Immunophenotypic differentiation patterns of normal hematopoiesis in human bone marrow: Reference patterns for age‐related changes and disease‐induced shifts
Background The abundance of monoclonal antibodies (mAb) and the routine use of quadruple stainings in flow cytometry allow stepwise analysis of bone marrow (BM) samples that are suspected for abnormal hematopoiesis. A screening phase that precedes lineage‐specific classification phases should be suf...
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Veröffentlicht in: | Cytometry. Part B, Clinical cytometry Clinical cytometry, 2004-07, Vol.60B (1), p.1-13 |
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creator | van Lochem, E.G. van der Velden, V.H.J. Wind, H.K. te Marvelde, J.G. Westerdaal, N.A.C. van Dongen, J.J.M. |
description | Background
The abundance of monoclonal antibodies (mAb) and the routine use of quadruple stainings in flow cytometry allow stepwise analysis of bone marrow (BM) samples that are suspected for abnormal hematopoiesis. A screening phase that precedes lineage‐specific classification phases should be sufficient to assess whether the BM has a normal or abnormal composition, as well as to identify the abnormal differentiation lineage.
Methods
For a quick and easy flow cytometric screening of BM samples, we selected six quadruple immunostainings that cover multiple differentiation stages of the B‐cell, monocytic, granulocytic, and erythroid lineages: TdT/CD20/CD19/CD10 and CD45/CD34/CD19/CD22 for B cells, CD34/CD117/CD45/CD13.33 for precursor granulocytic and precursor monocytic cells (myelo/monoblasts), CD14/CD33/CD45/CD34 for monocytic cells, CD16/CD13/CD45/CD11b for granulocytic cells, and CD71/CD235a/CD45/CD117 for erythroid cells.
Results
The six quadruple immunostainings reveal specific staining patterns in normal BM, which allow the recognition of various subpopulations of the respective lineages. These staining patterns can be used as a frame of reference for recognition of normal and abnormal BM development. Examples of normal (age‐related) variations in these otherwise stable staining patterns are presented together with several abnormal differentiation patterns.
Conclusions
Although alternative immunostainings can be used (e.g., including NK‐ and T‐cell markers), we feel that the selected six stainings represent a comprehensive and easy screening phase for quick identification of shifts in the composition of the studied differentiation lineages, reflecting age‐related changes or disease‐induced BM abnormalities. © 2004 Wiley‐Liss, Inc. |
doi_str_mv | 10.1002/cyto.b.20008 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_66654890</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>20379460</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4668-e42edcab991537c4ce90c3c5d6730ce9b1b1fe5a419e355d760e7af6c21198d73</originalsourceid><addsrcrecordid>eNqFkcFu1DAQhi1ERUvhxhn5xInd2ontxNzQikKlSpWqcuBkOfa4MUrsYDuq9tZH4BV4tT4J2e6K3uhpZjSfvpHmR-gdJWtKSHVmtiWuu3VFCGlfoBPKebVikjcv__VMHqPXOf8kpOZMNK_QMeVVRVvBTtCfi3GcQ5x6CLFsJ2-w9c5BglC8Lj4GPOlSIIWMo8MhplEPuIdRlzhFD9ln7APu51EH3MUAeNQpxbtP-BoeLQaeBC4mrG_h4f53gkEXsNj0OtxCxjrY5W4GnXdbH-xslm3uvSv5DTpyesjw9lBP0ffzLzebb6vLq68Xm8-XK8OEaFfAKrBGd1JSXjeGGZDE1IZb0dRkGTraUQdcMyqh5tw2gkCjnTAVpbK1TX2KPuy9U4q_ZshFjT4bGAYdIM5ZCSE4ayV5FqxI3UgmduDHPWhSzDmBU1Pyy3-2ihK1y07tslOdesxuwd8fvHM3gn2CD2EtQL0H7vwA2__K1ObHzdVe-xeuoqzD</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>20379460</pqid></control><display><type>article</type><title>Immunophenotypic differentiation patterns of normal hematopoiesis in human bone marrow: Reference patterns for age‐related changes and disease‐induced shifts</title><source>Wiley Free Content</source><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Alma/SFX Local Collection</source><creator>van Lochem, E.G. ; van der Velden, V.H.J. ; Wind, H.K. ; te Marvelde, J.G. ; Westerdaal, N.A.C. ; van Dongen, J.J.M.</creator><creatorcontrib>van Lochem, E.G. ; van der Velden, V.H.J. ; Wind, H.K. ; te Marvelde, J.G. ; Westerdaal, N.A.C. ; van Dongen, J.J.M.</creatorcontrib><description>Background
The abundance of monoclonal antibodies (mAb) and the routine use of quadruple stainings in flow cytometry allow stepwise analysis of bone marrow (BM) samples that are suspected for abnormal hematopoiesis. A screening phase that precedes lineage‐specific classification phases should be sufficient to assess whether the BM has a normal or abnormal composition, as well as to identify the abnormal differentiation lineage.
