scholarly journals Comparison of five diagnostic flow cytometry scores in patients with myelodysplastic syndromes: Diagnostic power and prognostic impact

Author(s):  
Uta Oelschlaegel ◽  
Lorenz Oelschlaeger ◽  
Malte Bonin ◽  
Michael Kramer ◽  
Katja Sockel ◽  
...  
Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2799-2799
Author(s):  
Yasuko Hamada ◽  
Hideto Tamura ◽  
Mariko Ishibashi ◽  
Namiko Okuyama ◽  
Asaka Kondo ◽  
...  

Abstract Introduction CD7 is expressed on human T and NK cells and progenitors of myeloid cells as well as blasts in some patients with myelodysplastic syndromes (MDS). We showed previously that CD7 positivity of MDS blasts was associated with aggressive characteristics and poor prognosis. However, the mechanisms by which CD7-expressing MDS blasts are associated with disease progression remain unknown. In this study, we first investigated the biology of CD7-expressing MDS blasts. Second, to validate the prognostic impact of CD7 on MDS blasts, prognostic variables including the CD7 positivity of MDS blasts and a new prognostic system, the revised International Prognostic Scoring System (IPSS-R) were evaluated in Japanese MDS patients. Methods & Results 1) To investigate the mechanisms regulating CD7 expression, we used MDS cell lines HNT-34 and F-36P. CD7 expression on these cells was partially down-regulated by inhibition of NFκB. 2) To investigate the survival potential in CD7+ MDS blasts, we analyzed cell cycles and spontaneous apoptosis by flow cytometry. CD7+ blasts had a cell cycle advantage compared with CD7– blasts in F-36P but not in HTN-34 cells. Compared with CD7– HNT-34 cells, CD7+ HTN-34 cells were more resistant to spontaneous and serum deprivation-induced apoptosis. 3) We then compared gene and protein expression levels of apoptosis-related proteins including Bad, Bax, Bcl-2-L1, Bcl-2, caspase-3, caspase-8, caspase-9, FADD, Fas, and FasL between CD7+ and CD7– blasts of these cell lines using real-time PCR and flow cytometry, respectively. CD7– blasts had markedly higher expression levels of the Bad gene and protein compared with CD7+ blasts in both cell lines. The expression levels of Fas and FasL were suppressed in CD7+ blasts compared with CD7– blasts in F36P cells. These results support the association of CD7 expression on MDS blasts with disease progression. 4) To reevaluate the prognostic impact of CD7 expression as well as R-IPSS, prognostic variables were analyzed in 81 MDS patients [refractory anemia (RA) 55, RA with ringed sideroblasts 7, RA with excess blasts (RAEB) 18, and RAEB in transformation 1], comprising 50 men/31 women with a median age of 67 (range 27–88) years. Immunophenotyping was performed by 3-color flow cytometry, in which blast cells were gated with a CD45-gating method, and 9 parameters including CD7 expression on MDS blasts, i.e., CD34+ myeloblast-related and B-progenitor-related cluster size, myeloblast CD45 expression, and aberrant expression of CD7, CD10, CD11, CD15, CD56, and B7-H1 on myeloblasts, were analyzed. Using the Cox proportional hazard regression model, we identified five prognostic variables: IPSS-R score; percentage of blasts in peripheral blood; CD7 expression; gender; and white blood cell count. The chi-square test showed that the IPSS-R score and CD7 expression were strong prognostic factors (P = 0.0114 and 0.006, respectively). Patients whose MDS blasts expressed high levels of CD7 (17% or more MDS blasts were CD7+) had significantly shorter survival than other patients. Conclusion Our study revealed that CD7+ MDS blasts had apoptosis resistance with decreased expression of apoptosis-related genes, especially Bad. Signaling via CD7 on MDS blasts might inhibit Bad expression and then confer apoptosis resistance. Further studies are in progress to clarify CD7 signaling in cell lines as well as in MDS blasts from patients. Furthermore, we demonstrated for the first time that IPSS-R as well as CD7 expression on blasts had a strong impact on MDS patient prognosis. Disclosures: Kurokawa: Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Consultancy, Research Funding. Shibayama:celgene: Honoraria, Research Funding; Janssen: Honoraria. Naoe:Otsuka Pharmaceutical Co., Ltd, Kyowa Hakko Kirin Co., Ltd., Wyeth, and Chugai Pharmaceutical Co., Ltd.: Research Funding.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4448-4448
Author(s):  
Valentina Giudice ◽  
Marisa Gorrese ◽  
Idalucia Ferrara ◽  
Rita Pepe ◽  
Angela Bertolini ◽  
...  

