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Molecular diagnostics in lymphoma: why, when and how to apply

Diagnostic Histopathology, 2, 18, pages 53 - 63

Abstract

Current strategies for diagnosing lymphomas include molecular methodologies next to histomorphological assessment supplemented by immunohistochemistry. Especially PCR-based clonality analysis and detection of chromosome aberrations by FISH can support the diagnosis and classification in difficult cases. We have to ensure that these existing molecular methodologies are used to their full potential. Yet, such analyses are not required in every situation. Ongoing optimization, dissemination of (new) protocols, standardized interpretation, and education are essential elements to ensure best practice for patient care. Here we discuss why, when, and how to apply these molecular diagnostic methods in the field of lymphoma.

Keywords: clonality, FISH, Ig/TCR, leukemia, lymphoma, PCR, translocation.

Introduction

Lymphomas are diagnosed and classified according to the most recent (2008) WHO Classification. 1 This classification is a collaborative project of the European Association for Haematopathology and the Society for Hematopathology (American). This classification also benefits from a clinical advisory board comprising clinical hematologists and oncologists. Lymphomas are malignant proliferations of B or T/NK lymphoid cells and we exclude in this review myelomas and plasmacytomas. Lymphomas are mainly divided into B-cell Non-Hodgkin lymphomas (NHL), T and NK cell NHL and Hodgkin lymphomas. This 2008 classification defines more than 70 types or subtypes of lymphoma and this distinction is important as prognosis and therapy protocols are different between most entities. This classification includes mainly clinical, morphological, immunophenotypical and molecular criteria underlining the importance of molecular tools for an optimal classification. However, with good clinical data, histology (architecture and cellular patterns) and immunohistochemistry are sufficient to diagnose more than 75% of lymphomas according to the WHO classification. However, this depends largely on the experience of the pathologist in lymphoma diagnosis. 2 Two ancillary techniques are being increasingly used in the clinical practice of lymphoma diagnosis: flow cytometry which provides quantitative data and precise phenotypical characterization of multiple membranous antigens, 3 and molecular genetics. Flow cytometry for example is an important tool for assessing the diagnosis of lymphocytic lymphoma using the Matutes score. 4 Flow cytometry however is difficult to manage as it has to be performed on fresh cells, often without knowledge of the probable diagnosis, with an algorithm of phenotypical markers not yet standardized.

Detection of karyotypic abnormalities is less frequently used due to the need of viable cells and high workload and has been replaced by techniques performed on frozen tissue, fixed cells (imprints) or paraffin-embedded tissue. Indeed, many countries recommend freezing a part of the diagnostic tissue when there is clinical suspicion of lymphoma. Although this might be performed on lymph nodes, it is more complicate on extranodal samples because diagnostic suspicion is not often firmly established. The two main techniques being used are immunoglobulin (Ig)/T-cell receptor (TCR) clonality testing 5 and FISH. 6 Ig/TCR clonality testing is crucial as most NHL are derived from a clonal proliferation of a B, T or NK cell. Therefore testing the presence of a clonal B or T-cell population in a tissue will be of great help in difficult cases. FISH is performed mainly to look for translocations, but amplification or deletion detection are being incorporated into clinical practice. Indeed translocations involving MYC or BCL2 are crucial to support, respectively, a diagnosis of Burkitt or follicular lymphoma in difficult cases. High throughput techniques such as deep sequencing, CGH arrays and gene expression profiling are important discovery tools but have not yet entered translational medicine. Signatures by quantitative multiplex polymerase chain reaction (PCR) of short fluorescent fragments (QMPSF) or reverse transcription (RT)-PCR of a few genes are promising as prognostic tools for example in diffuse large B-cell lymphoma7 and 8 and might soon be incorporated into clinical practice. Standardization of such techniques on frozen and paraffin-embedded tissue has nevertheless to be addressed.

As molecular genetic features are characteristic of a given entity of the classification, FISH and/or Ig/TCR clonality are needed in all discordant cases between histopathological and clinical data, and whenever the pathologist is unsure of the diagnosis. These tools might represent a valuable input in early phase B- or T-cell lymphoma. Nevertheless, some of these tools are already needed within the pathology report such as MYC translocation in Burkitt lymphoma. It is probable that molecular tools will become more frequent in the report as targeted therapies of oncogene pathways are developed. 9

In this review we address PCR and FISH strategies in lymphoma diagnostics, including implications (“why”), indications (“when”), and technical standardization and interpretation (“how”).