Methods
For a quick and easy flow cytometric screening of BM samples, we selected six quadruple immunostainings that cover multiple differentiation stages of the B‐cell, monocytic, granulocytic, and erythroid lineages: TdT/CD20/CD19/CD10 and CD45/CD34/CD19/CD22 for B cells, CD34/CD117/CD45/CD13.33 for precursor granulocytic and precursor monocytic cells (myelo/monoblasts), CD14/CD33/CD45/CD34 for monocytic cells, CD16/CD13/CD45/CD11b for granulocytic cells, and CD71/CD235a/CD45/CD117 for erythroid cells.
Results
The six quadruple immunostainings reveal specific staining patterns in normal BM, which allow the recognition of various subpopulations of the respective lineages. These staining patterns can be used as a frame of reference for recognition of normal and abnormal BM development. Examples of normal (age‐related) variations in these otherwise stable staining patterns are presented together with several abnormal differentiation patterns.
Conclusions
Although alternative immunostainings can be used (e.g., including NK‐ and T‐cell markers), we feel that the selected six stainings represent a comprehensive and easy screening phase for quick identification of shifts in the composition of the studied differentiation lineages, reflecting age‐related changes or disease‐induced BM abnormalities. © 2004 Wiley‐Liss, Inc.</description><identifier>ISSN: 1552-4949</identifier><identifier>EISSN: 1552-4957</identifier><identifier>DOI: 10.1002/cyto.b.20008</identifier><identifier>PMID: 15221864</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Aging - physiology ; B-Lymphocytes - cytology ; B-Lymphocytes - immunology ; Bone Marrow - immunology ; Bone Marrow - pathology ; Bone Marrow - physiology ; Bone Marrow Cells - cytology ; Bone Marrow Cells - immunology ; Cell Lineage ; Erythroid Cells - cytology ; Erythroid Cells - immunology ; expression profile ; Flow Cytometry ; Granulocytes - cytology ; Granulocytes - immunology ; Hematologic Diseases - pathology ; Hematopoiesis ; Humans ; Immunophenotyping ; Monocytes - cytology ; Monocytes - immunology ; normal bone marrow ; Reference Values ; staining patterns</subject><ispartof>Cytometry. Part B, Clinical cytometry, 2004-07, Vol.60B (1), p.1-13</ispartof><rights>Copyright © 2004 Wiley‐Liss, Inc.</rights><rights>Copyright 2004 Wiley-Liss, Inc.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4668-e42edcab991537c4ce90c3c5d6730ce9b1b1fe5a419e355d760e7af6c21198d73</citedby><cites>FETCH-LOGICAL-c4668-e42edcab991537c4ce90c3c5d6730ce9b1b1fe5a419e355d760e7af6c21198d73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fcyto.b.20008$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fcyto.b.20008$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15221864$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>van Lochem, E.G.</creatorcontrib><creatorcontrib>van der Velden, V.H.J.</creatorcontrib><creatorcontrib>Wind, H.K.</creatorcontrib><creatorcontrib>te Marvelde, J.G.</creatorcontrib><creatorcontrib>Westerdaal, N.A.C.</creatorcontrib><creatorcontrib>van Dongen, J.J.M.</creatorcontrib><title>Immunophenotypic differentiation patterns of normal hematopoiesis in human bone marrow: Reference patterns for age‐related changes and disease‐induced shifts</title><title>Cytometry. Part B, Clinical cytometry</title><addtitle>Cytometry B Clin Cytom</addtitle><description>Background
The abundance of monoclonal antibodies (mAb) and the routine use of quadruple stainings in flow cytometry allow stepwise analysis of bone marrow (BM) samples that are suspected for abnormal hematopoiesis. A screening phase that precedes lineage‐specific classification phases should be sufficient to assess whether the BM has a normal or abnormal composition, as well as to identify the abnormal differentiation lineage.
