A Multiple Myeloma Classification System That Associates Normal Bone Marrow B-Cell Subset Phenotypes with Disease Stage and Prognosis

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3352-3352 ◽  
Author(s):  
Hans Erik Johnsen ◽  
Julie Støve Bødker ◽  
Alexander Schmitz ◽  
Malene Krag Kjeldsen ◽  
Kim Steve Bergkvist ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
B Cell ◽  
Clinical Data ◽  
Cell Subset ◽  
Disease Stage ◽  
High Dose ◽  
Gene Probe ◽  
Cell Of Origin ◽  
Data Set ◽  
B Cell Subsets

Abstract Introduction Today’s diagnostic tests for multiple myeloma reflect the criteria of the updated WHO classification based on biological, morphological and clinical heterogeneity. It has been the concept behind the present study to extend our current biological classification and provide a new tool to generate insight into the stage of clonal differentiation and oncogenesis. The goal of the present study was to generate B-cell subset associated gene signatures (BAGS) from the BM hierarchy used to assign individual phenotypic cell of origin (pCOO) subtypes in patients and validate its pathogenetic impact by prognostic evaluation. Methods Bone marrows (BM, n=7) were harvested from sternum during cardiac surgery. B-cell subsets were phenotyped by Euroflow standard for multiparametric flow cytometry and FACS-sorted for microarray analysis on the Human Exon 1.0 ST Arrays platform. This combination allowed us to generate five BAGS for PreBI, PreBII, immature (Im), naïve (N), memory (M) B-cells, and plasma cells (PC) of normal BM. The BAGS classifier was based on all median-centred probe sets from the data set by regularized multinomial regression with 6 discrete outcomes corresponding to each B-cell subset and the elastic net penalty using the algorithm implemented in the R-package glmnet24. Each clinical data set was probe-set-wise adjusted to have a zero median and the same variance as in the BM data set. The associated cell of origin subset for each patient in each data set was predicted by the BAGS classifier by assigning the class with the highest predicted probability score above 0.45 and otherwise UC. All statistical analyses were done with R version 3.0.2. Survival analysis was performed by the Kaplan-Meier method and log-rank tests. Clinical data sets were from University of Arkansas for Medical Sciences UAMS (n=559), the Dana Farber Cancer Institute DFCI (n=170) both available on the GEO website. Results First, we verified the quality of the sampled B-cell subsets based on the expression patterns of differentiation marker genes. Next, we constructed the BAGS-classifier provided by 38-68 gene probe sets (n), capable of assigning samples to each of the six subtypes of PreBI (n=38), PreBII (n=82), Im (n=71), N (n=68), M (n=52) and PC (n=43). Second, we assigned individual myeloma cases in the 2 patient cohorts including a total of 729 myeloma patients. The resultant assignments generated patient BAGS subtypes with diagnostic frequencies of 0,5-0,6 % preBI, 7-8 % preBII, 27-30 % Im, 8-9 % N, 36-37 % M, 1-5 % PC and 15-16 % UC subtypes. The frequencies were not different between the cohorts. Third, the BAGS subtypes was associated significantly with overall survival (P = 8.6 x 10-5) for high dose melphalan and autologous stem cell transplanted UAMS patients1, as illustrated in Figure 1. The most significant impact was observed within the PreB-II (light blue) and M (acid green) subtypes conferred with significant inferior prognosis compared to the Im (amethyst), N (apple green) and PC (blue) subtypes. The PreB-II and M subtypes in the UAMS cohort were correlated to the ISS stage I-III with 33%, 49% and 69% of the cases, respectively. Fourth, we compared the BAGS subtypes and the TC classification2 with no observed correlations (results not shown). Conclusions Our data support a new COO defined BAGS classification based on the normal BM B-cell subset phenotypes with impact on staging and prognosis in multiple myeloma and a new diagnostic platform, which may result in more effective disease management. References 1) Zhan F, Huang Y, Colla S et al. The molecular classification of multiple myeloma. Blood. 2006 Sep 15;108(6):2020-8. 2) Bergsagel PL, Kuehl WM, Zhan F, Sawyer J, Barlogie B, Shaughnessy J Jr. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood. 2005 Jul 1;106(1):296-303. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

scholarly journals Multiple Myeloma Includes Phenotypically Defined Subsets of Clonotypic CD20+ B Cells that Persist during Treatment with Rituximab

