Incomplete DJH rearrangements as a novel tumor target for minimal residual disease quantitation in multiple myeloma using real-time PCR

Article metrics

Abstract

The hypervariable regions of immunoglobulin heavy-chain (IgH) rearrangements provide a specific tumor marker in multiple myeloma (MM). Recently, real-time PCR assays have been developed in order to quantify the number of tumor cells after treatment. However, these strategies are hampered by the presence of somatic hypermutation (SH) in VDJH rearrangements from multiple myeloma (MM) patients, which causes mismatches between primers and/or probes and the target, leading to a nonaccurate quantification of tumor cells. Our group has recently described a 60% incidence of incomplete DJH rearrangements in MM patients, with no or very low rates of SH. In this study, we compare the efficiency of a real-time PCR approach for the analysis of both complete and incomplete IgH rearrangements in eight MM patients using only three JH consensus probes. We were able to design an allele-specific oligonucleotide for both the complete and incomplete rearrangement in all patients. DJH rearrangements fulfilled the criteria of effectiveness for real-time PCR in all samples (ie no unspecific amplification, detection of less than 10 tumor cells within 105 polyclonal background and correlation coefficients of standard curves higher than 0.98). By contrast, only three out of eight VDJH rearrangements fulfilled these criteria. Further analyses showed that the remaining five VDJH rearrangements carried three or more somatic mutations in the probe and primer sites, leading to a dramatic decrease in the melting temperature. These results support the use of incomplete DJH rearrangements instead of complete somatically mutated VDJH rearrangements for investigation of minimal residual disease in multiple myeloma.

Introduction

Multiple myeloma (MM) is a mature B-cell malignancy characterized by the accumulation of clonal plasma cells in the bone marrow (BM) producing high amounts of monoclonal immunoglobulin (Ig). The origin of the neoplastic cells in MM is thought to be a postfollicular memory B cell, although there has been a great deal of debate regarding the possibility of a less mature origin or even of a stem cell origin.1,2,3 Evidence of a postfollicular origin comes from the Ig gene configuration in plasma cells, which are found to be somatically hypermutated, without intraclonal variation and class-switched.1,4 High-dose therapy (HDT) followed by stem cell transplantation (SCT) leads to a higher rate of complete remissions (cRs), although most patients eventually relapse.5,6,7,8 A clinical correlation between PCR detection of tumor cells after SCT and outcome has been suggested,9,10 but quantitative studies are needed for the evaluation of distinct molecular responses.

Different quantitative IgH PCR assays have proven to be useful but they are frequently time-consuming and need additional post-PCR manipulations, which could lead to PCR crosscontamination.7,11,12,13 Real-time PCR are usually preferred to end point calculations or limiting dilutions, because real-time PCR is simpler and allows automated analyses in a closed tube. The development of TaqMan technology, as well as the new generation of optical systems such as the ABI PRISM 7700 sequence detector system (PE Applied BioSystems, Foster City, CA, USA), has improved the quantification of tumor burden in treated patients.14,15,16 Immunoglobulin heavy-chain (IgH) real-time PCR is based on using the CDR3 sequence for the design of an ASO-primer or probe combined with JH and VH primers.17,18 The hypermutated IGH genes in MM have hampered molecular analyses by PCR because of the frequent occurrence of mismatches between the VH or JH segments and the corresponding primers.19 For this reason, patient-specific probes and/or primers must be designed in order to avoid mismatches caused by somatic hypermutation (SH),14 which is significantly more expensive and time-consuming than using consensus probes. Consequently, real-time quantitative PCR (RQ-PCR) analyses of the clonogenic VDJH rearrangements for the detection of minimal residual disease (MRD) appear to be much more complicated when applied to postfollicular B-cell malignancies than in immature B-cell malignancies.17,18,20 We have recently demonstrated that in 60% of MM patients, the nonfunctional IgH allele comprises an incomplete DJH unmutated rearrangement (González D et al. Blood 2001; 98: 1562; abstract), which makes them an attractive alternative to hypermutated complete VDJH rearrangements in MM as targets for RQ-PCR-based MRD investigation. Here, we provide evidence that DJH rearrangements used as RQ-PCR targets work better in terms of reliability, sensitivity and reproducibility than VDJH rearrangements in the same patients.