Methods
For a quick and easy flow cytometric screening of BM samples, we selected six quadruple immunostainings that cover multiple differentiation stages of the B‐cell, monocytic, granulocytic, and erythroid lineages: TdT/CD20/CD19/CD10 and CD45/CD34/CD19/CD22 for B cells, CD34/CD117/CD45/CD13.33 for precursor granulocytic and precursor monocytic cells (myelo/monoblasts), CD14/CD33/CD45/CD34 for monocytic cells, CD16/CD13/CD45/CD11b for granulocytic cells, and CD71/CD235a/CD45/CD117 for erythroid cells.
Results
The six quadruple immunostainings reveal specific staining patterns in normal BM, which allow the recognition of various subpopulations of the respective lineages. These staining patterns can be used as a frame of reference for recognition of normal and abnormal BM development. Examples of normal (age‐related) variations in these otherwise stable staining patterns are presented together with several abnormal differentiation patterns.
Conclusions
Although alternative immunostainings can be used (e.g., including NK‐ and T‐cell markers), we feel that the selected six stainings represent a comprehensive and easy screening phase for quick identification of shifts in the composition of the studied differentiation lineages, reflecting age‐related changes or disease‐induced BM abnormalities. © 2004 Wiley‐Liss, Inc.</description><subject>Aging - physiology</subject><subject>B-Lymphocytes - cytology</subject><subject>B-Lymphocytes - immunology</subject><subject>Bone Marrow - immunology</subject><subject>Bone Marrow - pathology</subject><subject>Bone Marrow - physiology</subject><subject>Bone Marrow Cells - cytology</subject><subject>Bone Marrow Cells - immunology</subject><subject>Cell Lineage</subject><subject>Erythroid Cells - cytology</subject><subject>Erythroid Cells - immunology</subject><subject>expression profile</subject><subject>Flow Cytometry</subject><subject>Granulocytes - cytology</subject><subject>Granulocytes - immunology</subject><subject>Hematologic Diseases - pathology</subject><subject>Hematopoiesis</subject><subject>Humans</subject><subject>Immunophenotyping</subject><subject>Monocytes - cytology</subject><subject>Monocytes - immunology</subject><subject>normal bone marrow</subject><subject>Reference Values</subject><subject>staining patterns</subject><issn>1552-4949</issn><issn>1552-4957</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkcFu1DAQhi1ERUvhxhn5xInd2ontxNzQikKlSpWqcuBkOfa4MUrsYDuq9tZH4BV4tT4J2e6K3uhpZjSfvpHmR-gdJWtKSHVmtiWuu3VFCGlfoBPKebVikjcv__VMHqPXOf8kpOZMNK_QMeVVRVvBTtCfi3GcQ5x6CLFsJ2-w9c5BglC8Lj4GPOlSIIWMo8MhplEPuIdRlzhFD9ln7APu51EH3MUAeNQpxbtP-BoeLQaeBC4mrG_h4f53gkEXsNj0OtxCxjrY5W4GnXdbH-xslm3uvSv5DTpyesjw9lBP0ffzLzebb6vLq68Xm8-XK8OEaFfAKrBGd1JSXjeGGZDE1IZb0dRkGTraUQdcMyqh5tw2gkCjnTAVpbK1TX2KPuy9U4q_ZshFjT4bGAYdIM5ZCSE4ayV5FqxI3UgmduDHPWhSzDmBU1Pyy3-2ihK1y07tslOdesxuwd8fvHM3gn2CD2EtQL0H7vwA2__K1ObHzdVe-xeuoqzD</recordid><startdate>200407</startdate><enddate>200407</enddate><creator>van Lochem, E.G.</creator><creator>van der Velden, V.H.J.</creator><creator>Wind, H.K.</creator><creator>te Marvelde, J.G.</creator><creator>Westerdaal, N.A.C.</creator><creator>van Dongen, J.J.M.</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>200407</creationdate><title>Immunophenotypic differentiation patterns of normal hematopoiesis in human bone marrow: Reference patterns for age‐related changes and disease‐induced shifts</title><author>van Lochem, E.G. ; van der Velden, V.H.J. ; Wind, H.K. ; te Marvelde, J.G. ; Westerdaal, N.A.C. ; van Dongen, J.J.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4668-e42edcab991537c4ce90c3c5d6730ce9b1b1fe5a419e355d760e7af6c21198d73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Aging - physiology</topic><topic>B-Lymphocytes - cytology</topic><topic>B-Lymphocytes - immunology</topic><topic>Bone Marrow - immunology</topic><topic>Bone Marrow - pathology</topic><topic>Bone Marrow - physiology</topic><topic>Bone Marrow Cells - cytology</topic><topic>Bone Marrow Cells - immunology</topic><topic>Cell Lineage</topic><topic>Erythroid Cells - cytology</topic><topic>Erythroid Cells - immunology</topic><topic>expression profile</topic><topic>Flow Cytometry</topic><topic>Granulocytes - cytology</topic><topic>Granulocytes - immunology</topic><topic>Hematologic Diseases - pathology</topic><topic>Hematopoiesis</topic><topic>Humans</topic><topic>Immunophenotyping</topic><topic>Monocytes - cytology</topic><topic>Monocytes - immunology</topic><topic>normal bone marrow</topic><topic>Reference Values</topic><topic>staining patterns</topic><toplevel>online_resources</toplevel><creatorcontrib>van Lochem, E.G.