Abstract Introduction. Myelodysplastic syndromes (MDS), a group of clonal hematological diseases, are characterized by ineffective hematopoiesis, progressive peripheral blood (PB) cytopenia(s), and increased risk of developing acute myeloid leukemia (AML). Classification and risk stratification are constantly under revision for a better estimation of prognosis in those patients. Investigation of immune biomarkers is needed, because immune dysregulation also plays an important role in dysplastic hemopoiesis and immunological escape of neoplastic clones. Here, we studied frequency of low-density granulocytes (LDGs), a neutrophil subset with immunoregulatory functions, in MDS and AML at diagnosis and during treatments. Methods. A total of 17 patients (M/F, 14/12; median age, 69 years old; range, 21-84 years) and seven healthy subjects were enrolled at the Hematology and Transplant Center, University Hospital "San Giovanni di Dio e Ruggi d'Aragona", Salerno, Italy, between October 2020 and July 2021. Patients were diagnosed with AML (N = 7), or MDS (N = 10) according to the 2016 World Health Organization criteria. For immunophenotyping, fresh EDTA whole PB was stained with the ollowing antibodies: CD45; HLA-DR; CD15; CD3; CD56; CD19; CD11b; CD33; CD34; CD14; and CD16 (all from Beckman Coulter, Brea, CA). Acquisition was carried out using a Navios EX flow cytometer, and Navios software v1.3 (Beckman Coulter). Post-acquisition compensation and analysis were performed using FlowJo software (v.10.7.1, Becton Dickinson). LDGs were identified as CD3-CD56-CD19-CD11b+CD33+CD14-CD15+ cells, following previously published gating strategies (Rahman S, et al. Ann Rheum Dis. 2019). Data were analyzed using Prism (GraphPad software, La Jolla, CA). A P < 0.05 was considered statistically significant. Results. Frequencies of circulating LDGs were significantly reduced in AML patients at diagnosis compared to controls (P = 0.0018) and MDS (P = 0.0077) and were slightly decreased compared to AML in complete remission (P = 0.1605). MDS patients were then divided based on Revised International Prognostic Scoring System (IPSS-R), and very-low and low-risk MDS patients displayed significantly higher circulating LDG frequencies compared to AML at diagnosis (P = 0.0083), while no differences were described between AML at baseline and intermediate-risk MDS (P = 0.1103). Subsequently, LDGs were correlated with clinical and phenotypic features by correlation analysis showing significant negative correlations between LDGs and blasts identified by flow cytometry (r = -0.5463; P = 0.0057) but not by cytology (P = 0.1346), between LDGs and lymphocytes (r = -0.4407; P = 0.0311) or flow cytometric normalized blast count (NBC; r = -0.5283; P = 0.0096) as previously defined (Giudice V, et al. Biomedicines. 2021). A slight negative correlation was described between LDGs and WT1 expression levels (r = -0.5369; P = 0.0719), particularly evident in MDS patients (r = -0.9980; P = 0.0402), supporting our previous findings of negative prognostic impact of WT1 expression in MDS and AML. Finally, we investigated CD16 expression on LDGs, because CD16 is essential for neutrophil degranulation. Despite no differences were described between percentage of LDG subsets among patients' groups, various correlations were identified by Pearson analysis. In particular, CD16+ LDGs negatively correlated with blasts (P = 0.0229), while positively correlated with lymphocytes (P = 0.0404) detected by flow cytometry. Conversely, CD16int and CD16- LDGs negatively correlated with lymphocytes (P = 0.0109 and P = 0.0021, respectively) and positively correlated with granulocytes identified by flow cytometry (P = 0.0024 and P = 0.0008, respectively). In addition, CD16int LDGs negatively correlated with blasts detected by flow cytometry (r = -0.65; P = 0.0414). Conclusions. Our preliminary results suggested a possible role of LDGs in prognostic definition of AML and MDS patients especially when combined with other biomarkers, such as WT1 expression levels or NBC. Moreover, our data supported the hypothesis of biological heterogeneity of granulocytes, as LDG subsets variously correlated with lymphocytes and leukemic cells suggesting different roles in suppression or activation of immune responses. However, our findings need further validation in larger cohorts and in in vitro studies. Disclosures No relevant conflicts of interest to declare.


2011 ◽  
pp. 121-143 ◽  
Author(s):  
C. Alhan ◽  
T.M. Westers ◽  
G.J. Ossenkoppele ◽  
Arjan A. van de Loosdrecht

2021 ◽  
pp. JCO.20.02810
Author(s):  
Aziz Nazha ◽  
Rami Komrokji ◽  
Manja Meggendorfer ◽  
Xuefei Jia ◽  
Nathan Radakovich ◽  
...  

PURPOSE Patients with myelodysplastic syndromes (MDS) have a survival that can range from months to decades. Prognostic systems that incorporate advanced analytics of clinical, pathologic, and molecular data have the potential to more accurately and dynamically predict survival in patients receiving various therapies. METHODS A total of 1,471 MDS patients with comprehensively annotated clinical and molecular data were included in a training cohort and analyzed using machine learning techniques. A random survival algorithm was used to build a prognostic model, which was then validated in external cohorts. The accuracy of the proposed model, compared with other established models, was assessed using a concordance (c)index. RESULTS The median age for the training cohort was 71 years. Commonly mutated genes included SF3B1, TET2, and ASXL1. The algorithm identified chromosomal karyotype, platelet, hemoglobin levels, bone marrow blast percentage, age, other clinical variables, seven discrete gene mutations, and mutation number as having prognostic impact on overall and leukemia-free survivals. The model was validated in an independent external cohort of 465 patients, a cohort of patients with MDS treated in a prospective clinical trial, a cohort of patients with paired samples at different time points during the disease course, and a cohort of patients who underwent hematopoietic stem-cell transplantation. CONCLUSION A personalized prediction model on the basis of clinical and genomic data outperformed established prognostic models in MDS. The new model was dynamic, predicting survival and leukemia transformation probabilities at different time points that are unique for a given patient, and can upstage and downstage patients into more appropriate risk categories.


2017 ◽  
Vol 7 ◽  
Author(s):  
Laiz Cameirão Bento ◽  
Rodolfo Patussi Correia ◽  
Cristóvão Luis Pitangueiras Mangueira ◽  
Rodrigo De Souza Barroso ◽  
Fernanda Agostini Rocha ◽  
...  

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