeloid leukemia. To facilitate analysis of flowcytometric data, reference databases of normal bone marrow samples and samples from acute myeloid leukemia patients, together with new software tools, are required. We here report on the building of a large database of acute myeloid leukemia patients (n = 1142) and 22 normal samples. We report on the quality assessment procedure used and its validation, discuss potential pitfalls, and provide possible solutions for avoiding such flaws in the construction of other databases. Our data show that obtaining and collecting reproducible flow cytometric data over time and across centers is feasible, but also that strict quality assessment remains crucial, even when standardized protocols for staining and instrument settings are being used in a multicenter setting. Flowcytometric analysis allows for detailed identification and characterization of large numbers of cells in blood, bone marrow, and other body fluids and tissue samples and therefore contributes to the diagnostics of hematological malignancies. Novel data analysis tools allow for multidimensional analysis and comparison of patient samples with reference databases of normal, reactive, and/or leukemia/lymphoma patient samples. Building such reference databases requires strict quality assessment (QA) procedures. Here, we compiled a datase

Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB,n = 41) and bone marrow (BM;n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r(2) > 0.95 for all cell types in PB andr(2) > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool).

Simple Summary B-cell regeneration during therapy has been associated with the outcome of multiple myeloma (MM) patients. However, the effects of therapy and hemodilution in bone marrow (BM) B-cell recovery have not been systematically evaluated. Here, we show that hemodilution is present in a significant fraction of MM BM samples, leading to lower total B-cell, B-cell precursor (BCP), and normal plasma cell (nPC) counts. Among MM BM samples, decreased percentages (vs. healthy donors) of BCP, transitional/naive B-cell (TBC/NBC) and nPC populations were observed at diagnosis. BM BCP, but not TBC/NBC, increased after induction therapy. At day+100 post-autolo-gous stem cell transplantation, a greater increase in BCP with recovered TBC/NBC numbers but persistently low memory B-cell and nPC counts were found. At the end of therapy, complete response (CR) BM samples showed higher CD19(-) nPC counts vs. non-CR specimens with no clear association between BM B-cell regeneration profiles and patient outcomes. B-cell regeneration during therapy has been considered as a strong prognostic factor in multiple myeloma (MM). However, the effects of therapy and hemodilution in bone marrow (BM) B-cell recovery have not been systematically evaluated during follow-up. MM (n = 177) and adult (>= 50y) healthy donor (HD; n = 14) BM samples were studied by next-generation flow (NGF) to simultaneously assess measurable residual disease (MRD) and residual normal B-cell populations. BM hemodilution was detected in 41 out of 177 (23%) patient samples, leading to lower total B-cell, B-cell precursor (BCP) and normal plasma cell (nPC) counts. Among MM BM, decreased percentages (vs. HD) of BCP, transitional/naive B-cell (TBC/NBC) and nPC populations were observed at diagnosis. BM BCP increased after induction therapy, whereas TBC/NBC counts remained abnormally low. At day+100 postautologous stem cell transplantation, a greater increase in BCP with recovered TBC/NBC cell numbers but persistently low memory B-cell and nPC counts were found. At the end of therapy, complete response (CR) BM samples showed higher CD19(-) nPC counts vs. non-CR specimens. MRD positivity was associated with higher BCP and nPC percentages. Hemodilution showed a negative impact on BM B-cell distribution. Different BM B-cell regeneration profiles are present in MM at diagnosis and after therapy with no significant association with patient outcome.

Patients with multiple myeloma (MM) carrying high-risk cytogenetic abnormalities (CA) have inferior outcome despite achieving similar complete response (CR) rates when compared to cases with standard-risk CA. This questions the legitimacy of CR as treatment endpoint for high-risk MM, and represents a biological conundrum regarding the nature of tumor reservoirs persisting after therapy in patients with standard- and high-risk CA. Here, we used next-generation flow (NGF) to evaluate measurable residual disease (MRD) in MM patients with standard- (N=300) vs high-risk CA (N=90) enrolled in the PETHEMA/GEM2012MENOS65 trial (NCT01916252), and to identify mechanisms determining MRD resistance in both patient subgroups (N=40). The 36-month progression-free and overall survival rates were higher than 90% in patients with undetectable MRD, with no significant differences (P¿0.202) between cases having standard- vs high-risk CA. Persistent MRD resulted in median progression-free survival of approximately three and two years in patients with standard- and high-risk CA, respectively (P<0.001). Further use of NGF to isolate MRD followed by whole-exome sequencing of paired diagnostic and MRD tumor cells, revealed greater clonal selection in patients with standard-risk CA, higher genomic instability with acquisition of new mutations in high-risk MM, and no unifying lost or acquired genetic abnormalities driving MRD resistance. Conversely, RNA sequencing of diagnostic and MRD tumor cells uncovered the selection of MRD clones with singular transcriptional programs and ROS-mediated MRD resistance in high-risk MM. Our study supports undetectable MRD as treatment endpoint for MM patients with high-risk CA and proposes characterizing MRD clones to understand and overcome MRD resistance.

Here, we describe the detailed protocol for minimal residual disease (MRD) assessment as well as circulating tumor cell (CTC) detection in patients with plasma cell disorders using the next-generation flow (NGF) method developed by EuroFlow. This includes the previous setup of flow cytometers, preparation and staining of samples, cell acquisition, quality control of instruments, methods and samples, as well as data interpretation to monitor MRD and CTCs with great sensitivity. It should be noted that the NGF method fully described below can be equally applied to monitor MRD in patients with systemic light-chain amyloidosis and to detect occult bone marrow involvement in patients with solitary plasmocytoma.