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

Rationale

Outline

How

Why

The Immunophenotype of Normal

Plasma CellsCD38 bright

CD19(+) CD20(-)

Normal Plasma Cells Normal B cells Granulocytes Monocytes

Polytypic Light

ChainsCD45(+)

CD56(-)

CD38 on Normal Marrow Populations

Plasma Cells

HematogonesT Cells

Monocytes

Mature B cellsGranulocytes

T Cells

Other Features of Normal Plasma Cells

CD117(-)

CD27(bright+)

CD28(dim+/-)

CD52(-) CD52(-)

CD200(dim+)

Typical MyelomaCD19(-)

Myeloma Cells Normal B cells

CD56(+)Monotypic cytoplasmic Ig

Technical Issues

General

MRD

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

Comparable

results

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

aberrancy

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

(additive)

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

N=48

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%)

N=48

WHY

Diagnostic Prognostic Therapeutic Diagnostic

Issues

Prognostic

Issues

Therapeutic

Issues

MYELOMA

ISNT DIFFICULT

TO DIAGNOSETO DIAGNOSE

usually

Unusual morphologic variants of myeloma

Florid reactive plasmacytosis

Non-Hodgkin lymphomas with prominent plasmacytic differentiationplasmacytic differentiation

Myeloma

Myeloma

Lymphoplasmacytic Lymphoma

Reactive Plasmacytosis (HIV)

Lymphoplasmacytic Lymphoma

CD19(+) PCs:

NHL--95%

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

NHL76%

MM44%

NHL with plasmacytic

differentiation

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

CD45: 91% v. 41%

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

population

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

Issues

Prognostic

Issues

Therapeutic

Issues

Prognostic Issues

Qualitative immunophenotypic features

Quantitative features (at diagnosis)

Minimal residual disease

5% of myelomas are CD19(+)

Unfavorable

Not significant in

multivariate analysis

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

One third of myelomas are CD117(+)

Favorable

Not significant in

multivariate analysis

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

36% of myelomas are CD28(+)

Unfavorable

Not significant in

multivariate analysis

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

but not when

cytogenetics are included

Significant in multivariate

analysis

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

analysis

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

P=0.0002

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

multivariate

analysis

Flow

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

Significant in

multivariate

analysis

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

analysis

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

N=141

Paiva et al, Blood 2008:4017-4023

WHY

Diagnostic Prognostic Therapeutic Diagnostic

Issues

Prognostic

Issues

Therapeutic

Issues

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

Introduction

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)

analysis.

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

below.

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

Rationale

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.

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