Search

Background: Previous reports have suggested that a higher bone marrow plasma-cell percentage (BMPC%) is associated with worse outcomes. However, it is unknown whether BMPC% is an independent predictor because genetic information was not available at that time. Currently the impact of BMPC% at diagnosis of multiple myeloma (MM) is not well described., Patients and Methods: We evaluated the prognostic impact of BMPC% ≥ 60% versus < 60% in 1426 newly diagnosed MM patients. All patients had an estimation of their BMPC% at diagnosis, and the highest percentage was used. Progression-free survival (PFS) and overall survival (OS) analyses were performed by the Kaplan-Meier method. Univariate and multivariate analyses for PFS and OS using the Cox proportional hazards model were performed for age, Revised International Staging System (R-ISS) score, creatinine level, and BMPC%., Results: BMPC% ≥ 60% was found in 562 patients (39%), and the median PFS was shorter for these patients compared to BMPC% < 60% (22.6 vs. 32.1 months; P < .0001). Also, for OS, the median was shorter for the higher BMPC% group (53.4 vs. 75.4 months; P < .0001). On the multivariate analysis for PFS, age ≥ 65 years (hazard ratio [HR], 1.46; P < .0001), R-ISS (1-2 vs. 3) (HR, 0.49; P < .0001), and BMPC% ≥ 60% (HR, 1.23; P = .015) were predictive. On the multivariate analysis for OS, age ≥ 65 years (HR, 2.23; P < .001), R-ISS (1-2 vs. 3) (HR, 0.41; P < .0001), and BMPC% ≥ 60% (HR, 1.24; P = .02) were also predictive., Conclusion: BMPC% ≥ 60% at diagnosis is predictive for PFS and OS, even in a multivariate analysis that included known prognostic factors for MM., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Oncogenic drivers of progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) such as c-MYC have downstream effects on intracellular metabolic pathways of clonal plasma cells (PCs). Thus, extracellular environments such as the bone marrow (BM) plasma likely have unique metabolite profiles that differ from patients with MGUS compared to MM. This study utilized an untargeted metabolite and targeted complex lipid profiling of BM plasma to identify significant differences in the relative metabolite levels between patients with MGUS and MM from an exploratory cohort. This was followed by verification of some of the metabolite differences of interest by targeted quantification of the metabolites using isotopic internal standards in the exploratory cohort as well as an independent validation cohort. Significant differences were noted in the amino acid profiles such as decreased branch chain amino acids (BCAAs) and increased catabolism of tryptophan to the active kynurenine metabolite 3-hydroxy-kynurenine between patients with MGUS and MM. A decrease in the total levels of complex lipids such as phosphatidylethanolamines (PE), lactosylceramides (LCER) and phosphatidylinositols (PI) were also detected in the BM plasma samples from MM compared to MGUS patients. Thus, metabolite and complex lipid profiling of the BM plasma identifies differences in levels of metabolites and lipids between patients with MGUS and MM. This may provide insight into the possible differences of the intracellular metabolic pathways of their clonal PCs.

We conducted a retrospective review of multiple myeloma (MM), smoldering multiple myeloma (SMM), and monoclonal gammopathy of undetermined significance (MGUS) patients seen at Mayo Clinic to determine whether a bone marrow biopsy (BM) is necessary in all patients diagnosed with a monoclonal protein. A total of 2254 MM, 397 SMM, and 5836 MGUS patients were included in the study. A total of 29 (1.3%) MM patients "without CRAB/FLC" were identified where BM or advanced imaging was critical for diagnosis, 8 (0.3% MM cohort) of whom were diagnosed with MM solely on BM findings (plasma cells > 60%). Without BM or advanced imaging none of these patients would be classified low-risk MGUS. A total of 314 (79%) MGUS-like SMM patients were identified where classification of SMM was based on BM findings. Without BM 97 would be classified as low/low-intermediate-risk MGUS and 151 intermediate or high-risk MGUS; 66 had missing information precluding classification. Only three (<1% SMM cohort) were low-risk MGUS without abnormalities in hemoglobin, calcium, and renal function. In patients presenting with low-risk MGUS and normal hemoglobin, calcium, and renal function, the risk of missing a diagnosis of SMM and MM by omitting BM is <1%. BM should be deferred in these patients in preference to clinical and laboratory monitoring.