Ig/TCR clonality testing

PCR-based clonality analyses 10 were developed in the early 1990s from previous DNA targeting techniques, such as Southern blotting that were applied in the mid to late 1980s. 11 The latter were developed to complement immunohistochemical determination of light chain restriction – a useful means of recognizing monoclonal expansion, but with limited sensitivity. 12 The PCR-based approach solved several of the technical drawbacks of Southern blotting such as the need for large amounts of high molecular weight DNA (formalin fixed paraffin embedded – FFPE – material could not be used), and that it was slow and labour intensive. PCR was fast and could be applied to FFPE material, but was problematic due to the complexity of the targeted genomic regions (antigen receptor genes) which led to high false negative rates and to difficulties in interpretation. 13 The methodology required considerable improvements before its widespread use was appropriate. As a result, a huge effort has been undertaken by a European consortium (originally BIOMED-2 now the EuroClonality group) to optimize all stages of the process, work that is still underway.

Principle

The most common aim of clonality analysis is to determine if there is significant monoclonal expansion of B-cells or T-cells and to correlate this information with clinical, histological and immunohistochemical data to help distinguish between reactive and malignant lymphoproliferation. The general rule is that reactive proliferations are polyclonal and malignant proliferations are monoclonal. 12 Clonality analysis of lymphocyte populations relies on size analysis of PCR amplified rearranged antigen receptor genes. B-cell clonality analysis targets immunoglobulin (Ig) genes (Ig heavy chain, IGH; Ig kappa light chain, IGK; or Ig lambda light chain, IGL). T-cell clonality analysis targets T-cell receptor (TCR) genes (TCR beta, TCRB; TCR gamma, TCRG; or TCR delta, TCRD). Variable (V), diversity (D), and joining (J) genes of antigen receptor gene complexes rearrange during lymphocyte development to yield highly diverse, functional coding sequences. 5 The process is also referred to as V(D)J recombination and is specific to a particular clone, thus yielding V(D)J exons of different size in different clones ( Figure 1 ). The resulting rearranged V(D)J exons can be amplified using PCR and a size analysis performed using polyacrylamide gel electrophoresis 5 ( Figure 2 ) or capillary analysis of fluorescently labelled products (“GeneScan” 5 ) ( Figure 3 ). Significant monoclonal expansion can be recognized by the preponderance of one or two fragment sizes rather than a wide spread of product sizes. On a gel the expanded clones are represented by dominant bands in the presence or absence of a background smear or ladder representing the polyclonal non-neoplastic cells that may be present in the sample ( Figure 2 ). Exclusively polyclonal samples appear as smears. On a GeneScan expanded clones appear as dominant peaks with or without a background; polyclonal samples appear as normal distributions of peaks without dominant peaks ( Figure 3 ).

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Figure 1 (a) Immunoglobulin heavy chain (IGH) gene rearrangement. The germline IGH gene complex (top) contains clusters of V, D and J genes which rearrange to form functional V(D)J exons in individual B-cells. Additional “N” regions are inserted at the junctions (bottom) thus creating a B-cell (or B-cell clone) specific signature. (b) PCR primers for IGH clonality analysis. Different rearrangements create different sized coding regions which can be targeted using PCR. PCR primers are shown in red- these span the highly variable V(D)J exons. PCR product sizes vary, mainly as a result of different sized inserted N regions. Monoclonal B-cell populations yield a preponderance of PCR products of a single size, whereas polyclonal populations yield a wide range of product sizes. (The antigen receptor gene rearrangement process and primer target regions are fully explained in Van Dongen, 2003). The genes are coded as follows: V = variable, D = diversity, J = joining, C = constant.

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Figure 2 Polyacrylamide gel (8%) of IGH FR3-JH PCR products. Lane 1, no template control; 2, positive control B-cell lymphoma showing a dominant band; 3 and 4, test case 1 in duplicate showing evidence of minor monoclonal B-cell expansion with bi-allelic rearrangement (reproducible dominant band); 5 and 6, test case 2 in duplicate showing no evidence of B-cell expansion (smear of products with no dominant bands); 7 and 8, test case 3 in duplicate showing evidence of monoclonal B-cell expansion (reproducible dominant band); 9 and 10, test case 4 in duplicate showing evidence of monoclonal B-cell expansion (reproducible dominant band); 11 and 12, test case 5 in duplicate showing evidence of monoclonal B-cell expansion with bi-allelic rearrangement (reproducible dominant bands). Additional bands migrating a shorter distance in the gels represent heteroduplexes.