2008 ◽  
Vol 2 ◽  
pp. CMO.S615 ◽  
Author(s):  
Linda M. Pilarski ◽  
Eva Baigorri ◽  
Michael J. Mant ◽  
Patrick M. Pilarski ◽  
Penelope Adamson ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
B Cells ◽  
B Cell ◽  
Plasma Cells ◽  
Cell Subset ◽  
Light Scatter ◽  
Cell Compartments ◽  
B Lineage ◽  
B Cell Subsets ◽  
Anti Cd20

Potential progenitor B cell compartments in multiple myeloma (MM) are clinically important. MM B cells and some circulating MM plasma cells express CD20, predicting their clearance by treatment with anti-CD20. Here we describe two types of clonotypic CD20+ B cell in peripheral blood of myeloma patients, identified by their expression of CD19 and CD20 epitopes, their expression of CD45RA and their light scatter properties. Thus, the circulating component of the MM clone includes at least two distinct CD19+ CD20+ B cell compartments, as well as CD138+CD20+ plasma cells. To determine whether either or both B cell subsets and the CD20+ plasma cell subset were depleted by anti-CD20 therapy, they were evaluated before, during and after treatment of patients with rituximab (anti-CD20), followed by quantifying B cell subsets over a 5 month period during and after treatment. Overall, all three types of circulating B lineage cells persist despite treatment with rituximab. The inability of rituximab to prolong survival in MM may result from this failure to deplete CD20+ B and plasma cells in MM.

A Diffuse Large B-Cell Lymphoma Classification System That Associates Normal B-Cell Subset Phenotypes with Prognosis

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2973-2973
Author(s):  
Karen Dybkær ◽  
Martin Bøgsted ◽  
Steffen Falgreen ◽  
Malene Krag Kjeldsen ◽  
Alexander Schmitz ◽  
...  
Keyword(s):  
B Cell ◽  
Cell Lymphoma ◽  
Cell Subset ◽  
B Cell Lymphoma ◽  
Gene Probe ◽  
Prognostic Impact ◽  
Cell Of Origin ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Abstract Background Recent findings have introduced biological classification of non-Hodgkin lymphomas as exemplified by the “activated B-cell-like” (ABC) and “germinal-center B-cell–like” (GCB) subgroups of diffuse large B-cell lymphoma (DLBCL). Aims The goal is to generate a refined cell of origin (COO) classification that includes B-cell subset associated gene signatures (BAGS) from the normal B-cell hierarchy. Methods We have combined fluorescence activated cell sorting and gene expression profiling by Gene Chip HG U133 Plus 2.0 to generate five BAGS for naïve, germinal centrocytes and centroblasts, post germinal memory B-cells, and plasmablasts of normal human tonsils. Clinical data sets are the Aalborg Project CHEPRETRO (N=89), the Lymphoma/Leukemia Molecular Profiling Project LLMPP (N=233), the International DLBCL Rituximab-CHOP Consortium MD Anderson Project IDRC (N=460), the Mayo Clinic, Brigham & Women Hospital, and Dana-Farber Cancer Institute Project MDFCI (N=88) available on the GEO website. All statistical analyses were done with R version 3.0.1 and full documentation is provided by a Sweave document. Results First, we verified the quality of the sampled B-cell subsets based on the expression patterns of differentiation molecules, transcription factors, and genes matching biological knowledge. Next, we constructed a BAGS-classifier provided by 77-115 gene probe sets, capable of assigning samples to each of the five COO subtypes. Second, we assigned individual lymphoma cases in 5 patient cohorts including a total of 1063 patient. BAGS identified COO subtypes with frequencies of 2-7 % naïve (N), 35-41 % centrocytes (CC), 18-21 % centroblasts (CB), 4-15 % memory (M), 12-18 % plasmablast (PB), and 15-16 % unclassified (UC) subtypes. The frequencies was not different between cohorts (p=0.41). Third, the BAGS subtypes was associated significantly with overall survival and time to progression for R-CHOP–treated patients in clinical cohorts from the LLMPPN (p=0.0441/0.0358) and the IDRC Program (p=0.002/8e-04). Fourth, we found a very high fraction of GCB samples to be of CC or CB subtypes. On the contrary, a major fraction of BAGS-unclassified subtypes were of the ABC class. In a multiple Cox proportional hazards model we identified the BAGS subtypes to be a prognostic variables independent of ABC/GCB subtypes but not of IPI and age. The most significant impact was observed within the GCB subclass, where the GCB-CC subtype had superior prognosis compared to the GCB-CB subtype, in accordance with individual assignments for drug specific sensitivity to hydroxydaunomycin and vincristine. Fifth, we performed genetic evaluation of the BAGS subtypes by mutation analysis within the CHEPRETRO cohort for EZH2, CD79B, and MYD88 identifying frequencies of 6.3%, 10.1% and 14.7%, respectively. The EZH2 mutation was only identified in the GCBN-CC and -CB subtypes. Mutations of CD79B and MYD88 were preferential in ABC, present in all subtypes. The CC subtype had high p53 mutation and indel frequencies, whereas the CB subtype had high Chr12q15 amplification frequencies and a complex genotype. Finally, the CC subtype expressed LMO2, NF-κB targets, CD58, Stroma1, and MHCII genes, known to have prognostic impact. Summary In summary, this study addresses an unmet medical need for a new diagnostic platform for individual DLBCL classification of “cell of origin” phenotyping attempting to design new strategies and more effective disease management. Disclosures No relevant conflicts of interest to declare.

