Role of Flow Role of Flow Cytometry Cytometry in...

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Role of Flow Role of Flow Cytometry Cytometry in Myeloma: in Myeloma: New Diagnosis and MRD New Diagnosis and MRD Steven H. Kroft, MD Steven H. Kroft, MD Professor and Director of Professor and Director of Hematopathology Hematopathology Medical College of Wisconsin Medical College of Wisconsin

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  • Role of Flow Role of Flow CytometryCytometry in Myeloma: in Myeloma:

    New Diagnosis and MRDNew Diagnosis and MRD

    Steven H. Kroft, MDSteven H. Kroft, MD

    Professor and Director of Professor and Director of HematopathologyHematopathology

    Medical College of WisconsinMedical College of Wisconsin

  • Outline

    Technical issues


  • Outline



  • The Immunophenotype of Normal

    Plasma CellsCD38 bright

    CD19(+) CD20(-)

    Normal Plasma Cells Normal B cells Granulocytes Monocytes

    Polytypic Light



  • CD38 on Normal Marrow Populations

    Plasma Cells

    HematogonesT Cells


    Mature B cellsGranulocytes

    T Cells

  • Other Features of Normal Plasma Cells




    CD52(-) CD52(-)


  • Typical MyelomaCD19(-)

    Myeloma Cells Normal B cells

    CD56(+)Monotypic cytoplasmic Ig

  • Technical Issues



  • General Technical Point #1:

    Myeloma Cells Dont Show Predictable FS/SS and CD45/SS Patterns

  • Myeloma cells stick

    to things

    General Technical Point #2

  • CD10(+)?

    CD19(dim+) CD20(dim+)?

    Myeloma cells T cells B cells

    General Technical Point #3

    Myeloma cells often have a lot of autofluorescence

  • CD10(-)

    CD19(-) CD20(-)

    Myeloma cells T cells B cells

    General Technical Point #3

    Myeloma cells often have a lot of autofluorescence

  • General Technical Point #4:

    Myeloma Cells Are Under-Represented in FC Analyses

    60-70% average decrement compared to aspirate differential count (Smock et al, Arch Pathol Lab Med 2007;131:951-955; Nadav et al, Br J Haematol 2006;133:530-532; Paiva Haematologica 2009;94:1599-1602)

    Causes? Causes? Hemodilution

    Different distribution of plasma cells in particle-associated and liquid marrow components than other cellular elements?

    Loss in processing

  • MRD Analysis

    1/10,000 (10-4) at day 100 after auto HSCT appears to be clinically relevant threshold

    ASO PCR Sensitivity of 10-6

    Applicable to 75% of cases Applicable to 75% of cases Expensive, time consuming, limited availability

    Flow Sensitivity of 10-4 with current methodology

    Simply report as positive or negative

    Applicable to nearly all cases Inexpensive, rapid, widely available



  • Technical Issues for MRD Analysis

    How to gate?

    What antibodies to use?

    How many events?

    How many colors? How many colors?

    Immunophenotypic instability

  • CD38 in Myeloma

    Myeloma cells often have dimmer

    CD38 than normal plasma cells

  • CD38 in Myeloma

    Myeloma cells often have dimmer

    CD38 than normal plasma cells

    Usually still brighter than

    other CD38(+) cells (such

    as hematogones)

    but not always.

    Granulocytes Monocytes

  • CD38 in Myeloma

    Myeloma cells often have dimmer

    CD38 than normal plasma cells

    Small numbers

    of junk events

    Usually still brighter than

    other CD38(+) cells (such

    as hematogones)

    but not always.

    Granulocytes Monocytes

    of junk events

  • CD138 in Myeloma

    Improves both sensitivity and specificity Specific for plasma cells among hematolymphoid cells

    Expressed on virtually all normal and neoplastic plasma cells

    Brighter on myeloma than normal plasma cells

    Technical issues (clone, lyse, refrigeration)

  • Gating Strategies

    Gating Strategy % sensitivity

    CD38 84.1%

    CD138 76.6%

    CD38 and CD45 90.7%

    CD138 and CD45 79.4%

    CD38 and CD138 98.1%

    CD38, CD138, and CD45* 100.0%

    From: Gupta et al, AJCP 2009;132:728-732

  • Antibodies

    Detection of MRD generally based on aberrant antigen expression, not line chain restriction

    Cytoplasmic light chains not strictly necessary for

    MRD detectionMRD detection

    CD19 and CD56 will allow detection of >90% of cases

    Addition of several more frequently aberrant antigens will allow nearly 100% detection

  • Antigen Frequency of


    CD19 95%

    CD20 15-20%

    CD27 40-50%

    CD28 15-45%

    CD52 15-45%

    CD56 75%

    CD117 33%

    CD200 80%

    Myeloma cells (0.32%) Normal PCs (0.15%) Mature B cells

  • Events to Acquire

    European Myeloma Network recommends a minimum of 100 aberrant plasma cell events

    to call a positive result

    Conservative (20 events is typical Conservative (20 events is typical

    recommendation for MRD analysis)

    100 events need not be acquired in a single tube


    Rawstron et al, Haematologica 2008;93:431-438

  • How Many Colors?