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Figure 3 GeneScan analysis of Ig/TCR products. (a) In GeneScan analysis one of the primers is fluorescently labeled. Resulting fluorescently-labeled products are denatured and the single-strandeds molecules are electrically separated in a high resolution polymer matrix and detected by a laser. In the electropherogram fluorescence intensity (Y-axis) is shown as a function of PCR product size (X-axis). (b) In a polyclonal sample with reactive lymphocytes many different PCR products are found, giving rise to a Gaussian shaped distribution. In a monoclonal sample one clear peak is seen, derived from PCR products of identical size. The most common result in a lymphoma is a mixture of a monoclonal and polyclonal pattern. This is seen as a dominant peak on top of a Gaussian curve.

In B-cell clonality analysis IGH is the most popular target, by amplification of V framework to joining regions (FR1-JH, FR2-JH or FR3-JH; Figure 1 ). However, as some expanded clones are missed due to somatic mutations or gene deletion events, 13 IGK and IGL genes may also be analyzed. This especially holds for post germinal center derived lymphomas. In T-cell clonality analysis TCRB and TCRG are most popular as these give the highest success rate in both αβ- and γδ-expressing T-cells. TCRA is not targeted as the gene is too complex and TCRD is less informative as the gene is deleted during TCRA rearrangement, and thus only applicable to immature or γδ-expressing T-cells. Gene targets for clonality analysis and their relative values are shown in Table 1 .

Table 1 Gene targets for clonality analysis

Gene Value
IGH +++
IGK +++
IGL +
TCRB ++
TCRG +++
TCRD +

Gel analysis of PCR products has been improved by use of polyacrylamide gels and heteroduplex analysis (heating and rapid cooling of PCR products; HAD) 5 to improve distinction of monoclonal products from polyclonal fragments of similar size. Many laboratories prefer to use capillary fragment analysis as this is less labour intensive, easier to standardize and provides accurate sizing of PCR products. However problems of interpretation exist with both technologies and the optimal approach depends on laboratory expertise and personal preference. Some genes with less diverse rearrangements such as IGK and IGL are better analyzed with gel electrophoresis with HDA rather than with capillary fragment analysis.

Clonality analysis using PCR amplification of antigen receptor genes is complex and relies on considerable expertise. The existence of many different approaches of variable effectiveness demanded the standardization and optimization of techniques by inter-laboratory co-operation.

Technical standardization in the BIOMED-2 (EuroClonality) consortium

In 1998 a European group was formed with the aim of optimizing and standardizing techniques for clonality analysis. With central European funding, this became the BIOMED-2 group (now referred to as the EuroClonality group). Over 40 laboratories were involved which enabled considerable pooling of resources. The group re-designed all procedures from first principles using up to date sequence information and primer design software. All potentially useful targets were optimized. For B-cell antigen receptor rearrangement this involved IGH (including partial rearrangements), IGK (including rearrangements involving the kappa deleting element, Kde) and IGL. For T-cell antigen receptor rearrangements this involved TCRB, TCRG, and TCRD. For completion, PCR amplification of t(14;18), t(11;14) and a multiplex procedure for determination of DNA quality were included. Procedures were standardized in terms of reaction conditions and cycling parameters and multiplexed to reduce the numbers of reactions required as much as possible.

The performance of each primer set was evaluated using a set of samples with well established clonality determined by Southern blot and further evaluated in terms of clonality detection rate in various lymphoma sub-types. It was previously established that different lymphoma types had different success rates in clonality analysis for example in B-cell lymphomas 13 later found to be due to somatic hypermutation. Performance of the new primer sets was considerably better than previously achieved. Evaluation of all primer sets was carried out using both HDA with polyacrylamide gels and capillary detection. The results of the BIOMED-2 collaboration were published in a comprehensive report. 5 This report has become an essential manual and reference source in the field of clonality analysis for lymphoma diagnosis and the primer sets are now used worldwide. However, there is inevitably some redundancy inherent in such a comprehensive set of tests and selection of appropriate targets is necessary to streamline the analysis. For example in B-cell clonality the use of two IGH targets and both IGK targets may be chosen. 14 For T-cell clonality analysis TCRB and TCRG genes may be targeted. 15 An example of the added value of TCR analysis in lymphoma diagnostics is shown in Figure 4 . Guidelines for selection of targets for B-cell and T-cell analysis have been published by the EuroClonality group. 2 Furthermore, a practical strategy for routine use of BIOMED-2 clonality assays on FFPE tissue has been proposed, 16 which is highly valuable and complementary to the EuroClonality strategy especially in cases with low DNA amounts. A website provides further resources including an expert manned helpline ( www.euroclonality.org ).