Our prior studies identified the prognostic significance of quantifying cPCs by multiparametric flow cytometry (MFC) in newly diagnosed multiple myeloma (NDMM) patients. We evaluated if a similar quantification of cPCs could add prognostic value to the current R-ISS classification of 556 consecutive NDMM patients seen at the Mayo Clinic, Rochester from 2009 to 2017. Those patients that had ≥5 cPCs/μL and either R-ISS stage I or stage II disease were re-classified as R-ISS IIB stage for the purposes of this study. The median time to next therapy (TTNT) and overall survival (OS) for patients with ≥5 cPCs/μL at diagnosis was as follows: R-ISS I (N = 110) - 40 months and not reached; R-ISS II (N = 69) - 30 and 72 months; R-ISS IIB (N = 96) - 21 and 45 months and R-ISS III (N = 281) - 20 and 47 months respectively. Finally, ≥ 5 cPCs/μL retained its adverse prognostic significance in a multivariable model for TTNT and OS. Hence, quantifying cPCs by MFC can potentially enhance the R-ISS classification of a subset of NDMM patients with stage I and II disease by identifying those patients with a worse than expected survival outcome., (© 2019 Wiley Periodicals, Inc.)

Achievement of a complete response has been associated with improved outcomes in patients with multiple myeloma. Recently, increasing application of minimal residual disease (MRD) assessment has shown that MRD negativity is a powerful prognostic factor for survival outcomes. We wanted to examine the impact of the polyclonal plasma cell (pPC) compartment among patients in complete response (CR) but are MRD positive. This is a retrospective cohort study where 460 myeloma patients were identified who met criteria for CR and had multicolor flow cytometry performed on the bone marrow (BM). Monoclonal and pPCs were estimated during MRD testing. Final outcomes including overall survival (OS) and time to next treatment (TTNT) were compared among the groups. The median OS for the entire cohort was not reached (95% CI; 63 mos, NR) and the median TTNT was 31 months (95% CI; 27,36). Among the MRD neg group, median TTNT was 37.6 months vs 23 months for MRD pos patients (P < .001); the median OS was not reached for either group, but there was a trend toward better survival for MRD neg patients. Among the MRD pos group, median percentage of pPCs was 65% (2.5-98.5), and those with >95% pPCs had a significantly better TTNT (NR vs 23 months; P = .02) and a trend toward better OS. We conclude that achievement of MRD negativity predicts for better response durability and trend toward improved OS and an increased proportion of pPC predicts for better outcomes within those who have residual tumor cells highlighting the importance of marrow normalization., (© 2019 Wiley Periodicals, Inc.)

Myeloma patients failing to achieve a complete response post autologous stem cell transplantation are heterogeneous, some ultimately achieving deeper responses and prolonged remission, whilst others relapse rapidly with poor outcomes. We evaluated the prognostic impact of the plasma cell proliferative index (PCPI) post-therapy, in 382 patients with myeloma failing to achieve complete response at 100 days post-transplant. Sixty percent (n = 230) of patients had zero clonal or too few clonal plasma cells to accurately assess PCPI (No PCPI). The remaining 40% (n = 152) of patients had PCPI performed with 79% (n = 120) having a low PCPI and 21% (n = 32) having an elevated PCPI. Patients with an elevated PCPI had significantly shorter progression free and overall survival. The median PFS was 8 months for elevated PCPI vs. 19 months for low PCPI vs. 24 months for no PCPI (p < 0.0001). The median OS was 27 months for elevated PCPI vs. 79 months for low PCPI vs. not reached for no PCPI, p < 0.0001). On multivariable analysis post-therapy PCPI was an independent predictor of progression free and overall survival. The PCPI post-therapy is a powerful predictor of survival and risk stratifies myeloma patients failing to achieve complete response early in the disease course.