    Minimum of three colors

    Sensitivity of 10-4 achievable with multi-tube assay

    (Rawstron et al, Blood 2002;100:3095-3100)

    No clear enhancement of sensitivity with up No clear enhancement of sensitivity with up to 6 colors (de Tute et al, Leukemia 2007;21:2046-2047)

  • Immunophenotypic Stability

    Over Time


    Gains, losses, changes in level of expression in

    commonly assessed antigens in about 1/3 of cases

    CD19 CD20 CD45 CD56

    Gain 3 2 4 1

    Loss 1 1 1

    Gain followed by loss 2

    Change in intensity 5 1

    Total 3 (6.3%) 3 (6.3%) 12 (25%) 3 (6.3%)


  • WHY

    Diagnostic Prognostic Therapeutic Diagnostic









  • usually

    Unusual morphologic variants of myeloma

    Florid reactive plasmacytosis

    Non-Hodgkin lymphomas with prominent plasmacytic differentiationplasmacytic differentiation

  • Myeloma


  • Lymphoplasmacytic Lymphoma

    Reactive Plasmacytosis (HIV)

    Lymphoplasmacytic Lymphoma

  • CD19(+) PCs:


    MM--5% Surface LC(+) PCs:



    NHL with plasmacytic


    Seegmiller et al, AJCP 2007;127:176-181

    CD45: 91% v. 41%

    CD56: 33% v. 71%Abnormal B-cell


  • Other Diagnostic Issues

    Prediction of genetic abnormalities

    Insufficiently robust

    Distinction of myeloma from MGUS

    Ratio of abnormal to total marrow plasma cells Ratio of abnormal to total marrow plasma cells

    (97% threshold: Ocqueteau et al, Am J Pathol 1998;152:1655-1665)

  • Progression of MGUS

    Perez-Persona et al, Blood 2007;110:2586-2592

  • WHY

    Diagnostic Prognostic Therapeutic Diagnostic






  • Prognostic Issues

    Qualitative immunophenotypic features

    Quantitative features (at diagnosis)

    Minimal residual disease

  • 5% of myelomas are CD19(+)


    Not significant in

    multivariate analysis

    Mateo et al, J Clin Oncol 2008;26:2737-2744

  • One third of myelomas are CD117(+)


    Not significant in

    multivariate analysis

    Mateo et al, J Clin Oncol 2008;26:2737-2744

  • 36% of myelomas are CD28(+)


    Not significant in

    multivariate analysis

    Mateo et al, J Clin Oncol 2008;26:2737-2744

  • but not when

    cytogenetics are included

    Significant in multivariate


    Combined CD28 and CD117

    Mateo et al, J Clin Oncol 2008;26:2737-2744

  • CD200 is expressed in 80% of myelomas

    UnfavorableCytogenetics not

    included in multivariate


    Moreaux et al, Blood 2006;108:4194-4197



    *Expression array data

  • CD56 is negative in 1/4 of myelomas

    Prognostic impact?

    Mateo et al, J Clin Oncol 2008;26:2737-2744

  • N=70


    Sahara et al, Br J Haematol 2002;117:882-885Sahara et al, Br J Haematol 2002;117:882-885

    Pellat-Deceunynck et al, Leukemia 1998;12:1977-1982

    Rawstron et al, Br J Haematol 1999;104:138-143

    CD56(-) myeloma associated with:

    PB involvement and frank plasma cell leukemia

    High BM tumor burden

    Extramedullary tumors

    Less osteolytic tendency

  • CD45 is expressed in 18-75% of myelomas

    Technical issues

    Controversial prognostic significance Favorable in one retrospective series of 95


    Favorable in one retrospective series of 95

    patients(Moreau et al, Haematologica 2004;89:547-551)

    No impact in prospective series of 685 patients (Mateo et al, J Clin Oncol 2008;26:2737-2744)

  • Quantitative Issues at Diagnosis

    Myeloma cells as a percentage of total cells

    Myeloma cells as % of total plasma cells

  • MorphNS in




    Paiva et al, Haematologica 2009;94:1599-1602

    Significant in



  • Paiva et al, Haematologica 2009;94:1599-1602

  • Persistence of Normal Plasma Cells Most myelomas have few or

    no normal residual plasma cells at diagnosis

    NS in multivariate analysis including cytogenetics (N=176)

    >5% normal plasma cells associated with cells associated with other favorable prognostic indicators

    Fewer high-risk cytogenetic changes

    Higher rate of CD117 expression

    Paiva et al, Blood 2009;4369-4372

  • Progression of Smoldering Myeloma

    Perez-Persona et al, Blood 2007;110:2586-2592

  • Why else do flow on

    myelomas at diagnosis?

    Immunophenotypic Immunophenotypic

    fingerprint for MRD


  • MRD Matters

    Blood 2008;112:4017-4023

  • Day 100 MRD s/p ASCT

    All patients (N=295)

    Paiva et al, Blood 2008:4017-4023

    58% of patients MRD positive, with median level of 0.14% (range .01-4%)

  • Day 100 MRD s/p ASCT

    CR patients* (N=147)

    Paiva et al, Blood 2008:4017-4023

    *1998 EBMT Criteria (

  • Day 100 MRD s/p ASCT

    All patients (N=295)

    MRD v. IFX

    Paiva et al, Blood 2008:4017-4023

  • Pre-Transplant and Day 100 MRD


    Paiva et al, Blood 2008:4017-4023

  • WHY

    Diagnostic Prognostic Therapeutic Diagnostic






  • Therapeutic Targets

    CD20 is expressed in ~15-25% of myelomas

    Disappointing responses in several small phase II

    trials with single agent Rituximabtrials with single agent Rituximab

    CD52 is expressed by 15-45% of myelomas

    Expressed at low levels (Rawstron, 2006)

  • 1

    Role of Flow Cytometry in Myeloma

    New Diagnosis and Minimal Residual Disease

    Society For Hematopathology Companion Meeting

    March 21, 2009

    Steven H Kroft, MD

    Medical College of Wisconsin


    While flow cytometry is an important and well-established ancillary study in many

    areas of neoplastic hematopathology, its role in the diagnosis and follow-up of

    plasma cell myeloma has been less clear-cut. In recent years, however, a number of

    investigators have provided data supporting a role for flow cytometry in this

    disorder, both at diagnosis and during follow-up. The first part of this review will

    discuss technical issues in analyzing plasma cells by flow cytometry, and the second

    will be devoted to the rationale for the use of flow cytometry in plasma cell

    myeloma. Prior to discussing these issues, a brief introduction to the general

    immunophenotypic features of normal and myeloma plasma cells is warranted.