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Figure 4 (a) Core biopsy of sub-cutaneous mass. The lesion was ALK1 negative. Left panel H&E staining, middle panel immunohistochemistry for CD30, right panel immunohistochemistry for perforin. (b) Polyacrylamide gel (6%) of TCRG (tube B) PCR products. Lane 1, no template control; 2, positive control T-cell lymphoma showing a dominant band; 3 and 4, test case 1 in duplicate showing evidence of monoclonal T-cell expansion (reproducible dominant band); 5 and 6, test case 2 in duplicate showing no evidence of T-cell expansion (smear of products with no dominant bands); 7 and 8, test case 3 (this case) in duplicate showing evidence of monoclonal T-cell expansion (reproducible dominant band). The T-cell monoclonality confirmed a diagnosis of ALK negative anaplastic large cell lymphoma.

Importance of the pre- and post-analytical phases

In order for the clonality analysis process to work effectively, several steps in the pre-analytical phase are essential. This implies that the right tissue samples have to be delivered in a timely fashion to the molecular diagnostics laboratory and that the material is handled appropriately. It is inevitable that frozen tissue samples that yield the best quality DNA will not be available in the majority of cases. This necessitates the use of FFPE material in which the DNA will be highly and variably degraded. The degradation can be minimized by the use of neutral buffered formalin for a minimum time period. The analysis will be improved by selection of the tissue block containing the largest proportion of suspicious lymphoid cells and by microdissection of specific areas if necessary and practical. However, microdissection may in itself create a false impression of neoplastic monoclonal expansion, for example when isolated germinal centres are involved. 17 This is referred to as pseudo-clonality. Clonality analysis is thus only meaningful when significant populations of lymphocytes are analyzed rather than restricted populations. This process demands close collaboration between histopathologists and the molecular pathology laboratory. DNA can be efficiently extracted from FFPE material using dedicated kits, which maximize DNA yield and minimize concentrations of PCR inhibitors.

Equally important is the post-analytical phase following PCR analysis, during which the results must be interpreted and described accurately and delivered quickly to the pathologist to be incorporated into the pathology report. Selection of appropriate techniques and interpretation requires considerable skill and depends on the selected technology. At present this interpretation cannot be automated and recommendations are soon to be available from the EuroClonality group (see below).

Ongoing EuroClonality effort: standardization of interpretation and reporting and further optimization

Standardization of reporting of clonality analysis results is necessary as the patterns are complex and a clear message must be given to pathologists reading the reports. At present the EuroClonality group is formulating a comprehensive set of guidelines for interpretation and reporting which will make the process clear, unambiguous and consistent. Publication of this scheme is scheduled in the near future, probably in the course of 2012. The primer sets designed by the EuroClonality consortium have provided a vastly improved means of analyzing clonality in histological material. Nevertheless, improvements to the basic design can still be made and efforts are underway to further optimize TCRG gene analysis for example. The original primer sets were designed to identify the germline V and J genes used in the rearrangement. As this is not strictly necessary in pure clonality analysis, redesign of the primers to bring PCR product sizes within the same relatively narrow size range will improve correct interpretation and thus reliability of the test.

Other EuroClonality projects include development of methodology that combines the advantages of capillary electrophoresis and heteroduplex analysis and design of leader primers to amplify the complete variable region of the IGH gene for improved detection of somatic mutations by sequencing. Finally, EuroClonality also runs an external QC scheme involving testing of circulated DNA samples and interpretation of existing results. This scheme is currently accessible to members of the EuroClonality network only, but ways to disseminate this QC scheme in connection with national QC schemes in the various European countries are being evaluated.

Fluorescence in situ hybridization (FISH) analysis

Many lymphomas are characterized by the presence of typical chromosomal aberrations, which often concern translocations between antigen receptor (Ig/TCR) genes and oncogenes. As a result, the oncogene is juxtaposed to the antigen receptor gene, often resulting in ectopic expression of the oncogene involved in cell cycle regulation (e.g. cyclin D1, CCND1) or apoptotic (e.g. BCL2) processes ( Table 2 ). Other translocations in lymphoma give rise to fusion genes, thereby contributing to oncogenesis ( Table 2 ).