scholarly journals Hyper‐metabolic B cells in the spleens of old mice make antibodies with autoimmune specificities

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Daniela Frasca ◽  
Maria Romero ◽  
Denisse Garcia ◽  
Alain Diaz ◽  
Bonnie B. Blomberg
Keyword(s):  
B Cells ◽  
B Cell ◽  
Inflammatory Markers ◽  
Cell Subset ◽  
Antibody Responses ◽  
Metabolic Phenotype ◽  
Cellular Mechanisms ◽  
Autoimmune Antibodies ◽  
B Cell Subsets ◽  
Old Mice

Abstract Background Aging is associated with increased intrinsic B cell inflammation, decreased protective antibody responses and increased autoimmune antibody responses. The effects of aging on the metabolic phenotype of B cells and on the metabolic programs that lead to the secretion of protective versus autoimmune antibodies are not known. Methods Splenic B cells and the major splenic B cell subsets, Follicular (FO) and Age-associated B cells (ABCs), were isolated from the spleens of young and old mice and left unstimulated. The RNA was collected to measure the expression of markers associated with intrinsic inflammation and autoimmune antibody production by qPCR. B cells and B cell subsets were also stimulated with CpG and supernatants collected after 7 days to measure autoimmune IgG secretion by ELISA. Metabolic measures (oxygen consumption rate, extracellular acidification rate and glucose uptake) were performed using a Seahorse XFp extracellular flux analyzer. Results Results have identified the subset of ABCs, whose frequencies and numbers increase with age and represent the most pro-inflammatory B cell subset, as the cell type mainly if not exclusively responsible for the expression of inflammatory markers and for the secretion of autoimmune antibodies in the spleen of old mice. Hyper-inflammatory ABCs from old mice are also hyper-metabolic, as compared to those from young mice and to the subset of FO B cells, a feature needed not only to support their higher expression of RNA for inflammatory markers but also their higher autoimmune antibody secretion. Conclusions These results identify a relationship between intrinsic inflammation, metabolism and autoimmune B cells and suggest possible ways to understand cellular mechanisms that lead to the generation of pathogenic B cells, that are hyper-inflammatory and hyper-metabolic, and secrete IgG antibodies with autoimmune specificities.

scholarly journals Diffuse large B-cell lymphoma: R-CHOP failure—what to do?