The plasma cell proliferative index (PCPI), determined by a slide technique or by flow cytometry, detects cells in the S phase of the cell cycle and is a useful prognostic tool in patients with plasma cell disorders such as multiple myeloma and amyloidosis. We conducted a retrospective review analyzing the prognostic effect of PCPI in 306 patients with smoldering multiple myeloma (SMM). Seventy-nine (26%) patients had an elevated PCPI (>0.5). An elevated PCPI predicted an inferior time to progression (median, 3.0 vs 7.1 years for those with a low PCPI; P = .0004). Within 24 months, the progression rate was significantly higher for patients with an elevated PCPI (49% vs. 20%; P < .0001). PCPI is a valuable tool in risk stratifying patients with SMM and identifies patients with earlier progression who may benefit from closer follow-up and consideration of early intervention trials., (© 2018 by The American Society of Hematology.)

The plasma cell proliferative index provides an insight into plasma cell biology in plasma cell disorders and is an important prognostic marker in myeloma and smoldering myeloma. We analyzed the prognostic impact of the plasma cell proliferative index in 513 patients with systemic immunoglobulin light chain (AL) amyloidosis undergoing stem cell transplantation at the Mayo Clinic between 1 st January 2003 and 31 st August 2016. Two cohorts were identified according to Low or Elevated plasma cell proliferative index. Patients with an Elevated plasma cell proliferative index had more cardiac involvement (56% vs 44%; P =0.01), less renal involvement (55% vs 70%; P =0.001), and were more likely to have 10% or over bone marrow plasma cells (58% vs 32%; P <0.0001) compared to those with a Low plasma cell proliferative index. Both progression-free survival and overall survival were lower in patients with an Elevated compared to Low plasma cell proliferative index: median progression-free survival 44 vs 95 months ( P <0.0001) and median overall survival 102 vs 143 months ( P =0.0003). All-cause mortality at 100 days was higher in patients with an Elevated plasma cell proliferative index (elevated 10.3% vs low 4.3%; P =0.008). On multivariate analysis Elevated plasma cell proliferative index was an independent prognostic factor for overall survival (Hazard Ratio 1.5, 95%CI: 1.1-2.1; P =0.021). The plasma cell proliferative index is an important prognostic tool in patients with AL amyloidosis undergoing stem cell transplant., (Copyright© 2018 Ferrata Storti Foundation.)

We evaluated the prognostic impact of clonal circulating plasma cells (cPCs) detected by six-color multi-parametric flow cytometry (MFC) in light chain (AL) amyloidosis at diagnosis. Of the 154 patients who underwent MFC, cPCs were detected in 42% (n = 65) patients. Median number of cPCs was 81 per 150,000 events (range: 6-17,844). High bone marrow plasma cell percentage was an independent predictor of presence of cPCs. Presence of cPCs at diagnosis was associated with inferior overall survival (OS) (90 vs. 98 months, p = 0.003) and inferior progression free survival (PFS) (31 vs. 52 months, p = 0.02). Estimated 1, 2 and 5 year OS in the two groups was: 74, 64 and 57 and 89, 87, and 80%, respectively. Estimated PFS at 1, 2, and 5 years was: 69, 56, and 23% and 80, 74, and 37%, respectively. Furthermore, the presence of cPCs at diagnosis was an independent adverse predictor of OS in multivariable analysis. Achieving a very-good partial response, or better, was able to overcome the adverse impact of cPCs at diagnosis. Patients with cPCs at diagnosis may warrant closer monitoring post-treatment, especially if they do not achieve a deep hematologic response.

The production of the oncometabolite 2-hydroxyglutarate (2-HG) has been associated with c-MYC overexpression. c-MYC also regulates glutamine metabolism and drives progression of asymptomatic precursor plasma cell (PC) malignancies to symptomatic multiple myeloma (MM). However, the presence of 2-HG and its clinical significance in PC malignancies is unknown. By performing 13C stable isotope resolved metabolomics (SIRM) using U[13C6]Glucose and U[13C5]Glutamine in human myeloma cell lines (HMCLs), we show that 2-HG is produced in clonal PCs and is derived predominantly from glutamine anaplerosis into the TCA cycle. Furthermore, the 13C SIRM studies in HMCLs also demonstrate that glutamine is preferentially utilized by the TCA cycle compared with glucose. Finally, measuring the levels of 2-HG in the BM supernatant and peripheral blood plasma from patients with precursor PC malignancies such as smoldering MM (SMM) demonstrates that relatively elevated levels of 2-HG are associated with higher levels of c-MYC expression in the BM clonal PCs and with a subsequent shorter time to progression (TTP) to MM. Thus, measuring 2-HG levels in BM supernatant or peripheral blood plasma of SMM patients offers potential early identification of those patients at high risk of progression to MM, who could benefit from early therapeutic intervention.

