The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases
IntroductionMinimal residual disease (MRD) is commonly assessed in bone marrow (BM) aspirate. However, sample quality can impair the MRD measurement, leading to underestimated residual cells and to false negative results. To define a reliable and reproducible method for the assessment of BM hemodilu...
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Frontiers Media S.A.
2022-10-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.1001048/full |
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author | Ilaria Vigliotta Ilaria Vigliotta Silvia Armuzzi Silvia Armuzzi Martina Barone Martina Barone Vincenza Solli Vincenza Solli Ignazia Pistis Enrica Borsi Enrica Borsi Barbara Taurisano Barbara Taurisano Gaia Mazzocchetti Gaia Mazzocchetti Marina Martello Marina Martello Andrea Poletti Andrea Poletti Chiara Sartor Chiara Sartor Ilaria Rizzello Ilaria Rizzello Lucia Pantani Paola Tacchetti Cristina Papayannidis Katia Mancuso Katia Mancuso Serena Rocchi Serena Rocchi Elena Zamagni Elena Zamagni Antonio Curti Antonio Curti Mario Arpinati Mario Arpinati Michele Cavo Michele Cavo Carolina Terragna |
author_facet | Ilaria Vigliotta Ilaria Vigliotta Silvia Armuzzi Silvia Armuzzi Martina Barone Martina Barone Vincenza Solli Vincenza Solli Ignazia Pistis Enrica Borsi Enrica Borsi Barbara Taurisano Barbara Taurisano Gaia Mazzocchetti Gaia Mazzocchetti Marina Martello Marina Martello Andrea Poletti Andrea Poletti Chiara Sartor Chiara Sartor Ilaria Rizzello Ilaria Rizzello Lucia Pantani Paola Tacchetti Cristina Papayannidis Katia Mancuso Katia Mancuso Serena Rocchi Serena Rocchi Elena Zamagni Elena Zamagni Antonio Curti Antonio Curti Mario Arpinati Mario Arpinati Michele Cavo Michele Cavo Carolina Terragna |
author_sort | Ilaria Vigliotta |
collection | DOAJ |
description | IntroductionMinimal residual disease (MRD) is commonly assessed in bone marrow (BM) aspirate. However, sample quality can impair the MRD measurement, leading to underestimated residual cells and to false negative results. To define a reliable and reproducible method for the assessment of BM hemodilution, several flow cytometry (FC) strategies for hemodilution evaluation have been compared.MethodsFor each BM sample, cells populations with a well-known distribution in BM and peripheral blood - e.g., mast cells (MC), immature (IG) and mature granulocytes (N) – have been studied by FC and quantified alongside the BM differential count.ResultsThe frequencies of cells’ populations were correlated to the IG/N ratio, highlighting a mild correlation with MCs and erythroblasts (R=0.25 and R=0.38 respectively, with p-value=0.0006 and 0.0000052), whereas no significant correlation was found with B or T-cells. The mild correlation between IG/N, erythroblasts and MCs supported the combined use of these parameters to evaluate BM hemodilution, hence the optimization of the ALLgorithMM. Once validated, the ALLgorithMM was employed to evaluate the dilution status of BM samples in the context of MRD assessment. Overall, we found that 32% of FC and 52% of Next Generation Sequencing (NGS) analyses were MRD negative in samples resulted hemodiluted (HD) or at least mildly hemodiluted (mHD).ConclusionsThe high frequency of MRD-negative results in both HD and mHD samples implies the presence of possible false negative MRD measurements, impairing the correct assessment of patients’ response to therapy and highlighs the importance to evaluate BM hemodilution. |
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language | English |
last_indexed | 2024-04-11T10:29:02Z |
publishDate | 2022-10-01 |
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series | Frontiers in Oncology |