Hematology ◽  
2016 ◽  
Vol 2016 (1) ◽  
pp. 366-378 ◽  
Author(s):  
Bertrand Coiffier ◽  
Clémentine Sarkozy
Keyword(s):  
B Cell ◽  
Cell Lymphoma ◽  
Unmet Need ◽  
Prognostic Index ◽  
B Cell Lymphoma ◽  
Disease Stage ◽  
High Dose ◽  
Good Definition ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Abstract Although rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) is the standard treatment for patients with diffuse large B-cell lymphoma (DLBCL), ∼30% to 50% of patients are not cured by this treatment, depending on disease stage or prognostic index. Among patients for whom R-CHOP therapy fails, 20% suffer from primary refractory disease (progress during or right after treatment) whereas 30% relapse after achieving complete remission (CR). Currently, there is no good definition enabling us to identify these 2 groups upon diagnosis. Most of the refractory patients exhibit double-hit lymphoma (MYC-BCL2 rearrangement) or double-protein-expression lymphoma (MYC-BCL2 hyperexpression) which have a more aggressive clinical picture. New strategies are currently being explored to obtain better CR rates and fewer relapses. Although young relapsing patients are treated with high-dose therapy followed by autologous transplant, there is an unmet need for better salvage regimens in this setting. To prevent relapse, maintenance therapy with immunomodulatory agents such as lenalidomide is currently undergoing investigation. New drugs will most likely be introduced over the next few years and will probably be different for relapsing and refractory patients.

scholarly journals Proportions of B-cell subsets are altered in incomplete systemic lupus erythematosus and correlate with interferon score and IgG levels

Rheumatology ◽  
2020 ◽  
Vol 59 (9) ◽  
pp. 2616-2624
Author(s):  
Svenja Henning ◽  
Wietske M Lambers ◽  
Berber Doornbos-van der Meer ◽  
Wayel H Abdulahad ◽  
Frans G M Kroese ◽  
...  
Keyword(s):  
B Cells ◽  
B Cell ◽  
Lupus Erythematosus ◽  
Cell Subset ◽  
Cross Sectional Study ◽  
Type I ◽  
Healthy Controls ◽  
Sectional Study ◽  
Cross Sectional ◽  
B Cell Subsets

Abstract Objectives Incomplete SLE (iSLE) patients display symptoms typical for SLE but have insufficient criteria to fulfil the diagnosis. Biomarkers are needed to identify iSLE patients that will progress to SLE. IFN type I activation, B-cell-activating factor (BAFF) and B-cell subset distortions play an important role in the pathogenesis of SLE. The aim of this cross-sectional study was to investigate whether B-cell subsets are altered in iSLE patients, and whether these alterations correlate with IFN scores and BAFF levels. Methods iSLE patients (n = 34), SLE patients (n = 41) with quiescent disease (SLEDAI ≤4) and healthy controls (n = 22) were included. Proportions of B-cell subsets were measured with flow cytometry, IFN scores with RT-PCR and BAFF levels with ELISA. Results Proportions of age-associated B-cells were elevated in iSLE patients compared with healthy controls and correlated with IgG levels. In iSLE patients, IFN scores and BAFF levels were significantly increased compared with healthy controls. Also, IFN scores correlated with proportions of switched memory B-cells, plasma cells and IgG levels, and correlated negatively with complement levels in iSLE patients. Conclusion In this cross-sectional study, distortions in B-cell subsets were observed in iSLE patients and were correlated with IFN scores and IgG levels. Since these factors play an important role in the pathogenesis of SLE, iSLE patients with these distortions, high IFN scores, and high levels of IgG and BAFF may be at risk for progression to SLE.

scholarly journals B Cell Subsets as Severity-Associated Signatures in COVID-19 Patients