Materials and methods

Cell samples and DNA extraction

Cell samples were obtained from BM aspirates of eight untreated MM patients with a tumor load ranging from 10 to 93%. High molecular weight DNA was isolated by standard proteinase K digestion, phenol–chloroform extraction and ethanol precipitation.21 All patients were randomly selected from a previous series of 44 patients that had both IGH alleles rearranged with one incomplete DJH rearrangement and one complete VDJH rearrangement (González D et al. Blood 2001; 98: 1562; abstract).

Identification of IGH rearrangements

For amplification of complete VDJH rearrangements, three different sets of family specific primers and one JH consensus primer were used in three different multiplexed PCR reactions, covering the three framework regions (FR). Amplification of incomplete DJH rearrangements was performed in two different reactions using family specific primers for DH1–DH6 and DH7 families, respectively, together with the consensus JH primer (Figure 1). All primers had been newly designed during the BIOMED-2 Concerted Action, ‘PCR-based clonality studies for early diagnosis of lymphoproliferative disorders’ (PL96-3936) (van Dongen JM et al. Blood, 2001; 98: 129; abstract). All reactions were carried out in 50 μl containing 0.1 μg DNA samples and 10 pmol of each primer. PCR products were eluted from the polyacrylamide gels and directly sequenced in an automated ABI 377 DNA sequencer using Big-Dye terminators (Applied Biosystems, Foster City, CA, USA). In order to avoid nucleotide misinterpretations because of Taq error, all products were sequenced at least twice from different PCR reactions using 5′ VH/DH and/or 3′ JH primers. Germline VH, DH and JH segments from complete VDJH rearrangements were identified by comparison with the V base22 and IGMT database23 using on-line DNAPLOT (MRC Center for Protein Engineering). DH and JH germline segments from incomplete DJH rearrangements were identified using BLAST search in the DH–JH germline locus sequence (accession number EMB/X97051).

Figure 1
figure1

BIOMED-2 PCR strategy VDJH amplification is carried out in three separate reactions containing the JH consensus primer and a combination of the different VH family specific primers for FR1, FR2 and FR3 regions (tubes 1, 2 and 3, respectively). DJH amplification is performed in two separate reactions containing the JH consensus primer combined with the DH family specific primers (DH1–DH6 in tube 1 and DH7 in tube 2).

ASO-primer design

RQ-PCR strategy using JH consensus probes was adapted from the method of Verhagen et al.20 Briefly, three JH consensus probes (JH1.2.4.5, JH3 and JH6) covering all six JH segments were used in combination with the ASO primer and one of the six JH intron-specific primers (JH1–JH6) (Table 1) (Figure 2). For each rearrangement, one ASO primer complementary to the DH–JH or VH–DH junction was designed using OLIGO 6.1 software (W Rychlik, Molecular Biology Insights, Cascade, CO, USA). Design conditions avoided primer–dimer formation with ΔG higher than −3.5 kcal/mol, GC-rich 3′ ends and Tm differences with JH primers higher than 2°C. Amplicon sizes were always lower than 170 bp.

Table 1 Primer and probe sequences used for RQ-PCR
Figure 2
figure2

(a) Diagrammatic representation of consensus RQ-PCR using complete VDJH rearrangements, and the strategy to amplify and sequence the primer and probe sites. (b) Representation of consensus RQ-PCR for incomplete DJH rearrangements. Arrows indicate primer positions and bold lines represent positions of the TaqMan JH consensus probes.

RQ-PCR analysis

RQ-PCR was performed in MicroAmp 96-well optical plates on an ABI PRISM 7700 sequence detection system (PE Applied BioSystems, Foster City, CA, USA). All reactions were carried out in 25 μl final volume, containing 12.5 μl of 2 × TaqMan Universal Mastermix (PE Applied BioSystems, Foster City, CA, USA), including AmpErase Uracil N-Glycosylase (UNG), 200 nM of each primer and 300 nM of probe. A measure of 1 μg genomic DNA was added in triplicate for RQ-PCR assay. RQ-PCR conditions included 2 min at 50°C for UNG activation, 10 min at 95°C for AmpliTaq Gold activation, and 50 cycles of PCR with 10 s denaturation at 95°C followed by 30 s at 59–63°C for annealing/extension (depending on each particular ASO primer). The cycle in which fluorescent emission reaches 10-fold the basal emission is known as the cycle threshold (CT), a value that is proportional to the copy number of the target gene.