Prior studies have revealed that the presence of increasing number of polyclonal plasma cells (pPCs) in the bone marrow (BM) are associated with better outcomes in newly diagnosed multiple myeloma (MM) patients. This effect has not been studied in patients with MM at the time of disease relapse. We determined the prognostic value of depletion of pPCs in the BM by 7-color multiparameter flow cytometry in a series of 174 relapsing MM patients. The time to next therapy (TTNT) in those with <5% pPCs was 9.4 months versus 13.9 months in those with ≥5% pPCs (P = .0091). The median overall survival (OS) in those with <5% pPCs was 21.4 months, while the median OS was not reached in those patients with ≥5% pPCs (P = .019). Of the 109 patients with standard risk cytogenetics, the median OS of those with <5% pPCs was 28.4 months, while the median OS was not reached in those with ≥5% pPCs (P = .033). As such, <5% pPCs in the BM appears to have prognostic utility in identifying a subset of relapsing MM patients, even with standard-risk cytogenetics, who have a particularly adverse outcome., (© 2017 Wiley Periodicals, Inc.)

Evaluation of clonal plasma cells (PCs) in the bone marrow (BM) of multiple myeloma (MM) patients reveals two distinct clonal PC populations based on the presence or absence of CD45 expression. We explored the prognostic significance of CD45 expression by clonal PCs in the BM of MM patients in the era of novel agent therapy. All 156 MM patients seen at the Mayo Clinic, Rochester from 2009 to 2011 who had their BM evaluated by multiparametric flow cytometry were included. Patients whose BM had ≥20% of the clonal PCs expressing CD45 were classified as CD45 positive (+) and the rest as CD45 negative (-). Of these patients, the median overall survival (OS) for patients in the CD45 (+) group (n=43, 28%) was 38 months versus not reached for the CD45 (-) group (n=113, 72%) (P=0.009). In a multivariable analysis, CD45 (+) status was an independent predictor of inferior OS among newly diagnosed patients with MM. CD45 expression may be a surrogate for a more aggressive phenotype of MM and warrants further investigation., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The presence of clonal circulating plasma cells (cPCs) remains a marker of high-risk disease in newly diagnosed multiple myeloma (MM) patients. However, its prognostic utility in MM patients with previously treated disease is unknown. We studied 647 consecutive patients with previously treated MM seen at the Mayo Clinic, Rochester who had their peripheral blood evaluated for cPCs by multi-parameter flow cytometry. Of these patients, 145 had actively relapsing disease while the remaining 502 had disease that was in a plateau and included 68 patients in complete remission (CR) and 434 patients with stable disease. Patients with actively relapsing disease were more likely to have clonal cPCs than those in a plateau (P < 0·001). None of the patients in CR had any clonal cPCs detected. Among patients whose disease was in a plateau, the presence of clonal cPCs predicted for a worse median survival (22 months vs. not reached; P = 0·004). Among actively relapsing patients, the presence of ≥100 cPCs predicted for a worse survival after flow cytometry analysis (12 months vs. 33 months; P < 0·001). Future studies are needed to determine the role of these findings in developing a risk-adapted treatment approach in MM patients with actively relapsing disease., (© 2014 John Wiley & Sons Ltd.)

This letter, published in the Blood Cancer Journal, discusses the use of minimal residual disease (MRD) monitoring for multiple myeloma (MM), a type of blood cancer. MRD monitoring involves detecting the presence of disease below the level of routine tests. Two widely accepted methods for evaluating MRD in MM are DNA-based next-generation sequencing (NGS) assays and high sensitivity flow cytometry (FC) immunophenotyping assays. The authors of the letter conducted a retrospective review of cases examined at their institution and found that the FC MRD assay had a sensitivity better than the defined minimum sensitivity of 10^-5 and closer to the sensitivity of the NGS assay. They also found that pre-screening bone marrow samples with a lower sensitivity assay helped optimize MRD test utilization. [Extracted from the article]