2020 ◽  
Vol 11 ◽  
Author(s):  
Víctor A. Sosa-Hernández ◽  
Jiram Torres-Ruíz ◽  
Rodrigo Cervantes-Díaz ◽  
Sandra Romero-Ramírez ◽  
José C. Páez-Franco ◽  
...  
Keyword(s):  
B Cells ◽  
B Cell ◽  
Cell Subset ◽  
Hierarchical Cluster ◽  
Specific Subset ◽  
Respiratory Parameters ◽  
Cell Subpopulations ◽  
Severity Of The Disease ◽  
B Cell Subsets ◽  
Relationship Of

BackgroundSARS-CoV-2 infection represents a global health problem that has affected millions of people. The fine host immune response and its association with the disease course have not yet been fully elucidated. Consequently, we analyze circulating B cell subsets and their possible relationship with COVID-19 features and severity.MethodsUsing a multiparametric flow cytometric approach, we determined B cell subsets frequencies from 52 COVID-19 patients, grouped them by hierarchical cluster analysis, and correlated their values with clinical data.ResultsThe frequency of CD19+ B cells is increased in severe COVID-19 compared to mild cases. Specific subset frequencies such as transitional B cell subsets increase in mild/moderate cases but decrease with the severity of the disease. Memory B compartment decreased in severe and critical cases, and antibody-secreting cells are increased according to the severity of the disease. Other non-typical subsets such as double-negative B cells also showed significant changes according to disease severity. Globally, these differences allow us to identify severity-associated patient clusters with specific altered subsets. Finally, respiratory parameters, biomarkers of inflammation, and clinical scores exhibited correlations with some of these subpopulations.ConclusionsThe severity of COVID-19 is accompanied by changes in the B cell subpopulations, either immature or terminally differentiated. Furthermore, the existing relationship of B cell subset frequencies with clinical and laboratory parameters suggest that these lymphocytes could serve as potential biomarkers and even active participants in the adaptive antiviral response mounted against SARS-CoV-2.

Immunophenotypic and Genetic Characteristics of Diffuse Large B-Cell Lymphoma (DLBCL), and Prognostic Significance of Cell of Origin (COO) in a Southeast Asian Cohort

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4222-4222 ◽  
Author(s):  
Vanessa CL Chong ◽  
Eng Soo Yap ◽  
Liu Xin ◽  
Suk Teng Chin ◽  
Anand Jeyasekharan ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
B Cell ◽  
Prognostic Markers ◽  
Prognostic Significance ◽  
B Cell Lymphoma ◽  
Southeast Asian ◽  
Disease Stage ◽  
Prognostic Impact ◽  
Cell Of Origin ◽  
Asian Patients