For ASO-primer specificity testing, we performed an RQ-PCR assay that included the diagnosis DNA from the patient as positive control for the reaction, and a buffy coat pool from healthy individuals as negative control. Each ASO primer was tested at different annealing temperatures, ranging from 59 to 63°C in order to determine the maximum sensitivity and specificity for each particular assay. The quality and quantity of the sample was checked by RQ-PCR amplification of the albumin gene, as previously described.18

Analysis of patient samples

Diagnosis DNA from each patient was 10-fold serially diluted into the buffy coat pool from healthy individuals up to 10−5. Furthermore, between the lower dilutions (10−3–10−5), we performed two additional five-fold dilution steps to ensure reliability of the results obtained in dilutions containing only a few copies.17 Thus, standard curves were calculated using the following dilutions: 10−1, 10−2, 10−3, 5 × 10−4, 10−4, 5 × 10−5 and 10−5. Calculations were made to allow amplification of 1 μg of each dilution. Based on the assumption that 1 μg DNA contains 1.6 × 105 genomes, amplification of the 10−4 dilution of diagnostic sample represents a detection rate of 1–20 tumor cells (depending on tumor burden at diagnosis in each patient) within 105 normal cells. All patients were analyzed by comparison of standard curves obtained from diluted genomic DNA in both types of rearrangements. Successful RQ-PCR was assessed according to the following three criteria: (i) specific amplification of at least 10 copies of tumor-specific IGH rearrangement; (ii) lack of nonspecific amplification in the buffy coat control; (iii) standard curves generating at least a four-linear dynamic range with correlation coefficients (r) of at least 0.98.14

Analysis of primer and probe site mutations in VDJH and DJH rearrangements

In order to assess possible mutations in the sites of annealing primers and probes in IgH gene rearrangements, we performed a shifted PCR with the ASO primer upstream and the next JH intron-specific primer downstream (Figure 2a). These products were sequenced and compared to the sequence of JH consensus probes and JH intron primers. The MeltCalc program24 was used to estimate the changes that somatic mutations produce in ΔTm for each probe and primer in VDJH rearrangements.

Results

Eight MM patients carrying both an incomplete DJH and a complete VDJH rearrangement were randomly selected from a series of 44 MM patients. Sequences of the junction regions of each rearrangement are shown in Table 2.

Table 2 Junction regions and primer locations of DH and VDJH rearrangements

Evaluation of ASO-primer design

16 primers were designed for the eight patients containing two rearrangements each (Table 1). All of them were successful since they produced a positive signal on the diagnostic sample, while no amplification signals were detected with any of these primers in the negative control.

Comparison of RQ-PCR effectiveness between DJH and VDJH rearrangements

Upon analyzing RQ-PCR data, all DJH rearrangements fulfilled the three criteria for successful RQ-PCR assay in the eight MM patients: positive signals were not seen in the buffy coat control with any of the ASO primers designed for DJH rearrangements, correlation coefficient values for standard curves were always at least 0.98, and the limit of detection was 1–5 tumor cells in 1.6 × 105 normal cells (Table 3). The mean r value was 0.986 with an overall detection rate of 1.7 cells and a dynamic linear range of 4.6 log on average. By contrast, only three out of eight (37.5%) VDJH rearrangements fulfilled the established criteria, mainly because the standard curves generated gave rise to r values below 0.98 (Table 3). Furthermore, for two VDJH rearrangements the r values from the standard curves were lower than 0.90–0.88 and 0.2- (Table 3), and the limit of detection within 1.6 × 105 normal cells was 15 and 75 tumor cells, respectively. However, in the remaining three VDJH-derived standard curves with r values of 0.96 and 0.97, we could obtain a sensitivity of 1–5 cells, which is similar to that obtained with DJH-based RQ-PCR.