Primary plasma cell leukemia (pPCL) is a rare malignancy with an aggressive course and poor outcome. There has been significant improvement in the survival of multiple myeloma patients over the past decade as a result of incorporating autologous stem cell transplantation (ASCT) and novel agents into treatment regimens. However, it is unknown whether these therapies have had a similar impact on the survival of patients with pPCL. We conducted an analysis of the Surveillance, Epidemiology, and End Results database to evaluate the trends in survival of 445 patients with pPCL between 1973 and 2009. The widespread availability of ASCT and use of novel agents in the upfront setting of multiple myeloma and pPCL began after 1995 and 2006, respectively. The median overall survival based on periods of diagnosis were 5, 6, 4, and 12 months for those diagnosed during 1973-1995,1996-2000, 2001-2005, and 2006-2009, respectively (P = .001). Thus, the current study confirms the recent survival improvement in pPCL within a large US population that may be associated with the use of better therapeutic strategies. [ABSTRACT FROM AUTHOR]

Objective: To develop a whole-body low-dose CT (WBLDCT) deep learning model and determine its accuracy in predicting the presence of cytogenetic abnormalities in multiple myeloma (MM).WBLDCTs of MM patients performed within a year of diagnosis were included. Cytogenetic assessments of clonal plasma cells via fluorescent in situ hybridization (FISH) were used to risk-stratify patients as high-risk (HR) or standard-risk (SR). Presence of any of del(17p), t(14;16), t(4;14), and t(14;20) on FISH was defined as HR. The dataset was evenly divided into five groups (folds) at the individual patient level for model training. Mean and standard deviation (SD) of the area under the receiver operating curve (AUROC) across the folds were recorded.One hundred fifty-one patients with MM were included in the study. The model performed best for t(4;14), mean (SD) AUROC of 0.874 (0.073). The lowest AUROC was observed for trisomies: AUROC of 0.717 (0.058). Two- and 5-year survival rates for HR cytogenetics were 87% and 71%, respectively, compared to 91% and 79% for SR cytogenetics. Survival predictions by the WBLDCT deep learning model revealed 2- and 5-year survival rates for patients with HR cytogenetics as 87% and 71%, respectively, compared to 92% and 81% for SR cytogenetics.A deep learning model trained on WBLDCT scans predicted the presence of cytogenetic abnormalities used for risk stratification in MM. Assessment of the model’s performance revealed good to excellent classification of the various cytogenetic abnormalities.Materials and methods: To develop a whole-body low-dose CT (WBLDCT) deep learning model and determine its accuracy in predicting the presence of cytogenetic abnormalities in multiple myeloma (MM).WBLDCTs of MM patients performed within a year of diagnosis were included. Cytogenetic assessments of clonal plasma cells via fluorescent in situ hybridization (FISH) were used to risk-stratify patients as high-risk (HR) or standard-risk (SR). Presence of any of del(17p), t(14;16), t(4;14), and t(14;20) on FISH was defined as HR. The dataset was evenly divided into five groups (folds) at the individual patient level for model training. Mean and standard deviation (SD) of the area under the receiver operating curve (AUROC) across the folds were recorded.One hundred fifty-one patients with MM were included in the study. The model performed best for t(4;14), mean (SD) AUROC of 0.874 (0.073). The lowest AUROC was observed for trisomies: AUROC of 0.717 (0.058). Two- and 5-year survival rates for HR cytogenetics were 87% and 71%, respectively, compared to 91% and 79% for SR cytogenetics. Survival predictions by the WBLDCT deep learning model revealed 2- and 5-year survival rates for patients with HR cytogenetics as 87% and 71%, respectively, compared to 92% and 81% for SR cytogenetics.A deep learning model trained on WBLDCT scans predicted the presence of cytogenetic abnormalities used for risk stratification in MM. Assessment of the model’s performance revealed good to excellent classification of the various cytogenetic abnormalities.Results: To develop a whole-body low-dose CT (WBLDCT) deep learning model and determine its accuracy in predicting the presence of cytogenetic abnormalities in multiple myeloma (MM).WBLDCTs of MM patients performed within a year of diagnosis were included. Cytogenetic assessments of clonal plasma cells via fluorescent in situ hybridization (FISH) were used to risk-stratify patients as high-risk (HR) or standard-risk (SR). Presence of any of del(17p), t(14;16), t(4;14), and t(14;20) on FISH was defined as HR. The dataset was evenly divided into five groups (folds) at the individual patient level for model training. Mean and standard deviation (SD) of the area under the receiver operating curve (AUROC) across the folds were recorded.One hundred fifty-one patients with MM were included in the study. The model performed best for t(4;14), mean (SD) AUROC of 0.874 (0.073). The lowest AUROC was observed for trisomies: AUROC of 0.717 (0.058). Two- and 5-year survival rates for HR cytogenetics were 87% and 71%, respectively, compared to 91% and 79% for SR cytogenetics. Survival predictions by the WBLDCT deep learning model revealed 2- and 5-year survival rates for patients with HR cytogenetics as 87% and 71%, respectively, compared to 92% and 81% for SR cytogenetics.A deep learning model trained on WBLDCT scans predicted the presence of cytogenetic abnormalities used for risk stratification in MM. Assessment of the model’s performance revealed good to excellent classification of the various cytogenetic abnormalities.Conclusion: To develop a whole-body low-dose CT (WBLDCT) deep learning model and determine its accuracy in predicting the presence of cytogenetic abnormalities in multiple myeloma (MM).WBLDCTs of MM patients performed within a year of diagnosis were included. Cytogenetic assessments of clonal plasma cells via fluorescent in situ hybridization (FISH) were used to risk-stratify patients as high-risk (HR) or standard-risk (SR). Presence of any of del(17p), t(14;16), t(4;14), and t(14;20) on FISH was defined as HR. The dataset was evenly divided into five groups (folds) at the individual patient level for model training. Mean and standard deviation (SD) of the area under the receiver operating curve (AUROC) across the folds were recorded.One hundred fifty-one patients with MM were included in the study. The model performed best for t(4;14), mean (SD) AUROC of 0.874 (0.073). The lowest AUROC was observed for trisomies: AUROC of 0.717 (0.058). Two- and 5-year survival rates for HR cytogenetics were 87% and 71%, respectively, compared to 91% and 79% for SR cytogenetics. Survival predictions by the WBLDCT deep learning model revealed 2- and 5-year survival rates for patients with HR cytogenetics as 87% and 71%, respectively, compared to 92% and 81% for SR cytogenetics.A deep learning model trained on WBLDCT scans predicted the presence of cytogenetic abnormalities used for risk stratification in MM. Assessment of the model’s performance revealed good to excellent classification of the various cytogenetic abnormalities. [ABSTRACT FROM AUTHOR]