Table 2 Most relevant recurrent translocations in lymphoma entities

Lymphoma Translocation Involved gene(s) Estimated frequency
Mantel cell lymphoma t(11;14)(q13;q32) CCND1, IGH >95%
Follicular lymphoma t(14;18)(q21;q32) BCL2, IGH >90%
Diffuse large B-cell lymphoma t(14;18)(q21;q32)

t(8;14)(q24;q32)

3q27 translocations
BCL2, IGH

MYC, IGH

BCL6
20–30%

10–15%

30–35%
Burkitt lymphoma t(8;14)(q24;q32)

t(2;8)(p11;q24)

t(8;22)(q24;q11)
MYC, IGH

MYC, IGK

MYC, IGL
all: >95%
Extranodal marginal zone lymphoma t(11;18)(q21;q22) API2-MLT1 30% (gastric)
Anaplastic large cell lymphoma t(2;5)(p23;q35)

+ variants
NPM-ALK1

(and variants)
>50% (nodal)

0% (cutaneous)

Translocations can be considered as an alternative clonality marker (see above). However, their use as markers to classify lymphoma into subtypes is even more valuable. Translocation detection can be done by means of a specific PCR targeting the fusion gene at the DNA level (such as BCL2-IGH fusions in case of t(14;18) in follicular lymphoma) or targeting the fusion transcript at the RNA level (such as for the NMP-ALK fusion transcript in t(2;5) in anaplastic large cell lymphoma). Given the enormous variation in breakpoint sites, PCR-based detection of chromosome aberrations can however be troublesome, even when multiplex protocols are designed with multiple primers in the oncogene locus, as has been done in the BIOMED-2 programme (above). Alternatively, fluorescence in situ hybridization (FISH) analysis can be applied for translocation detection and lymphoma classification, even on paraffin sections.

Principle

In FISH analysis fluorescent DNA probes are employed that allow detection of genes on their respective chromosomal regions. In the classical FISH strategy, also referred to as fusion FISH, two differently labelled probes (mostly red and green fluorochromes) are chosen to recognize the genes involved in the translocation of interest. When no translocation is present, the two genes are not fused and hence the probes are visible as separate red and green signals; however, in case of a translocation the red and green signals co-localize leading to a fused (yellow) signal. In Figure 5 an example of double-fusion FISH for IGH/BCL2 is shown. In this way lymphomas can be classified based on the presence or absence of specific translocations. However, occasionally the fusion FISH approach would lead to false-positive signals (estimated frequency 5%). This is because in the 2-dimensional microscopic image of a tissue section or cytospin slide the two signals may seem to co-localize, despite the fact that in the 3-dimensional nuclear configuration the signals may be far apart. For this reason an alternative strategy has been developed in which two differently-labelled (red and green) FISH probes are used that target only one of the genes involved in the translocation. 17 By positioning these probes in the regions flanking the breakpoint area, a fused yellow signal is seen in case of a normal chromosome, whereas the signals break apart (split) into the individual red and green signals in case of a translocation. This split-signal FISH or break-apart FISH approach suffers less from false-positivity, and allows detection of variant translocations involving a different partner gene. 18 The very high content of tumour cells in the majority of the histopathological samples, also renders this approach very easy to interpret, as the presence of a brak is readily apparent.

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Figure 5 (a) Core biopsy of lymph node showing indistinct follicles (H&E staining). (b) Immunohistochemistry for BCL2 protein showing negative follicles. (c) Dual-fusion FISH for IGH/BCL2 showing positivity for t(14;18), thus confirming a diagnosis of follicular lymphoma.

Standardization of detection on FFPE material in the EuroFISH consortium

Both fusion FISH probe sets and break-apart FISH probe sets are now commercially available. The EuroFISH programme, a consortium of nine European laboratories, has validated a robust, standardized protocol to improve the diagnostic approach on lymphoma entities. 6 A total of 16 fluorescent split-signal FISH probe sets for the most relevant lymphoma translocations were selected to be evaluated on FFPE material of lymphomas from 10 WHO entities. The results of the EuroFISH programme show that all probes were correctly cytogenetically located, and that the standardized protocol is robust, resulting in reproducible results in approximately 90% of cases. 6 Based on this standardization, the procedure can in principle be implemented in every laboratory, which ensures that the relatively easy split-signal FISH approach is widely available in pathology laboratories for routine care.

Interpretation of FISH results

Even though technically FISH detection has been thoroughly optimized and standardized there are pitfalls in interpretation. Firstly, it should be kept in mind that with the split-signal FISH approach chromosomal breaks in the relevant genes are detected rather than the actual translocations. This implies that in certain situations it might be necessary to identify the translocation partners with a classical fusion FISH strategy. Secondly, even though some translocations are considered genetic hallmarks that define a lymphoma entity, the results of FISH analysis should always be interpreted with histopathological and clinical findings to ensure to a correct diagnosis. In this respect it is known that BCL2 translocations not only occur in follicular lymphoma but also in a subset of diffuse large cell lymphomas; similarly, MYC translocations are virtually always seen in Burkitt lymphoma, but also in 10–15% of diffuse large cell lymphomas and rarely in other types of lymphomas.