Table 3 Coefficients of correlation, linear range and limit of detection of RQ-PCR using DJH and VDJH rearrangements as tumor targets

JH consensus probes for RQ-PCR in MM

Owing to the high degree of SH in VDJH rearrangements from MM patients, we attempted to assess if SH could lead to a different effectiveness in RQ-PCR using JH consensus probes when applied to DJH or VDJH rearrangements. We amplified and sequenced the region spanning the JH probe and JH intron primer binding sites (Figure 2). All DJH rearrangements from these eight patients were previously seen to be unmutated (González D et al. Submitted for publication; data not shown). Consequently a perfect match between probes/primers and the target sequence can ensure a successful RQ-PCR in the eight patients. All three patients in which a successful RQ-PCR was achieved (at least r=0.98) using VDJH rearrangements had two or less mutations in the probe and primer binding site. By contrast, the remaining five patients with a suboptimal r value for the standard curve had more than two mutations, ranging from 3 to 7 nucleic acid changes (Table 4).

Table 4 Probes and reverse primer binding site mutations from VDJH rearrangements and ΔTm changes

In our study, there is a correlation between total number of mutations (in both primer and probe sites) and failure of the RQ-PCR assay. Furthermore, in two patients in which only one point mutation was present in the probe site, the RQ-PCR gave rise to r values of 0.96 and 0.97 (Table 4) because of the presence of two further mutations in the primer binding site. The patient with r=0.88 had three mutations and one point deletion in the probe site, and three mutations in the primer site, which explains the failure of the RQ-PCR. Interestingly, the sequence of probe and primer sites could not be obtained in the patient in whom VJDH-based RQ-PCR produced a lowest r value of 0.2, and the detection limit was 75 cells. The lack of amplification with the next JH intron primer could be due to of a deletion or, alternatively, an exceptionally high degree of SH in the JH-Cμ intron region.

Melting analyses for probe and primer mismatches

The MeltCalc program has proven to be an efficient approach for calculating differences in the melting temperature (Tm) of oligonucleotide probes.24 In order to obtain a more accurate determination of how the VDJH mutations affect the RQ-PCR, we analyzed the changes that somatic mutations produced in the Tm of the probes and primers for each VDJH rearrangement. As we could not obtain the complete sequence of one of the eight valuable patients (UPN 4994), we performed melting calculations for the remaining seven VDJH rearrangements. Table 4 shows the point mutations (deletions are not included because of program limitations) affecting the Tm variations (ΔTm), and cumulative values for these two variables at the probe and primer sites. In the three VDJH rearrangements in which successful RQ-PCR was achieved, the values for ΔTm were always below 6°C. By contrast, in the three VDJH rearrangements that gave rise to a standard curve with values of 0.97 and 0.96, the ΔTm increased up to a range between 9 and 13°C. The VDJH rearrangement with r=0.88 had a ΔTm=23.8°C, which is significantly higher. These results correlate with the number of point mutations, since VDJH rearrangements with more than three cumulative mutations in the primer and probe sites are those that yield ΔTm>9°C and standard curves with r<0.98. However, it may be noted that a single point mutation (eg UPN 4572: only one point mutation corresponded to a ΔTm=5.8°C) can cause more drastic changes in the ΔTm than two different point mutations (eg UPN 11000: two different point mutations in the primer binding site caused a ΔTm=5.5°C) (Table 4).

Discussion

The use of high-dose chemotherapy in MM patients has highlighted the impact of the quality of response (complete vs partial response) on disease outcome. 5,6,7,8,9,10 Thus, an accurate quantification of residual cells following treatment would be essential for monitoring MRD in MM patients. Although several approaches have been studied for tumor cell quantification, there are still difficulties for their clinical application. Firstly, consensus PCR strategies with sensitivities between 10−1 and 10−3 can be misleading, since a high rate of molecular CRs would be achieved without influencing outcome.10 Secondly, very sensitive assays such as ASO-PCR show that almost all patients remain positive, which also hampers the discrimination of risk categories.7,11,12,13 This approach has been successfully modified by using limiting dilutions25,26 or band densitometry, but this involves post-PCR steps, which increase crossover contamination and have a high intra- and interassay variation (up to 31%).15 RQ-PCR using TaqMan technology, by contrast, is a very reproducible approach with a coefficient of variation bellow 2%.15