</creatorcontrib><creatorcontrib>van der Velden, V.H.J.</creatorcontrib><creatorcontrib>Wind, H.K.</creatorcontrib><creatorcontrib>te Marvelde, J.G.</creatorcontrib><creatorcontrib>Westerdaal, N.A.C.</creatorcontrib><creatorcontrib>van Dongen, J.J.M.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Cytometry. Part B, Clinical cytometry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>van Lochem, E.G.</au><au>van der Velden, V.H.J.</au><au>Wind, H.K.</au><au>te Marvelde, J.G.</au><au>Westerdaal, N.A.C.</au><au>van Dongen, J.J.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Immunophenotypic differentiation patterns of normal hematopoiesis in human bone marrow: Reference patterns for age‐related changes and disease‐induced shifts</atitle><jtitle>Cytometry. Part B, Clinical cytometry</jtitle><addtitle>Cytometry B Clin Cytom</addtitle><date>2004-07</date><risdate>2004</risdate><volume>60B</volume><issue>1</issue><spage>1</spage><epage>13</epage><pages>1-13</pages><issn>1552-4949</issn><eissn>1552-4957</eissn><abstract>Background
The abundance of monoclonal antibodies (mAb) and the routine use of quadruple stainings in flow cytometry allow stepwise analysis of bone marrow (BM) samples that are suspected for abnormal hematopoiesis. A screening phase that precedes lineage‐specific classification phases should be sufficient to assess whether the BM has a normal or abnormal composition, as well as to identify the abnormal differentiation lineage.
Methods
For a quick and easy flow cytometric screening of BM samples, we selected six quadruple immunostainings that cover multiple differentiation stages of the B‐cell, monocytic, granulocytic, and erythroid lineages: TdT/CD20/CD19/CD10 and CD45/CD34/CD19/CD22 for B cells, CD34/CD117/CD45/CD13.33 for precursor granulocytic and precursor monocytic cells (myelo/monoblasts), CD14/CD33/CD45/CD34 for monocytic cells, CD16/CD13/CD45/CD11b for granulocytic cells, and CD71/CD235a/CD45/CD117 for erythroid cells.
Results
The six quadruple immunostainings reveal specific staining patterns in normal BM, which allow the recognition of various subpopulations of the respective lineages. These staining patterns can be used as a frame of reference for recognition of normal and abnormal BM development. Examples of normal (age‐related) variations in these otherwise stable staining patterns are presented together with several abnormal differentiation patterns.
Conclusions
Although alternative immunostainings can be used (e.g., including NK‐ and T‐cell markers), we feel that the selected six stainings represent a comprehensive and easy screening phase for quick identification of shifts in the composition of the studied differentiation lineages, reflecting age‐related changes or disease‐induced BM abnormalities. © 2004 Wiley‐Liss, Inc.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>15221864</pmid><doi>10.1002/cyto.b.20008</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aging - physiology B-Lymphocytes - cytology B-Lymphocytes - immunology Bone Marrow - immunology Bone Marrow - pathology Bone Marrow - physiology Bone Marrow Cells - cytology Bone Marrow Cells - immunology Cell Lineage Erythroid Cells - cytology Erythroid Cells - immunology expression profile Flow Cytometry Granulocytes - cytology Granulocytes - immunology Hematologic Diseases - pathology Hematopoiesis Humans Immunophenotyping Monocytes - cytology Monocytes - immunology normal bone marrow Reference Values staining patterns |
title | Immunophenotypic differentiation patterns of normal hematopoiesis in human bone marrow: Reference patterns for age‐related changes and disease‐induced shifts |
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