Abstract BACKGROUND/OBJECTIVE: DLBCL is a heterogeneous disease which on gene expression profiling studies (GEP) can be divided into 2 distinct subtypes, germinal center (GCB) as well as activated B cell subtype (non GCB) based on the cell-of-origin. Immunochemistry (IHC) based algorithms have been shown to have good concordance with GEP for COO classification. While Western data suggests that GCB-subtypes are associated with improved outcomes, there has been limited and conflicting data on the prognostic significance of COO amongst Asian patients. The prevalence and prognostic significance of other prognostic markers such as MYC overexpression or translocation amongst DLBCL Asian patients also remains unclear. Our study aimed to evaluate i) the prevalence of MYC translocation and overexpression, as well as COO subgroups of DLBCL in a cohort of Singaporean patients, and ii) the prognostic impact of these factors in comparison with International Prognostic Index (IPI) score and other standard prognostic markers. METHODS: A single-center retrospective analysis of 384 consecutive DLBCL patients diagnosed 2013 - 2018 was performed. Hans criteria was used to assign COO. (Prior validation studies from the hospital's pathology laboratory had confirmed concordance between Hans algorithm and GEP of 75 %.) Majority of the patients received R-CHOP (N =228) or R-EPOCH (N =47) chemotherapy RESULTS: The median age of the cases was 61 years (range 18-88), 223 were female and the majority had stage 3-4 disease (62%). Of the 297 cases with IHC data for COO, 120 (40%) were GCB subtype and 177 cases (60%) were non-GCB. MYC was overexpressed in 75% of cases (165/220) tested, while MYC FISH was positive in 23% of cases (28/122) tested. 10 of the 28 patients with MYC FISH positive were treated with R-EPOCH chemotherapy. With a median follow up of 1.2 years (0.1-5.3 years), the projected 5-year OS and PFS for the entire cohort was 69.5% and 65.6% respectively. Amongst baseline clincopathologic characteristics, only age, IPI and disease stage was associated with improved OS on both univariate and multivariate analysis. Age, IPI and disease stage was associated with PFS in univariate analysis but only IPI remained significant (p<0.001) after multivariate analysis. Neither MYC overexpression, MYC translocation nor COO was found to be prognostic for OS or PFS on multivariate analysis. The 5-year PFS and OS for the GCB vs the non-GCB subgroups was 72% vs 66%, (p=0.10), and 71% vs 70%, (p=0.06) respectively. (See Figure 1A and 1B). CONCLUSION: In this Southeast Asian DLBCL cohort, we confirmed the prognostic significance of the IPI score for both PFS and OS. GCB subtype of DLBCL comprised 40% of all DLBCL cases. COO based on Hans criteria had no prognostic significance on PFS or OS. This is in contrast to Western series where GCB subtypes identified by IHC-algorithms are associated with better prognosis. Disclosures Jeyasekharan: PerkinElmer: Other: Collaboration; Merck Sharp & Dohme: Honoraria; Janssen: Research Funding; AstraZeneca: Other: Collaboration.

Multiple Myeloma Profile In Latin America: Clinical and Epidemiological Observational Study

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 5327-5327
Author(s):  
Vania T M Hungria ◽  
Angelo Maiolino ◽  
Gracia Aparecida Martinez ◽  
Carmino A De Souza ◽  
Rosane Bittencourt ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Latin America ◽  
Clinical Features ◽  
Median Overall Survival ◽  
High Dose Chemotherapy ◽  
Patterns Of Care ◽  
Disease Stage ◽  
High Dose

Abstract Introduction Little is known about the incidence and clinical features of Multiple Myeloma (MM) in Latin America. A clinical registry of Latin American (LA) patients with MM represents an opportunity to gain insight into the prevalence of the disease in this region, the patterns of care and the current treatment status in different LA countries. Objective To characterize the demographic and clinical features of patients with multiple myeloma from five LA countries (Brazil, Argentina, Chile, Mexico and Peru) and to create a LA database on MM; in addition to investigating the patterns of care for MM patients in Latin America. Patients and Methods This is an observational, non-intervention study, with a prospective evaluation of data. Eligible patients were diagnosed with multiple myeloma, between January 1, 2005, and December 31, 2007, at any one of the participating centers, regardless of disease stage or treatment modality. The follow-up period extended to at least 5 years for each patient (December 31, 2012). Results Eight hundred and seventy six patients were included. The median age was 60 years old (25-97), 53.4% male and 46.6% female. The median follow-up was 31.4 months, and the median overall survival was 57 months. The median overall survival to patients who received high-dose chemotherapy was 77 months and for patients who received conventional chemotherapy was 48 months (p<0.001). The multivariate prognostic model included patient baseline variables that were associated with mortality in the Kaplan-Meier univariate analyses. Only hypercalcemia, DSS II and III, ISS stage III andnon- high-dose chemotherapy were independent predictors of mortality. Conclusion This current study, which is the largest case series of MM patients in Latin America, recognizes the feasibility of large, collaborative, observational studies among various tertiary-care hematology centers in Latin America. Note We will present more details related to the demographic and most frequently used treatments in Latin America for newly diagnosed and relapsed patients in these LA countries. Disclosures: No relevant conflicts of interest to declare.