Added value of molecular diagnostics in lymphoma

Implications of Ig/TCR clonality

As indicated above, detection of Ig or TCR monoclonality serves to confirm the malignant character of a histopathologically suspect lesion. The major indications for Ig/TCR clonality testing are listed in Table 3 . In this way clonality assessment is a helpful adjunct in the process of lymphoma and leukemia diagnostics.6, 14, and 15 Conversely, monoclonality detection does not always directly imply that the involved cell population is a tumor cell population; in other words, clonality does not equal malignancy. Probably the best documented example is monoclonal gammopathy of undetermined significance (MGUS), which consists of a monoclonal plasma cell population that clinically does not behave aggressively. 19 Another example concerns a benign disorder of T-cells, which by analogy to MGUS, is sometimes referred to as T-cell clonopathy of undetermined significance (TCUS).20 and 21 Furthermore, it has been well documented that clonality can be detected in histologically defined reactive lesions. Detailed molecular Ig/TCR analysis in a series of more than 100 reactive lesions revealed polyclonality in only about 75% of samples, whereas suspected oligoclonality was seen in 15% that could be explained by some kind of immune activation. 22 Even more intriguing were those samples (about 10%) with clear signs of monoclonal Ig/TCR products reflecting a B- or T-cell expansion. A few were shown to be early lymphomas that were missed initially, whereas in some samples after review no clear explanation for Ig/TCR clonality could be found. The techniques can reliably detect monoclonal expansion but cannot predict behaviour. This illustrates that caution is warranted in interpreting clonality data.

Table 3 Most relevant indications for molecular diagnostics on lymphoid histological samples

Histological pattern Molecular tests
Expansion of interfollicular T-cell areas suspect of early phase of angioimmunoblastic T-cell lymphoma TCR and Ig clonality (∼5% of cases show Ig clonality without TCR clonality; Brüggeman 2007)
Middle and large T-cell expansion inside B-cell follicles suspect of a peripheral T-cell lymphoma NOS in a follicular variant TCR clonality
Expansion of paracortical areas in a lymph node arising in patients with mycosis fungoides TCR clonality
Marginal zone expansion in a lymph node, spleen, or an extranodal sample without demonstration of light chain restriction by immunohistochemistry, suspect of marginal zone lymphoma (MALT, splenic, nodal) Ig clonality

FISH for MLT1 (if important to differentiate MALT from non-MALT marginal zone lymphoma)
Immunohistochemically BCL2 negative follicles in a sample suspect of follicular lymphoma Ig clonality

BCL2-IGH clonality by PCR

FISH for BCL2, BCL6 a
Differential diagnosis between follicular lymphoma with marginal differentiation vs. marginal zone lymphoma with follicular colonization BCL2-IGH clonality by PCR

FISH for BCL2, BCL6 a
Suspicion of mantle cell lymphoma but overfixed with negative cyclin D1 staining of internal positive control (stromal cells) BCL1-IGH (MTC) clonality by PCR

FISH for CCND1 a
Discordance between morphology and clinical diagnosis According to the clinical suspicion and history
In situ follicular or mantle cell lymphoma BCL2-IGH and BCL1-IGH (MTC) clonality by PCR

Ig clonality (microdissection might be useful due to low sensitivity)

a Interphase FISH is the preferred option over a PCR-based approach for translocation detection, as FISH can be applied to the (immuno)histologically suspect area.

To prevent misinterpretation, Ig/TCR clonality analysis results should thus always be integrated with histological, immunophenotypic and clinical data. We therefore envisage a model of molecular biologists, pathologists, immunologists, and clinicians interacting by means of multidisciplinary patient meetings. In such meetings correct interpretation of the Ig/TCR data can be critically discussed in the context of histopathological, flow cytometric, and clinical data. In this way over- and under-interpretation of clonality results can be prevented. This requires detailed insight into the technical and biological pitfalls that may complicate clonality testing (see below).