    Plasma cells are classically defined immunophenotypically by bright CD38

    expression. However, CD38 is not specific for plasma cells, being expressed at

    various levels by virtually all other nucleated marrow subsets. Notably, though,

    normal plasma cells express higher levels of CD38 than any other normal cell

    population. However, it should be noted that doublets of other populations can

    express levels of CD38 similar to plasma cells, rendering a degree of non-specificity

    to CD38 as a sole marker for the identification of plasma cells, particularly when

    they are few in number. In addition to CD38, at least the large majority of normal

    plasma cells express CD19 and CD45, whereas they lack CD20 and CD56. Normal

    plasma cells express polytypic cytoplasmic immunoglobulin, with kappa:lambda

    ratios usually in the range of 1-2:1, but occasionally as high as 4:1 in reactive

    plasmacytoses. Additional immunophenotypic findings in normal plasma cells

    include lack of CD117 and CD52, dim CD200, dim/negative expression of CD28, and

    bright expression of CD27.

    The typical immunophenotype of myeloma cells includes expression of CD56, lack of

    CD19 and CD20, and monotypic cytoplasmic immunoglobulin expression. Other

    immunophenotypic features of myeloma, as well as deviations from this typical

    pattern, will be discussed in the remainder of this review.

    Technical Issues

  • 2

    A number of technical issues may be encountered in the flow cytometric evaluation

    of myeloma that may complicate analysis. I have broadly divided them into general

    technical issues, and those more specific to minimal residual disease (MRD)


    General Technical Issues

    Myeloma cells dont show predictable forward scatter/side scatter and CD45/side

    scatter patterns.

    Myeloma cells can fall pretty much anywhere with respect to their light scatter and

    CD45 characteristics. Traditional gating approaches using these parameters are

    thus inadequate for myeloma, and gating must be made on other fluorescence

    parameters, such as CD38 and/or CD138. This issue will be discussed in more detail


    Myeloma cells tend to stick to other cells.

    In my experience, myeloma cells tend to stick to other cell types, particularly

    granulocytes, potentially confusing interpretation of antigen expression, such as

    CD45 and CD10. This phenomenon may be partly responsible for the widely varying

    reports of the prevalence of expression of these antigens in myeloma. Viewing the

    plasma cell populations in a CD45/SS scatter plot will generally provide clear

    discrimination between myeloma cells and myeloma/granulocyte doublets.

    Myeloma cells often show high levels of autofluorescence.

    Because of typically high levels of autofluorescence, comparison of antigen

    expression to internal negative populations (e.g., B cells or T cells) can lead to false

    positive assessments. This is another factor that may be partly responsible for

    conflicting data regarding prevalence of antigen expression in the literature. In my

    laboratory, we include an isotype control containing CD38, in order to assess non-

    specific fluorescence on plasma cells.

    Myeloma cells are generally under-represented in flow cytometric analysis.

    There is universal consensus that myeloma cells are generally under-represented in

    flow cytometric analyses compared to morphology. However, the causes of this are

    not entirely clear. The decrement is generally attributed to hemodilution in a

    second pull bone marrow aspirate (Rawstron, 2008). However, it often appears

    that plasma cells are disproportionately depleted compared to other elements that

    would be expected to be affected similarly by hemodilution (e.g., blasts)(Nadav,

    2006). One explanation is that plasma cells may be differentially distributed in the

    liquid versus particle portions of the bone marrow aspirate, and thus may be

    disproportionately depleted relative to other cellular elements in less particle-rich

    aspirate specimens (Nadav, 2006). The percentage of plasma cells enumerated by

    flow cytometry is on average 60-70% lower than morphologic differential counts on

    first pull aspirates, and may be greater than an order of magnitude lower (Smock,

    2007; Nadav, 2006; Pavia, 2009). Smock et al (2007) studied plasma cell recovery

  • 3

    by flow cytometry in 30 bone marrow containing at least 10% plasma cells. They

    found an average 70% decrement in the plasma cell percentage in flow cytometric

    analyses compared to that obtained by differential count. In only two of 30 cases

    were the numbers of plasma cells obtained by the two methods similar. Notably,

    these authors also prepared smears from the pre-processed flow cytometry

    specimens, and found that these had fewer plasma cells than the first pull aspirates,

    but still considerably more on average than were recovered by flow cytometry. It is

    possible that other factors affect the survival of plasma cells during processing, such

    as physical characteristics of the plasma cells.

    Technical Issues Related to MRD Analysis

    A relatively limited literature exists describing MRD analysis following autologous

    stem cell transplantation. It appears that the clinically relevant threshold for MRD

    in this setting is 0.01% (10-4)(Sarasquete, 2005; Bakkus, 2004; Fenk, 2004;

    Rawstron, 2002). Presently, there are two methods available to achieve this level of

    sensitivity: PCR using allele-specific oligonucleotides (ASO-PCR) and flow

    cytometry. ASO-PCR has the advantage of being more sensitive than flow cytometry

    (10-6), but is only applicable to 75% of patients. Additionally, it is expensive, time

    consuming, and not widely available. Flow cytometry is applicable to almost all

    patients, and is rapid, inexpensive, and widely available. The current level of

    sensitivity of published flow cytometry assays is right at the 10-4 level required for

    clinical relevance. Recent clinical studies using flow cytometry have typically

    reported results as positive or negative; this seems warranted given the issues

    regarding plasma cell enumeration discussed earlier. However, it should be noted

    that increasing levels of MRD have been shown by ASO analysis to be associated

    with increased risk of relapse (Sarasquete, 2005), so a single 10-4 threshold may be

    overly simplistic. It is also notable that ASO-PCR and flow cytometry produce very

    similar results (Sarasquete, 2005).