Differences in Cell of Origin (COO) Affect Outcomes in Caucasian(C) but Not in African American(AA) Patients with Diffuse Large B-Cell Lymphoma(DLBCL)

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1460-1460 ◽  
Author(s):  
Uma Borate ◽  
Deniz Peker ◽  
James M. Foran ◽  
Luciano J Costa
Keyword(s):  
B Cell ◽  
B Cell Lymphoma ◽  
Disease Stage ◽  
Rank Test ◽  
Advanced Stage ◽  
Cell Of Origin ◽  
First Line ◽  
First Line Therapy ◽  
Log Rank Test ◽  
Line Therapy

Abstract Introduction: DLBCL is an aggressive mature B-cell neoplasm with a low incidence in African Americans and other minority groups. The differences in outcomes based on DLBCL Cell of Origin(COO) immunophenotypic subtypes as defined by the Hans algorithm using CD10, Bcl-6, and MUM1 namely germinal center B-cell (GCB) and non-GCB have been based on predominantly Caucasian patients (pts) and their impact on outcomes in AA patients have not been well studied. Material and Methods: A retrospective review of clinicopathologic data from patients diagnosed and treated for DLBCL at UAB between 2002-2011 was conducted following IRB approval .The data collected included patient demographics (age, sex, self identified race), DLBCL subtype (GCB vs. non-GCB based on the Hans algorithm), disease stage, first line therapy regimens and patient outcomes. We analyzed group differences in both C and AA pts with GCB and non-GCB subtypes of DLBCL in all the parameters mentioned above using the chi square test for categorical variables,. In addition, OS was examined using Kaplan Meier curves and the log rank test. We performed univariate and multivariate analyses to examine the effects of variables of interest on OS. All results were considered statistically significant at α=0.05 level. Results: We included a total of 259 pts in our analysis after excluding patients with missing demographics, disease related data, primary mediastianal DLBCL, missing first line therapy data and outcomes data as well as race identified as other than C or AA. 45 patients (17.4%) of patients self identified as AA and 214 (82.6%) self identified as Caucasian. The mean age of presentation for AA pts was 52 yrs compared to 58 years for C patients (p=0.045) and 28 (62.2%) AA patients presented with advanced Stage III and IV disease compared to 89 (44.6%) of C patients (P=0.04) both being statistically significant. Based on COO characterization using immunophenotype by Hans algorithm, 27 AA pts (60%) and 145(67%) of C pts were GCB by immunophenotype(p=0.317). 95% of all patients received R-CHOP as first line therapy , 3.5% received R-CVP and the remaining received a combination of Rituximab alone, FCR or radiation therapy .On analyzing OS based on COO, AA patients did not demonstrate a significant difference in OS based on COO with both GCB and non-GCB groups having a median OS of 84 months ( p=0.74)( 95% CI 72-121 months). However, the median OS for C pts with GCB phenotype was 104 months compared to 25 months for the non-GCB phenotype and the median OS was 55 months +/-12.6 months for the C pt group as a whole( p<0.001 by log rank test )which was highly statistically significant.Multivariate analyses of different factors affecting OS showed only COO (p<0.001), age(p=0.07) and stage of DLBCL at presentation(p=0.027) to affect OS significantly.Race,Gender and IPI score did not appear to impact OS significantly. Conclusion: Our study aimed to study the impact of COO and Race on OS in DLBCL especially in AA pts where this has not been well characterized. Our results show that as expected the incidence of DLBCL is lower in AA patients compared to C pts. However, DLBCL presents at younger age and with more advanced stage in AA than in C patients. Although distribution of COO is similar in AA and C patients, our findings suggest that COO may not have the same effect on prognosis among AA pts as it does among the C pt population where we see non-GCB patients do significantly worse than their GCB counterparts. This may reflect a different disease biology in AA patients that has yet to be understood. Our study limitations include not taking into account disease relapse, second line therapy and effect of autologous bone marrow transplantation on overall survival. Figure 1. Figure 1. Figure 2. Figure 2. Figure 3. Figure 3. Disclosures No relevant conflicts of interest to declare.

Sign in / Sign up

Export Citation Format

Share Document