Pitfalls and immunobiological explanations for Ig/TCR clonality

Ig/TCR PCR products should generally be in the correct size range to be interpreted as true rearrangement products. This avoids misinterpretation of non-specific products; however, products outside the range may be true rearrangements. This is because under- or oversized Ig/TCR products may result from internal V gene deletions or extended amplifications from a downstream J gene (see also Table 4 ).23, 24, and 25 The probability of products outside the standard size ranges being significant should be considered in the light of products seen in other samples, especially when DNA quality is sub-optimal. Multiple clonal signals might pose problems to distinguish monoclonality from oligoclonality. Insight into the expected number of rearranged PCR products for a particular locus is critical for correct interpretation as some primer sets yield more than one product per allele. 26

Table 4 Pitfalls in Ig/TCR clonality testing

Pitfall Phenomenon Solution/action
Bands/peaks outside size range CDR3 regions/junctions outside 5–95% size interval True rearrangement product; in case of doubt, sequence for confirmation
Undersized bands/peaks E.g. internal deletion in VH/Vκ/Vλ gene (SHM-related) Potential rearrangement product; sequence for confirmation
Oversized bands/peaks E.g. extended amplification from downstream J gene (e.g. due to SHM in actual JH gene) Potential rearrangement product; sequence for confirmation
Multiple clonal signals Bi-allelic rearrangements

Biclonality
Consider the number of potential rearrangements per allele/locus a and judge whether this fits with clonality or biclonality
Lack of clonal signal and lack of polyclonal Gaussian curve
  • 1. Few T/B cells
  • 2. Poor DNA quality
  • 3. Clonal signal not detected due to SHM in malignant cells
  • 1. Check T/B cell content by histology or flow cytometry
  • 2. Check DNA quality in control PCR
  • 3. Evaluate other framework or Ig target
Selective amplification and pseudo-clonality, due to low level of specific template Few T/B cells in sample Repeat multiple PCRs (same tissue, second independent DNA isolation, and/or related tissue) → compare patterns for consistency
Oligoclonal T-/(B)-cell repertoire in peripheral blood of elderly individuals Incomplete immune system, (e.g. immunosenescence) Repeat multiple PCRs (same tissue, second independent DNA isolation, and/or related tissue) → compare patterns for consistency and compare with primary process (in case of staging)
Oligo-/monoclonality in histologically reactive lesion Exaggerated immune response with dominant specificity (e.g. large germinal centers)
  • 1. Repeat mulpiple PCRs (same tissue, second independent DNA isolation, and/or related tissue) → compare patterns for consistency
  • 2. Re-evaluate histopathology

a In TCRB and IGK loci multiple rearrangements can be detectable per allele, which influences the number of peaks/bands that is compatible with a single clone. Complex patterns may be seen after heteroduplex analysis.

Abbreviation: SHM, somatic hypermutation.

Furthermore, there are several immunobiological aspects to be considered when interpreting Ig/TCR clonality data ( Table 4 ). Firstly, somatic hypermutation processes might cause lack of amplification of a clonal Ig product, which can be overcome by analyzing multiple Ig targets (the complementarity concept). Secondly, the fact that only few B or T-cells are present in the sample (e.g. in skin tissues) might cause preferential amplification leading to a false impression of monoclonality. This stresses the importance of evaluating duplicate PCR reactions to establish reproducibility of clonality patterns and products. Finally, under certain conditions multiple clonal peaks might be present as a result of an exaggerated immune response or in an ageing immune system (immunosenescence),22 and 27 which should not be misinterpreted as signs of a malignancy.

Applications of Ig/TCR clonality testing

Ig/TCR clonality analysis can be used in many clinical situations ( Table 5 ). 27 Beyond any doubt, the most widely used application is discriminating tumor cells from a reactive or normal lymphoid cell population. The analytical sensitivity (around 5–10%) of the multiplex Ig/TCR PCR assays is generally sufficient for detecting a lymphoma or leukemia cell population at clinical presentation. Moreover, testing of multiple Ig or TCR targets in PCR (complementarity of targets), has resulted in higher detection rates with low false negativity. 2 In ambiguous cases, detection of translocations (e.g. CCND1 and BCL2 translocations in mantle cell lymphoma and follicular lymphoma, respectively) by PCR or by FISH (see below) might lend further support for the monoclonal character of the suspicious cell population.

Table 5 Applications of Ig/TCR clonality testing

Application Value
Discrimination of tumor vs. reactive vs. Normal ++
Staging: evaluation of dissemination/localization (note: limited sensitivity level of 1–10%) +/++
Evaluation of clonal relationship between multiple lesions at same time ++
Evaluation of clonal relationship between diagnosis and disease recurrence (relapse) ++
Lineage determination (T vs. B vs. NK) +
Monitoring/evaluation of treatment effectiveness (note: limited sensitivity level of 1–10%) +

Another important application is identifying extranodal localization of lymphomas (staging), for example in blood or bone marrow. Dissemination to other compartments can be identified on the basis of Ig/TCR products that are identical to monoclonal products in the primary tumour. The true value of this strategy is, however, greatly influenced by the analytical sensitivity of the multiplex PCR methods, which limits detection in extranodal sites to above 1–5% or so. The same problem arises in using the Ig/TCR clonality assays for monitoring purposes. As the required sensitivity for monitoring is mostly below 1%, but preferably below 0.1%, in practice these assays are of low value.