    Gating Strategies

    As discussed earlier, because of the wide variability in CD45 expression and light

    scatter characteristics in myeloma, gating requires the use of specific antigens.

    Gating on bright CD38(+) events is the most widely used approach to myeloma, and

    this suffices at diagnosis. However, in the setting of minimal residual disease

    analysis, bright CD38 gating alone is insufficiently sensitive or specific. Myeloma

    cells typically have dimmer CD38 than normal plasma cells, although fortunately the

    level of CD38 generally is still higher than other marrow populations. In some

    instances, however, the level of CD38 expression overlaps with that of other

    populations, precluding detection in small numbers using CD38 gating.

    Furthermore, as indicated earlier, non-plasma cell events may occupy the bright

    CD38 region in small numbers. While not a problem when many plasma cells are

    present (e.g., at diagnosis), when very few plasma cells are present, these non-

    plasma cell CD38(bright) events can result in spurious results. Consequently, MRD

    analysis in myeloma requires gating on more than one marker.

  • 4

    CD138 has emerged as a favored marker for MRD gating. This antigen is essentially

    specific for plasma cells amongst hematolymphoid cells and is expressed by

    essentially 100% of myelomas (Lin 2004; Bataille, 2006). Furthermore, CD138 is

    expressed at higher levels in myeloma than in normal plasma cells. However,

    optimization of CD138 assessment may hampered by technical issues, including

    clone choice, lyse reagent, and refrigeration (Lin, 2004). Notably, in one recent

    study, CD138 was actually less sensitive as a single gating antigen than CD38 (76.6%

    versus 84.1%)(Gupta, 2009). Adding CD45 to the gating strategy enhances the

    sensitivity of either CD138 or CD38 (79.4% and 90.7%, respectively, in the Gupta

    study). However, the use of CD45 (typically gating on high CD38 and low/negative

    CD45 events) risks missing CD45(+) myeloma populations. Of the two antibody

    strategies, CD38 and CD138 in tandem appears to be superior, capturing the vast

    majority of cases (Gupta, 2009; Rawstron, 2008). Finally, if feasible, a three-

    parameter gate using CD38, CD138, and CD45 appears to be maximally sensitive

    (Gupta, 2009; Rawstron, 2008). An alternative approach to rigid two or three

    antigen gating strategies (requiring those two or three antibodies in every tube) is

    to combine CD38 and CD138 individually in separate tubes with commonly aberrant

    antigens (e.g., CD45, CD56, CD200, CD117), and use flexible, iterative approaches to

    analysis. The synergy obtained across multiple tubes allows enhancement of both

    sensitivity and specificity, while allowing flexibility and economy in antibody choice.

    However, this approach, while powerful, is difficult to standardize.

    Choice of antibodies

    The detection of MRD in myeloma does not generally depend on demonstration of

    light chain restriction. In fact, cytoplasmic light chain analysis is insensitive because

    of the frequent co-existence of normal plasma cells in follow-up samples. Instead,

    the identification of immunophenotypic aberrancy is the mainstay of MRD

    detection. Simply incorporating CD19 and CD56 will allow detection of MRD in over

    90% of cases. CD19 is the most frequently aberrant antigen in myeloma, as it is

    negative in roughly 90% of cases. However, it is somewhat limited as a single

    marker of aberrancy, because a minority sub-population of normal plasma cells may

    be negative (Bataille, 2006). CD56 is aberrantly expressed in about 75% of cases,

    most often brightly, making it a good target for MRD analysis. The addition of one or

    two more aberrantly expressed antigens advances the capture rate to virtually

    100%. Various antigens have been proposed for this purpose, including CD117

    (aberrantly positive in one third of cases), CD27 (weak or negative in 40-50%),

    CD28 (strongly positive in 15-45%), and CD52 (positive in 15-45%). CD200 holds

    particular promise, as it appears to be strongly positive in roughly 80% of myelomas

    (Moreaux, 2006), but this bears further investigation.

    How many events to acquire?

    The European Myeloma Network Report (Rawstron, 2008) recommends a minimum

    of 100 aberrant plasma cell events to make a diagnosis of MRD. Thus, to achieve a

    sensitivity of 10-4, a total of one million events need to be acquired. This is a

    conservative recommendation, given that in other MRD settings a cluster of 20

    events is usually considered sufficient. The rationale given in the report for this

  • 5

    number is that 100 events will produce an acceptably low coefficient of variation for

    quantification of the number of myeloma cells present. Given that at the present

    time most myeloma MRD studies are reported as essentially positive or negative

    based on the sensitivity of the assay, a high CV for very low levels of MRD is

    probably not a critical consideration. Consequently, a less conservative approach is

    probably acceptable. One other interesting feature of the European Myeloma

    Network recommendation is also worth highlighting. This group does not require

    all 100 events to be present in the same tube, just that the aberrant plasma cells

    events across tubes totals at least one hundred. This feature formally codifies the

    fact that reproducibility across multiple tubes strongly increases the specificity of a

    rare event analysis. Thus, if one is using a multi-tube analysis, fewer events need to

    be acquired per tube to satisfy the European Myeloma Network recommendation.

    How many colors?

    It is an article of faith among flow cytometrists that increasing the number of

    antibodies assessed in a single tube enhances the sensitivity of MRD analysis.