RQ-PCR has proved to be a successful approach when applied to hematological malignancies carrying gene translocations as tumor markers.27,28,29,30 For B- and T-cell malignancies in which no recurrent well-defined translocations are present, B- and T-cell receptor genes are used as tumor markers for RQ-PCR.17,20 In the last 4 years, RQ-PCR has become an attractive and useful approach for the detection of MRD in immature B-cell malignancies and the subset of B-CLL without somatic mutations,17 mainly because of the utilization of consensus probes in the JH region thereby avoiding the need to synthesize allele-specific probes (ASO probes) for each patient, which is very expensive and time-consuming.18,31 Unfortunately, this approach is less optimal for MRD analysis of postgerminal center derived-B-cell malignancies containing a high level of SH, because of mismatches between the probes/primers and the mutated VDJH rearrangement. Ladetto et al14 has suggested that zero or one point mutation in the probe binding site does not influence the effectiveness of the RQ-PCR, and the presence of three or more point mutations in that site is always associated with failure of the RQ-PCR. They have also suggested that when two mutations are present in the probe binding site, the effectiveness of the experiment depends on the type of mutations and whether they are close or not to the 5′ end of the probe binding site.14 However, our data demonstrate that RQ-PCR effectiveness is dramatically affected not only by mutations in the probe site but also in the primer binding site. Thus, the number of total mutations in both probe and primer binding sites is the parameter that could predict whether the experiment is going to be successful or not. In four out of the eight patients analyzed here, we found only one point mutation in the probe site, but the effectiveness of the experiment varied depending on the amount of mutations in the primer binding site. Thus, only those patients with less than three total mutations fulfilled the criteria of an optimal RQ-PCR. Moreover, we also investigated the variation that all mutations in VDJH rearrangements might produce in the melting temperature of probes and primers. These analyses have shown that the parameter that predicts whether a VDJH rearrangement is appropriate or not for RQ-PCR analysis using JH consensus probes is cumultative ΔTm values from both probe and primer. Thus, a total ΔTm value higher than 9°C is associated with lower effectiveness, while total values of less than 6°C can ensure that the VDJH rearrangement will result in an optimal RQ-PCR analysis. We think that this parameter of total ΔTm is more informative because it takes into account the type and the position of mutation together with the nucleotide environment in which such mutation is present, and can be predicted just from the sequence of the VDJH rearrangement.

Conclusion

In summary, this is the first study using incomplete DJH rearrangements as tumor markers for RQ-PCR in MM. We have demonstrated that DJH rearrangements generate standard curves with r0.98 and are specific and sensitive, allowing the detection of up to five tumor cells in a background of 1.6 × 10−5 normal cells (in a range of up to 5 logs). Our results support the use of incomplete DJH rearrangements instead of hypermutated VDJH rearrangements as preferential RQ-PCR targets for monitorizing of MRD in MM patients. Furthermore, when using VDJH rearrangements as RQ-PCR targets, the particular sequence must be analyzed prior to developing an RQ-PCR assay in MM, in order to evaluate if they are to be successful targets.

References

  1. 1

    Vescio RA, Cao J, Hong CH, Lee JC, Wu CH, Der DM et al. Myeloma Ig heavy chain V region sequences reveal prior antigenic selection and marked somatic mutation but no intraclonal diversity. J Immunol 1995; 155: 2487–2497.

  2. 2

    Kosmas C, Stamatopoulos K, Stavroyianni N, Zoi K, Belessi C, Viniou N et al. Origin and diversification of the clonogenic cell in multiple myeloma: lessons from the immunoglobulin repertoire. Leukemia 2000; 14: 1718–1726.

  3. 3

    Pilarski LM, Masellis S, Szczepek A, Mant MJ, Belch AR . Circulating clonotypic B cells in the biology of multiple myeloma: speculations on the origin of myeloma. Leukemia Lymphoma 1996; 22: 375–383.