Autologous stem cell transplantation (ASCT) is the standard-of-care for fit/younger patients with multiple myeloma. Outcomes are heterogeneous for those achieving less than a complete response (CR) after transplant; novel predictors of early relapse are needed to guide consolidation, maintenance and disease monitoring strategies. The post-ASCT proliferative index of clonal plasma cells (cPC) predicts for survival.1 In the present study, we evaluated nonmalignant proliferating polyclonal plasma cells (pPC) for an independent effect on outcome. From January 1 2013 to January 1 2014, 176 consecutive patients with multiple myeloma underwent their first ASCT at our institution and had a bone marrow (BM) specimen collected approximately 100 days post-ASCT. All BM was subject to multi-parametric flow cytometry using a BD FACS Canto IITM as previously described. Briefly, proliferating (S-phase) pPC were classified using DAPI staining and reported as a percentage of total pPC, which was calculated if there were at least 150 pPC/500000 events (Figure 1). Those with less than 150 pPC were deemed "non-evaluable." Time to next therapy (TNT) was calculated from ASCT Day 0 to the initiation of a new therapy (not including maintenance or consolidation), with patients censored at time of last follow-up or death without further therapy. Overall survival (OS) was calculated from Day 0 to death, with living patients censored at time of last follow-up. Statistics were performed using R 3.5.2. Responses at Day 100 were as follows: 71 (40%) CR, 48 (27%) very good partial response, 57 (33%) partial response or less. Among the 77 of 105 (73%) patients with