    Notably, however, Rawstron et al (2002) were able to achieve a level of sensitivity of

    10-4 with a 3-color, 4-tube approach, and thus 3 colors can be considered a

    minimum technical requirement (Rawstron, 2008). Notably, this group was unable

    to demonstrate an increase in sensitivity or specificity over their 3-color assay using

    a 6-color, single tube approach (Rawstron, 2007), although this may have been

    influenced by the study cohort (immediately post-therapy, with an absence of

    normal plasma cells). A theoretical advantage of using larger numbers of colors is

    the ability to combine aberrantly expressed surface markers with cytoplasmic light,

    thereby enabling the demonstration of light chain restriction in populations of

    interest. Clearly, the availability of additional colors can also decrease the time,

    expense, and effort required for MRD analysis, if not the sensitivity.

    Immunophenotypic stability

    A very real concern in any MRD analysis is the possibility of immunophenotypic

    changes over time in the neoplastic cells, compromising detection. We have

    recently studied this phenomenon in 48 myeloma patients (abstract at this

    meeting), and have found that immunophenotypic alterations in commonly assessed

    antigens (CD19, CD20, CD45, CD56) occur in about 1/3 of patients over time. By far

    the most common alterations were in CD45 expression [12 cases (25%) including 4

    gains, 1 loss, 2 gains followed by loss, and 5 changes in intensity). Interestingly, it

    has been demonstrated that myelomas contain CD45 positive and negative subsets,

    and that the CD45(+) subset is the proliferative compartment, while the CD45 (-)

    compartment may be more resistant to apoptosis (Bataille, 2006; Morice, 2007).

    Thus, it is perhaps not surprising to see modulation of expression of CD45 over time

    in treated myelomas. Significant changes (likely to compromise MRD analysis) in

    CD19, CD20, and CD56 were very uncommon in our study [although these results

    conflict with earlier data (Cao, 2008)]. Consequently, if one uses a reasonably

    flexible MRD approach, it appears that at least the vast majority of myelomas should

    remain amenable to MRD analysis over time.

  • 6


    The rationale for the performance of flow cytometry can be divided broadly into

    applications to diagnostic, prognostic, and therapeutic issues.

    Diagnostic issues

    The diagnosis of plasma cell myeloma is generally straightforward, and

    consequently flow cytometry generally contributes little to the initial evaluation.

    Occasionally, however, immunophenotyping does serve a decisive role in the

    differential diagnosis of plasma cell myeloma, as discussed below.

    Unusual Morphologic Variants of Myeloma

    Occasionally one encounters myelomas that are difficult to recognize as such by

    morphologic evaluation, such as particularly anaplastic examples or those with

    strikingly lymphoid or lymphoplasmacytoid cytologic features. Detection of a

    characteristic immunophenotype by flow cytometry will help to discriminate these

    from possible differential diagnoses.

    Florid Reactive Plasmacytosis

    While uncommon, reactive bone marrow plasmacytoses can reach proportions at

    which there is a real possibility for confusion with plasma cell myeloma.

    Associations with florid reactive bone marrow plasmacytosis include autoimmune

    disorders (Tanvetyanon, 2002), carcinomas (Tatsuno, 1994), Hodgkin lymphoma

    (Kass, 1975), drug-induced agranulocytosis (Jamshidi, 1972), HHV-8-associated

    mutlicentric Castlemans disease (Bacon, 2004), and HIV (Turbat-Herrera, 1993).

    Demonstration of a normal plasma cell immunophenotype and polytypic

    cytoplasmic light chain expression will serve to discriminate florid reactive

    plasmacytosis from plasma cell myeloma. Obviously, however, correlation with

    other clinical and laboratory features and the application of immunohistochemistry

    or in situ hybridization for light chain will also serve to make this distinction.

    Non-Hodgkin Lymphomas With Prominent Plasmacytic Differentiation

    Various non-Hodgkin lymphomas may show plasmacytic differentiation of the

    neoplastic cells, most commonly marginal zone lymphomas and lymphoplasmacytic

    lymphoma. Occasionally, the plasmacytic differentiation may be so prominent as to

    be confused for plasmacytoma or myeloma. The differential diagnosis depends on

    the detection of an abnormal, clonal B-cell population associated with the clonal

    plasma cells. When this population is very small, its recognition may be difficult or

    impossible with light microscopy and immunohistochemistry. Flow cytometry, with

    its enhanced sensitivity for detecting minor abnormal B cell populations, is well

    suited to make this distinction. Additionally, immunophenotypic differences have

    been described between the clonal plasma cells in non-Hodgkin lymphoma and

    those of myeloma. Seegmiller et al (2007) found that the best discriminator was

    CD19, which is expressed in the plasma cells of 95% of NHL with plasmacytic

    differentiation, but only 5% of myelomas. Other differences included CD45 (91% vs.

  • 7

    41%), CD56 (33% vs. 71%), and surface light chain (76% vs. 44%). It is worth

    noting that the clonal plasma cell populations in NHLs are almost always

    immunophenotypically distinct from the clonal B-cell populations, rather than

    showing an immunophenotypic spectrum.

    Myeloma versus MGUS

    The plasma cells of both MGUS and myeloma are immunophenotypically abnormal

    compared to normal plasma cells. Consequently, when both normal and abnormal

    plasma cells are present, it is possible to distinguish and quantify their proportions

    immunophenotypically. Ocqueteau et al (1998) have reported that normal plasma

    cells constitute >3% of total bone marrow plasma cells in 98% of MGUS cases but

    only 1.5% of myelomas, making it the single most powerful discriminator of MGUS

    and myeloma in multivariate analysis. However, other authors have found a greater

    proportion of symptomatic myelomas to contain significant normal plasma cell

    populations [14% with >5% normal PCs/total PCs in the series of Paiva et al (Blood

    2009)], limiting its discriminatory power. It would also seem that there are few

    clinical scenarios where flow cytometry is likely to contribute significantly to the

    generally straightforward distinction of MGUS and myeloma. Notably, the presence

    of fewer than 5% normal plasma cells of total marrow plasma cells has been found

    to be a strong predictor of progression in MGUS and smoldering myeloma (Perez-

    Persona, 2007).