  4. 4

    Bakkus MH, Heirman C, van Riet I, van Camp B, Thielemans K . Evidence that multiple myeloma Ig heavy chain VDJ genes contain somatic mutations but show no intraclonal variation. Blood 1992; 80: 2326–2335.

  5. 5

    Fermand JP, Ravaud P, Chevret S, Divine M, Leblond V, Belanger C et al. High-dose therapy and autologous peripheral blood stem cell transplantation in multiple myeloma: up-front or rescue treatment? Results of a multicenter sequential randomized clinical trial. Blood 1998; 92: 3131–3136.

  6. 6

    Dreyfus F, Ribrag V, Leblond V, Ravaud P, Melle J, Quarre MC et al. Detection of malignant B cells in peripheral blood stem cell collections after chemotherapy in patients with multiple myeloma. Bone Marrow Transplant 1995; 15: 707–711.

  7. 7

    Corradini P, Voena C, Astolfi M, Ladetto M, Tarella C, Boccadoro M et al. High-dose sequential chemoradiotherapy in multiple myeloma: residual tumor cells are detectable in bone marrow and peripheral blood cell harvests and after autografting. Blood 1995; 85: 1596–1602.

  8. 8

    Barlogie B, Jagannath S, Desikan KR, Mattox S, Vesole D, Siegel D et al. Total therapy with tandem transplants for newly diagnosed multiple myeloma. Blood 1999; 93: 55–65.

  9. 9

    Corradini P, Voena C, Tarella C, Astolfi M, Ladetto M, Palumbo A et al. Molecular and clinical remissions in multiple myeloma: role of autologous and allogeneic transplantation of hematopoietic cells. J Clin Oncol 1999; 17: 208–215.

  10. 10

    Lopez-Perez R, Garcia-Sanz R, Gonzalez D, Balanzategui A, Chillon MC, Alaejos I et al. The detection of contaminating clonal cells in apheresis products is related to response and outcome in multiple myeloma undergoing autologous peripheral blood stem cell transplantation. Leukemia 2000; 14: 1493–1499.

  11. 11

    Bergsagel PL, Smith AM, Szczepek A, Mant MJ, Belch AR, Pilarski LM . In multiple myeloma, clonotypic B lymphocytes are detectable among CD19+ peripheral blood cells expressing CD38, CD56, and monotypic Ig light chain. Blood 1995; 85: 436–447.

  12. 12

    Vescio RA, Han EJ, Schiller GJ, Lee JC, Wu CH, Cao J et al. Quantitative comparison of multiple myeloma tumor contamination in bone marrow harvest and leukapheresis autografts. Bone Marrow Transplant 1996; 18: 103–110.

  13. 13

    Billadeau D, Quam L, Thomas W, Kay N, Greipp P, Kyle R et al. Detection and quantitation of malignant cells in the peripheral blood of multiple myeloma patients. Blood 1992; 80: 1818–1824.

  14. 14

    Ladetto M, Donovan JW, Harig S, Trojan A, Poor C, Schlossnan R et al. Real-Time polymerase chain reaction of immunoglobulin rearrangements for quantitative evaluation of minimal residual disease in multiple myeloma. Biol Blood Marrow Transplant 2000; 6: 241–253.

  15. 15

    Gerard CJ, Olsson K, Ramanathan R, Reading C, Hanania EG . Improved quantitation of minimal residual disease in multiple myeloma using real-time polymerase chain reaction and plasmid-DNA complementarity determining region III standards. Cancer Res 1998; 58: 3957–3964.

  16. 16

    Rasmussen T, Poulsen TS, Honore L, Johnsen HE . Quantitation of minimal residual disease in multiple myeloma using an allele-specific real-time PCR assay. Exp Hematol 2000; 28: 1039–1045.

  17. 17

    Bruggemann M, Droese J, Bolz I, Luth P, Pott C, von Neuhoff N et al. Improved assessment of minimal residual disease in B cell malignancies using fluorogenic consensus probes for real-time quantitative PCR. Leukemia 2000; 14: 1419–1425.