spelling | doaj.art-45f876f6faa8455682afb6ec6aa42bb92022-12-22T04:29:29ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-10-011210.3389/fonc.2022.10010481001048The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseasesIlaria Vigliotta0Ilaria Vigliotta1Silvia Armuzzi2Silvia Armuzzi3Martina Barone4Martina Barone5Vincenza Solli6Vincenza Solli7Ignazia Pistis8Enrica Borsi9Enrica Borsi10Barbara Taurisano11Barbara Taurisano12Gaia Mazzocchetti13Gaia Mazzocchetti14Marina Martello15Marina Martello16Andrea Poletti17Andrea Poletti18Chiara Sartor19Chiara Sartor20Ilaria Rizzello21Ilaria Rizzello22Lucia Pantani23Paola Tacchetti24Cristina Papayannidis25Katia Mancuso26Katia Mancuso27Serena Rocchi28Serena Rocchi29Elena Zamagni30Elena Zamagni31Antonio Curti32Antonio Curti33Mario Arpinati34Mario Arpinati35Michele Cavo36Michele Cavo37Carolina Terragna38IRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyDepartment of Experimental, Diagnostic and Specialty Medicine - University of Bologna, Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Seràgnoli Institute of Hematology, Bologna, ItalyIntroductionMinimal residual disease (MRD) is commonly assessed in bone marrow (BM) aspirate. However, sample quality can impair the MRD measurement, leading to underestimated residual cells and to false negative results. To define a reliable and reproducible method for the assessment of BM hemodilution, several flow cytometry (FC) strategies for hemodilution evaluation have been compared.MethodsFor each BM sample, cells populations with a well-known distribution in BM and peripheral blood - e.g., mast cells (MC), immature (IG) and mature granulocytes (N) – have been studied by FC and quantified alongside the BM differential count.ResultsThe frequencies of cells’ populations were correlated to the IG/N ratio, highlighting a mild correlation with MCs and erythroblasts (R=0.25 and R=0.38 respectively, with p-value=0.0006 and 0.0000052), whereas no significant correlation was found with B or T-cells. The mild correlation between IG/N, erythroblasts and MCs supported the combined use of these parameters to evaluate BM hemodilution, hence the optimization of the ALLgorithMM. Once validated, the ALLgorithMM was employed to evaluate the dilution status of BM samples in the context of MRD assessment. Overall, we found that 32% of FC and 52% of Next Generation Sequencing (NGS) analyses were MRD negative in samples resulted hemodiluted (HD) or at least mildly hemodiluted (mHD).ConclusionsThe high frequency of MRD-negative results in both HD and mHD samples implies the presence of possible false negative MRD measurements, impairing the correct assessment of patients’ response to therapy and highlighs the importance to evaluate BM hemodilution.https://www.frontiersin.org/articles/10.3389/fonc.2022.1001048/fullminimal residual diseasemultiple myelomaacute lymphoblastic leukemiahemodilutionhemodilution/methodsflow cytometry |
spellingShingle | Ilaria Vigliotta Ilaria Vigliotta Silvia Armuzzi Silvia Armuzzi Martina Barone Martina Barone Vincenza Solli Vincenza Solli Ignazia Pistis Enrica Borsi Enrica Borsi Barbara Taurisano Barbara Taurisano Gaia Mazzocchetti Gaia Mazzocchetti Marina Martello Marina Martello Andrea Poletti Andrea Poletti Chiara Sartor Chiara Sartor Ilaria Rizzello Ilaria Rizzello Lucia Pantani Paola Tacchetti Cristina Papayannidis Katia Mancuso Katia Mancuso Serena Rocchi Serena Rocchi Elena Zamagni Elena Zamagni Antonio Curti Antonio Curti Mario Arpinati Mario Arpinati Michele Cavo Michele Cavo Carolina Terragna The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases Frontiers in Oncology minimal residual disease multiple myeloma acute lymphoblastic leukemia hemodilution hemodilution/methods flow cytometry |
title | The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases |
title_full | The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases |
title_fullStr | The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases |
title_full_unstemmed | The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases |
title_short | The ALLgorithMM: How to define the hemodilution of bone marrow samples in lymphoproliferative diseases |
title_sort | allgorithmm how to define the hemodilution of bone marrow samples in lymphoproliferative diseases |
topic | minimal residual disease multiple myeloma acute lymphoblastic leukemia hemodilution hemodilution/methods flow cytometry |
url | https://www.frontiersin.org/articles/10.3389/fonc.2022.1001048/full |
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