    Prediction of Genetic Abnormalities

    Various immunophenotypic features have been associated with genetic subgroups

    of myelomas, including CD19, CD20, and CD23 with the t(11;14), CD28 with

    del(17p) and t(4;16), lack of CD117 with nonhyperdiploidy, IgH translocations, ad

    del(13q), (Bataille, 2006; Mateo, 2008; Robillard, 2003; Walters, in press).

    However, these associations lack sufficient sensitivity and/or specificity to be

    clinically useful (Rawstron, 2008).

    Prognostic Issues

    Qualitative immunophenotypic features

    By far the largest study of the impact of myeloma immunophenotype on outcome

    was that of Mateo et al (2008). These authors studied 685 newly diagnosed

    myeloma patients and found that expression of CD19, lack of CD117, and expression

    of CD28 are all associated with worse progression-free and overall survival in

    univariate analysis. Furthermore, by combining CD28 and CD117, they identified

    three distinct risk groups: good [CD28(-)/CD117(+)], intermediate

    [CD28(+)/CD117(+)or CD28(-)/CD117(-)], and poor [CD28(+)/CD117(-)]. The

    CD28/CD117 status remained significant for overall survival, but not progression

    free survival, in multivariate analysis without cytogenetics. It lost significance when

    cytogenetic information was entered into the analysis in the subset of 231 cases in

    which it was available. Notably, the CD28(+)/CD117(-) profile had no impact on

    patients with high risk cytogenetics. The authors suggested that the

  • 8

    CD28(+)/CD117(-) subgroup does not benefit from autologous stem cell transplant,

    and that novel therapeutic strategies should be explored in these patients.

    CD20, CD56, and CD45 expression carried no prognostic significance in the Mateo

    (2008) study. However, this conflicted with earlier data for CD45 and CD56. Sahara

    et al (2202) demonstrated a worse outcome for CD56(-) myeloma in a series of 70

    patients; the cause of this discrepancy is unclear. Regardless of its impact on

    prognosis, CD56(-) myeloma appears to have distinct features, including peripheral

    blood involvement, high bone marrow tumor burden, tendency toward

    extramedullary tumors, and less osteolytic potential (Pellat-Deceunynck, 1998;

    Rawstron, 1999). Moreau et al (2004), in a retrospective series of 95 patients, found

    that lack of CD45 was associated with a worse outcome. However, interpretation of

    data regarding CD45 is complicated by widely varying reports of the frequency of

    CD45 expression in myeloma, ranging from 18 to 75% of cases (Moreau, 2004;

    Mateo, 2008; Morice, 2007; Lin, 2004; Walters, in press). These differences may be

    due to differences in gating approach, definitions of positivity, and interpretation of

    positivity and negativity.

    A single study examined the prognostic impact of CD200 expression. Although the

    outcome data was based on expression array data, not flow cytometry, lack of

    CD200 was associated with a more favorable outcome (Moreaux, 2006). Further

    study is required on this antigen.

    Quantitative issues at diagnosis

    Two quantitative flow cytometric parameters have been found to be of prognostic

    significance in myeloma: the number of myeloma cells as a percentage of total

    marrow cells, and the number of myeloma cells as a percentage of total plasma cells.

    The percentage of myeloma cells in bone marrow aspirates has long been

    recognized as a prognostic factor in myeloma, although it usually does not maintain

    its significance in multivariate analysis. Paiva et al (2009) have recently

    demonstrated that the number of plasma cells enumerated by both morphology and

    by flow cytometry are significant for both progression-free and overall survival in

    univariate analysis, although the cut-off was lower for flow cytometry than

    morphology (15% versus 30% plasma cells). Remarkably, while morphologic

    enumeration was no longer significant in multivariate analysis, flow cytometric

    enumeration maintained significance for overall survival, along with patient age and

    high-risk cytogenetics. This is a surprising finding. While the percentages obtained

    by the two methods were significantly correlated, the R2 was only 0.46. One

    possible implication of these results is that other biologic characteristics of

    myelomas cells that are related to prognosis affect the recovery by flow cytometry,

    perhaps by altering the distribution of plasma cells amongst the marrow

    compartments (liquid versus particle-associated), or the susceptibility to cell

    damage in processing.

  • 9

    As mentioned earlier, the marrows from myeloma patients at diagnosis typically

    contain few or no normal plasma cells. However, a minority of myeloma marrows

    do contain greater >3% or >5% normal plasma cells, as a percentage of total plasma

    cells (different cut-offs have been employed in different studies). Paiva et al (2009)

    recently demonstrated that >5% normal plasma cells as a percentage of total plasma

    cells in diagnostic myeloma marrows (14% in their series) was associated with

    significantly better progression-free and overall survival, although this was not

    significant in multivariate analysis that incorporated cytogenetics. Greater than 5%

    normal plasma cells was associated with other favorable prognostic factors, such as

    fewer high-risk cytogenetic changes and higher rate of CD117 expression.

    Obtaining an immunophenotypic fingerprint for future MRD studies

    One potential reason to do flow cytometry at diagnosis is to obtain an

    immunophenotypic fingerprint for future MRD studies, although robust MRD

    approaches should not strictly require knowledge of a prior immunophenotype.

