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Impact on outcomes of mixed chimerism of bone marrow CD34+ sorted cells after matched or haploidentical allogeneic stem cell transplantation for myeloid malignancies


Allogeneic hematopoietic stem cell transplantation (Allo-HSCT), proposed to patients with high-risk myeloid malignancies, may ultimately fail because of disease relapse. Bone marrow (BM) CD34+ cells in Allo-HSCT recipients can be either re-emerging recipient malignant cells or donor cells attesting of hematopoietic reconstitution. In this context, investigating donor/recipient chimerism in the population of BM CD34+ sorted cells (BM-CD34+SC) was performed in 261 Allo-HSCT recipients (matched n = 145, haploidentical n = 65, matched unrelated n = 51) with myeloid malignancies. BM-CD34+SC chimerism was compared to that of whole peripheral blood (PB) cells as well as other Allo-HSCT-related parameters, and impact on relapse and survival was assessed. Thresholds of 98% donor cells for PB and 90% for BM-CD34+SC were found to allow relapse prediction. This was completed by the application of machine learning tools to explore the predictive value of these parameters in multidimensional models with repeated iterations. BM-CD34+SC mixed chimerism stood out with all these methods as the most robust predictor of relapse with a significant impact on disease-free and overall survivals even after haploidentical Allo-HSCT and/or PTCY administration. This marker therefore appears to be of great interest for the decision of preemptive treatment to avoid post-transplant relapse.

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Fig. 1: Impact of BM CD34+SC chemotherapy on patient survivals.
Fig. 2: Features importance in predicting relapse with a Random Forest classifier, based on 100 iterations.

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All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.


  1. Ruggeri A, Sun Y, Labopin M, Bacigalupo A, Lorentino F, Arcese W, et al. Post-transplant cyclophosphamide versus anti-thymocyte globulin as graft- versus-host disease prophylaxis in haploidentical transplant. Haematologica. 2017;102:401–10.

    Article  Google Scholar 

  2. Ruggeri A, Labopin M, Bacigalupo A, Afanasyev B, Cornelissen JJ, Elmaagacli A, et al. Post-transplant cyclophosphamide for graft-versus-host disease prophylaxis in HLA matched sibling or matched unrelated donor transplant for patients with acute leukemia, on behalf of ALWP-EBMT. J Hematol Oncol. 2018;11:40.

    Article  Google Scholar 

  3. Alizadeh M, Bernard M, Danic B, Dauriac C, Birebent B, Lapart C, et al. Quantitative assessment of hematopoietic chimerism after bone marrow transplantation by real-time quantitative polymerase chain reaction. Blood. 2002;99:4618–25.

    CAS  Article  Google Scholar 

  4. Lange T, Hubmann M, Burkhardt R, Franke GN, Cross M, Scholz M, et al. Monitoring of WT1 expression in PB and CD34(+) donor chimerism of BM predicts early relapse in AML and MDS patients after hematopoietic cell transplantation with reduced-intensity conditioning. Leukemia. 2011;25:498–505.

    CAS  Article  Google Scholar 

  5. Bornhäuser M, Oelschlaegel U, Platzbecker U, Bug G, Lutterbeck K, Kiehl MG, et al. Monitoring of donor chimerism in sorted CD34+ peripheral blood cells allows the sensitive detection of imminent relapse after allogeneic stem cell transplantation. Haematologica. 2009;94:1613–7.

    Article  Google Scholar 

  6. Hoffmann JC, Stabla K, Burchert A, Volkmann T, Bornhäuser M, Thiede C, et al. Monitoring of acute myeloid leukemia patients after allogeneic stem cell transplantation employing semi-automated CD34+ donor cell chimerism analysis. Ann Hematol. 2014;93:279–85.

    CAS  Article  Google Scholar 

  7. Lacombe F, Campos L, Allou K, Arnoulet C, Delabarthe A, Dumezy F, et al. Prognostic value of multicenter flow cytometry harmonized assessment of minimal residual disease in acute myeloblastic leukemia. Hematological Oncol. 2018;36:422–8.

    CAS  Article  Google Scholar 

  8. Diaz-Blanco E, Bruns I, Neumann F, Fischer JC, Graef T, Rosskopf M, et al. Molecular signature of CD34(+) hematopoietic stem and progenitor cells of patients with CML in chronic phase. Leukemia. 2007;21:494–504.

    CAS  Article  Google Scholar 

  9. Catani L, Zini R, Sollazzo D, Ottaviani E, Vannucchi AM, Ferrari S, et al. Molecular profile of CD34+ stem/progenitor cells according to JAK2V617F mutation status in essential thrombocythemia. Leukemia. 2009;23:997–1000.

    CAS  Article  Google Scholar 

  10. Desjonqueres A, Illiaquer M, Duquesne A, Le Bris Y, Peterlin P, Guillaume T, et al. Longer delay of hematological recovery and increased transfusion needs after haploidentical compared to non-haploidentical stem cell transplantation. Bone Marrow Transpl. 2016;51:1150–2.

    CAS  Article  Google Scholar 

  11. Liu J, Ma R, Liu YR, Xu LP, Zhang XH, Chen H, et al. The significance of peri-transplantation minimal residual disease assessed by multiparameter flow cytometry on outcomes for adult AML patients receiving haploidentical allografts. Bone Marrow Transpl. 2018;54:567–77.

    Article  Google Scholar 

  12. Qin XY, Li GX, Qin YZ, Wang Y, Wang FR, Liu DH, et al. Quantitative chimerism: an independent acute leukemia prognosis indicator following allogeneic hematopoietic SCT. Bone Marrow Transpl. 2014;49:1269–77.

    CAS  Article  Google Scholar 

  13. Qin XY, Li GX, Qin YZ, Wang Y, Wang FR, Liu DH, et al. Machine learning applications for prediction of relapse in childhood acute lymphoblastic leukemia. Sci Rep. 2017;7:7402.

    Article  Google Scholar 

  14. Fuse K, Uemura S, Tamura S, Suwabe T, Katagiri T, Tanaka T, et al. Patient-based prediction algorithm of relapse after allo-HSCT for acute leukemia and its usefulness in the decision-making process using a machine learning approach. Cancer Med. 2019;8:5058–67.

    Article  Google Scholar 

  15. Norkin M, Katragadda L, Zou F, Xiong S, Chang M, Dai Y, et al. Minimal residual disease by either flow cytometry or cytogenetics prior to an allogeneic hematopoietic stem cell transplant is associated with poor outcome in acute myeloid leukemia. Blood Cancer J. 2017;7:634.

    Article  Google Scholar 

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The authors are grateful to the technical staff in the molecular hematology laboratory of Nantes Hematology Biology department for their involvement in the study.

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Authors and Affiliations



YLB designed the study, analyzed the data, performed statistics and wrote the manuscript. DC collected clinical information and AlloHSCT outcomes from the patient files. RB designed and performed machine learning analyzes. TG, PP and AG managed the patients and supervised sampling. PC designed the study, provided samples, contributed to data analysis and wrote the manuscript. MCB performed analyzes and wrote the manuscript.

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Correspondence to Yannick Le Bris.

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Le Bris, Y., Costes, D., Bourgade, R. et al. Impact on outcomes of mixed chimerism of bone marrow CD34+ sorted cells after matched or haploidentical allogeneic stem cell transplantation for myeloid malignancies. Bone Marrow Transplant (2022).

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