Another area in which clonality analysis can be very useful, is to establish the clonal relationship between multiple lesions. When such lesions occur at the same time in different parts of the body, Ig/TCR clonality results might help to discriminate between a single tumor or two distinct tumours. In recurrence of disease over time, clonality results will help to discriminate between a true relapse and a second malignancy.

Finally, lineage assignment is a complex application that should be considered with caution. This is because cross-lineage Ig/TCR rearrangements may occur, i.e. the presence of Ig rearrangements in T-cell malignancies and TCR rearrangements in B-cell malignancies. This phenomenon is frequently seen in immature leukemias and lymphomas, 28 but can also appear in 5–10% of mature B-cell malignancies.14 and 29 Lineage infidelity can also be caused by the parallel occurrence of B- and T-cell clones in a lymphoma.14 and 15 Lineage determination is perhaps most reliable in case of suspect NK-cell populations, where the lack of monoclonal TCR (and Ig) rearrangements is in keeping with the NK-cell lineage.

Implications of translocation detection

As stated above, translocation detection in lymphoma can be helpful as an additional clonality marker in rare situations in which clonality cannot be firmly established by means of Ig/TCR clonality analysis. However, a far more relevant application lies in classification of the lymphoma (see also Table 3 ). Traditionally this was done by means of karyotyping, but this was only easily applicable to cell suspensions from blood, bone marrow or aspirated lymph node samples. In haematopathology of tissues, translocation detection has been much more limited for this reason, and has relied on the immunohistochemical identification of the aberrantly expressed protein (e.g. BCL2 in germinal centre cells, Cyclin D1). Since the introduction of molecular genetic techniques, i.e. PCR and especially FISH, translocation detection in tissues has come within reach of many laboratories that have such facilities. The recent optimization of FISH methods in paraffin sections has helped to broadly implement this strategy in patient care. Correct classification is not only important with respect to prognosis, but also has implications for tailored therapy strategies.

Conclusion

The diagnosis of the lymphomas remains a challenging area and the current approach of morphological assessment supplemented by immunohistochemistry with FISH and PCR based clonality analysis in difficult cases is likely to be with us for some time. The use of next generation sequencing and comprehensive gene expression analysis methods for diagnosis are some way off. In the mean-time we have to ensure that our existing molecular methods are used to their full potential. This means education and dissemination of new protocols by inter-laboratory communication and collaboration. It is essential that ongoing optimization and development continues so that we do our best to ensure best practice for patient care.

Practice points

 

  • PCR-based clonality testing and FISH-based translocation detection show added value in the diagnosis and classification of lymphomas
  • Ig/TCR multiplex PCR clonality assays show unprecedented high clonality detection rates
  • FISH strategies allow translocation detection in lymphoma on paraffin material
  • Standardization of PCR clonality and FISH strategies has paved the way for routine application in patient care
  • Knowledge of immunobiology and recognition of pitfalls are essential for correct interpretation of the results obtained with these assays
  • Interpretation and reporting of these molecular methodologies require further standardization

Acknowledgement

We thank the members of the BIOMED-2/EuroClonality network for a longstanding collaboration and many fruitful discussions, which are at the basis of this review. We thank Mrs. Marieke Comans-Bitter for help in preparing figures, and Dr. Alan Ramsay and Dr. Hongtao Ye for histopathology and FISH images respectively.

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Footnotes

Tim C Diss PhD is a Clinical Scientist at the Histopathology Department, University College London Hospital and Department of Pathology, University College London, UK. Conflicts of interest: none declared

Thierry J Molina MD PhD is a Pathologist at the Service de Pathologie, AP-HP, Hôpitaux Universitaires Paris Centre, Université Paris Descartes, Paris, France. Conflicts of interest: none declared

Jose Cabeçadas MD is a Pathologist at the Departamento de Diagnóstico Laboratorial IPOLFG – Serviço de Anatomia Patológica, Lisbon, Portugal. Conflicts of interest: none declared

Anton W Langerak PhD is a Medical Immunologist at Erasmus Medical Centre, Rotterdam, The Netherlands. Conflicts of interest: none declared