    Various studies using ASO-PCR or flow, mainly small and/or retrospective, have

    previously established the relevance of MRD assessment in myeloma (reviewed by

    Paiva, 2008). Recently, Paiva et al (2008) reported the results of a large prospective

    study assessing the prognostic impact of MRD in myeloma. In this study, flow MRD

    was present at day 100 following autologous stem cell transplantation in 58% of

    patients. The median level of MRD in positive studies at this time point was 0.14%

    (range 0.01-4%). The presence or absence of MRD was strongly predictive of

    poorer progression free and overall survival both in the entire cohort (N=295) and

    those achieving complete remission (147) by 1998 EMBT criteria (immunofixation

    negative and

  • 10

    Theoretically, flow cytometry could be used to identify therapeutic targets;

    however, this area of clinical investigation is in its infancy. Treon et al (2002) in a

    phase II trial, treated 19 previous treated myeloma patients with single agent

    rituximab. One patient achieved a partial response and 5 had stable disease, all of

    whom had CD20(+) plasma cells. Moreau et al (2007) treated 14 previously treated

    patients with CD20(+) myeloma with single agent rituximab, achieving a minor

    response in one, stabilization of disease for varying intervals in 8, and no response

    in 5. Zojer concluded from a phase II trial of ten patients [only two of whom had

    CD20(+) plasma cells] that rituximab produced no clinical benefit in patients with

    pre-treated, advanced myeloma.

    Another potential therapeutic target in myeloma is CD52, which has been reported

    to be expressed in as many as 45% of cases. However, Rawstron et al (2006) found

    that the level of CD52 expression in myeloma was much lower than other types of

    cells that are known to be resistant to alemtuzumab (anti-CD52), and concluded that

    this agent is unlikely to have clinical efficacy.


    Bacon CM, Miller RF, Noursadeghi M, McNamara C, Du MQ, Dogan A. Pathology of bone

    marrow in human herpes virus-8 (HHV8)-associated multicentric Castleman disease. Br J

    Haematol. 2004;127:585-591.

    Bakkus MH, Bouko Y, Samson D, et al. Post-transplantation tumour load in bone marrow, as

    assessed by quantitative ASO-PCR, is a prognostic parameter in multiple myeloma. Br J

    Haematol. 2004;126:665-674.

    Bataille R, Jego G, Robillard N, et al. The phenotype of normal, reactive and malignant

    plasma cells. Identification of "many and multiple myelomas" and of new targets for

    myeloma therapy. Haematologica. 2006;91:1234-1240.

    Cao W, Goolsby CL, Nelson BP, Singhal S, Mehta J, Peterson LC. Instability of

    immunophenotype in plasma cell myeloma. Am J Clin Pathol. 2008;129:926-933.

    de Tute RM, Jack AS, Child JA, Morgan GJ, Owen RG, Rawstron AC. A single-tube six-colour

    flow cytometry screening assay for the detection of minimal residual disease in myeloma.

    Leukemia. 2007;21:2046-2049.

    Descamps G, Gomez-Bougie P, Venot C, Moreau P, Bataille R, Amiot M. A humanised anti-

    IGF-1R monoclonal antibody (AVE1642) enhances Bortezomib-induced apoptosis in

    myeloma cells lacking CD45. Br J Cancer. 2009;100:366-369.

    Durie BG, Harousseau JL, Miguel JS, et al. International uniform response criteria for

    multiple myeloma. Leukemia. 2006;20:1467-1473.

  • 11

    Fenk R, Ak M, Kobbe G, et al. Levels of minimal residual disease detected by quantitative

    molecular monitoring herald relapse in patients with multiple myeloma. Haematologica.


    Gupta R, Bhaskar A, Kumar L, Sharma A, Jain P. Flow cytometric immunophenotyping and

    minimal residual disease analysis in multiple myeloma. Am J Clin Pathol. 2009;132:728-


    Jamshidi K, Arlander T, Garcia MC, Windschitl HW, Swaim WR. Azulfidine agranulocytosis

    with bone marrow, megakaryocytosis, histiocytosis and plasmacytosis. Minn Med.


    Kass L, Votaw ML. Eosinophilia and plasmacytosis of the bone marrow in Hodgkin's

    disease. Am J Clin Pathol. 1975;64:248-250.

    Kobayashi S, Hyo R, Amitani Y, et al. Four-color flow cytometric analysis of myeloma

    plasma cells. Am J Clin Pathol. 2006;126:908-915.

    Kumar S, Rajkumar SV, Kimlinger T, Greipp PR, Witzig TE. CD45 expression by bone

    marrow plasma cells in multiple myeloma: clinical and biological correlations. Leukemia.


    Lin P, Owens R, Tricot G, Wilson CS. Flow cytometric immunophenotypic analysis of 306

    cases of multiple myeloma. Am J Clin Pathol. 2004;121:482-488.

    Mateo G, Montalban MA, Vidriales MB, et al. Prognostic value of immunophenotyping in

    multiple myeloma: a study by the PETHEMA/GEM cooperative study groups on patients

    uniformly treated with high-dose therapy. J Clin Oncol. 2008;26:2737-2744.

    Moreaux J, Hose D, Reme T, et al. CD200 is a new prognostic factor in multiple myeloma.

    Blood. 2006;108:4194-4197.

    Moreau P, Robillard N, Avet-Loiseau H, et al. Patients with CD45 negative multiple myeloma

    receiving high-dose therapy have a shorter survival than those with CD45 positive multiple

    myeloma. Haematologica. 2004;89:547-551.

    Moreau P, Voillat L, Benboukher L, et al. Rituximab in CD20 positive multiple myeloma.

    Leukemia. 2007;21:835-836.

    Morice WG, Hanson CA, Kumar S, Frederick LA, Lesnick CE, Greipp PR. Novel multi-

    parameter flow cytometry sensitively detects phenotypically distinct plasma cell subsets in

    plasma cell proliferative disorders. Leukemia. 2007;21:2043-2046.

    Nadav L, Katz BZ, Baron S, et al. Diverse niches within multiple myeloma bone marrow

    aspirates affect plasma cell enumeration. Br J Haematol. 2006;133:530-532.

  • 12

    Ocqueteau M, Orfao A, Almeida J, et al. Immunophenotypic characterization of plasma cells

    from monoclonal gammopathy of undetermined significance patients. Implications for the

    differential diagnosis between MGUS and multiple myeloma. Am J Pathol. 1998;152:1655-


    Paiva B, Vidriales MB, Cervero J, et al. Multiparameter flow cytometric remission is the

    most relevant prognostic factor for multiple myeloma patients who undergo autologous

    stem cell transplantation. Blood. 2008;112:4017-4023.

    Paiva B, Vidriales MB, Mateo G, et al. The persistence of immunophenotypically normal

    residual bone marrow plasma cells at diagnosis identifies a good prognostic subgroup of

    symptomatic multiple myeloma patients. Blood. 2009.

    Paiva B, Vidriales MB, Perez JJ, et al. Multiparameter flow cytometry quantification of bone

    marrow plasma cells at diagnosis provides more prognostic information than

    morphological assessment in myeloma patients. Haematologica. 2009;94:1599-1602.

    Pellat-Deceunynck C, Barille S, Jego G, et al. The absence of CD56 (NCAM) on malignant

    plasma cells is a hallmark of plasma cell leukemia and of a special subset of multiple

    myeloma. Leukemia. 1998;12:1977-1982.

    Perez-Persona E, Vidriales MB, Mateo G, et al. New criteria to identify risk of progression in

    monoclonal gammopathy of uncertain significance and smoldering multiple myeloma

    based on multiparameter flow cytometry analysis of bone marrow plasma cells. Blood.


    Rawstron A, Barrans S, Blythe D, et al. Distribution of myeloma plasma cells in peripheral

    blood and bone marrow correlates with CD56 expression. Br J Haematol. 1999;104:138-


    Rawstron AC, Davies FE, DasGupta R, et al. Flow cytometric disease monitoring in multiple

    myeloma: the relationship between normal and neoplastic plasma cells predicts outcome

    after transplantation. Blood. 2002;100:3095-3100.

    Rawstron AC, Laycock-Brown G, Hale G, et al. CD52 expression patterns in myeloma and

    the applicability of alemtuzumab therapy. Haematologica. 2006;91:1577-1578.

    Rawstron AC, Orfao A, Beksac M, et al. Report of the European Myeloma Network on

    multiparametric flow cytometry in multiple myeloma and related disorders.

    Haematologica. 2008;93:431-438.

    Robillard N, Avet-Loiseau H, Garand R, et al. CD20 is associated with a small mature plasma

    cell morphology and t(11;14) in multiple myeloma. Blood. 2003;102:1070-1071.

    Sahara N, Takeshita A, Shigeno K, et al. Clinicopathological and prognostic characteristics of

  • 13

    CD56-negative multiple myeloma. Br J Haematol. 2002;117:882-885.

    San Miguel JF, Almeida J, Mateo G, et al. Immunophenotypic evaluation of the plasma cell

    compartment in multiple myeloma: a tool for comparing the efficacy of different treatment

    strategies and predicting outcome. Blood. 2002;99:1853-1856.

    Sarasquete ME, Garcia-Sanz R, Gonzalez D, et al. Minimal residual disease monitoring in

    multiple myeloma: a comparison between allelic-specific oligonucleotide real-time

    quantitative polymerase chain reaction and flow cytometry. Haematologica. 2005;90:1365-


    Seegmiller AC, Xu Y, McKenna RW, Karandikar NJ. Immunophenotypic differentiation

    between neoplastic plasma cells in mature B-cell lymphoma vs plasma cell myeloma. Am J

    Clin Pathol. 2007;127:176-181.

    Smock KJ, Perkins SL, Bahler DW. Quantitation of plasma cells in bone marrow aspirates by

    flow cytometric analysis compared with morphologic assessment. Arch Pathol Lab Med.


    Tanvetyanon T, Leighton JC. Severe anemia and marrow plasmacytosis as presentation of

    Sjogren's syndrome. Am J Hematol. 2002;69:233.

    Tatsuno I, Nishikawa T, Sasano H, Shizawa S, Iwase H, Satoh S. Interleukin 6-producing

    gastric carcinoma with fever, hypergammaglobulinemia, and plasmacytosis in bone

    marrow. Gastroenterology. 1994;107:543-547.

    Treon SP, Pilarski LM, Belch AR, et al. CD20-directed serotherapy in patients with multiple

    myeloma: biologic considerations and therapeutic applications. J Immunother. 2002;25:72-


    Turbat-Herrera EA, Hancock C, Cabello-Inchausti B, Herrera GA. Plasma cell hyperplasia

    and monoclonal paraproteinemia in human immunodeficiency virus-infected patients. Arch

    Pathol Lab Med. 1993;117:497-501.

    Walters MP, Olteanu H, Van Tuinen P, Kroft SH. CD23 expression in plasma cell myeloma is

    specific for abnormalities of chromosome 11, and is associated with primary plasma cell

    leukemia in this cytogenetic sub-group. Br J Haematol, in press.

    Wood BL, Arroz M, Barnett D, et al. 2006 Bethesda International Consensus

    recommendations on the immunophenotypic analysis of hematolymphoid neoplasia by

    flow cytometry: optimal reagents and reporting for the flow cytometric diagnosis of

    hematopoietic neoplasia. Cytometry B Clin Cytom. 2007;72 Suppl 1:S14-22.

    Zojer N, Kirchbacher K, Vesely M, Hubl W, Ludwig H. Rituximab treatment provides no

    clinical benefit in patients with pretreated advanced multiple myeloma. Leuk Lymphoma.


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