  18. 18

    Pongers-Willemse MJ, Verhagen OJ, Tibbe GJ, Wijkhuijs AJ, de Haas V, Roovers E et al. Real-time quantitative PCR for the detection of minimal residual disease in acute lymphoblastic leukemia using junctional region specific TaqMan probes. Leukemia 1998; 12: 2006–2014.

  19. 19

    Garcia-Sanz R, Lopez-Perez R, Langerak AW, Gonzalez D, Chillon MC, Balanzategui A et al. Heteroduplex PCR analysis of rearranged immunoglobulin genes for clonality assessment in multiple myeloma. Haematologica 1999; 84: 328–335.

  20. 20

    Verhagen OJ, Willemse MJ, Breunis WB, Wijkhuijs AJ, Jacobs DC, Joosten SA et al. Application of germline IGH probes in real-time quantitative PCR for the detection of minimal residual disease in acute lymphoblastic leukemia. Leukemia 2000; 14: 1426–1435.

  21. 21

    Gonzalez M, Gonzalez D, Lopez-Perez R, Garcia-Sanz R, Chillon MC, Balanzategui A et al. Heteroduplex analysis of VDJ amplified segments from rearranged IgH genes for clonality assessments in B-cell non-Hodgkin's lymphoma. A comparison between different strategies. Haematologica 1999; 84: 779–784.

  22. 22

    Cook GP, Tomlinson IM . The human immunoglobulin VH repertoire. Immunol Today 1995; 16: 237–242.

  23. 23

    Lefranc MP . IMGT, the international ImMunoGeneTics database. Nucleic Acids Res 2001; 29: 207–209.

  24. 24

    Schutz E, von A . Spreadsheet software for thermodynamic melting point prediction of oligonucleotide hybridization with and without mismatches. Biotechniques 1999; 27: 1218–1222, 1224.

  25. 25

    Schiller G, Vescio R, Freytes C, Spitzer G, Sahebi F, Lee M et al. Transplantation of CD34+ peripheral blood progenitor cells after high-dose chemotherapy for patients with advanced multiple myeloma. Blood 1995; 86: 390–397.

  26. 26

    Henry JM, Sykes PJ, Brisco MJ, To LB, Juttner CA, Morley AA . Comparison of myeloma cell contamination of bone marrow and peripheral blood stem cell harvests. Br J Haematol 1996; 92: 614–619.

  27. 27

    Drunat S, Olivi M, Brunie G, Grandchamp B, Vilmer E, Bieche I et al. Quantification of TEL-AML1 transcript for minimal residual disease assessment in childhood acute lymphoblastic leukaemia. Br J Haematol 2001; 114: 281–289.

  28. 28

    Marcucci G, Caligiuri MA, Dohner H, Archer KJ, Schlenk RF, Dohner K et al. Quantification of CBFbeta/MYH11 fusion transcript by real time RT-PCR in patients with INV(16) acute myeloid leukemia. Leukemia 2001; 15: 1072–1080.

  29. 29

    Cassinat B, Zassadowski F, Balitrand N, Barbey C, Rain JD, Fenaux P et al. Quantitation of minimal residual disease in acute promyelocytic leukemia patients with t(15;17) translocation using real-time RT-PCR. Leukemia 2000; 14: 324–328.

  30. 30

    Wattjes MP, Krauter J, Nagel S, Heidenreich O, Ganser A, Heil G . Comparison of nested competitive RT-PCR and real-time RT-PCR for the detection and quantification of AML1/MTG8 fusion transcripts in t(8;21) positive acute myelogenous leukemia. Leukemia 2000; 14: 329–335.

  31. 31

    Pfitzner T, Engert A, Wittor H, Schinkothe T, Oberhauser F, Schulz H et al. A real-time PCR assay for the quantification of residual malignant cells in B cell chronic lymphatic leukemia. Leukemia 2000; 14: 754–766.

Download references

Acknowledgements

This work was partially supported by the BIOMED-2 Concerted Action (BMH4-CT98-3936). David González is supported by the ‘Instituto de Salud Carlos III’ (BISCIII) Grant 99/4230.

Author information

Rights and permissions

Reprints and Permissions

About this article

Cite this article

González, D., González, M., Alonso, M. et al. Incomplete DJH rearrangements as a novel tumor target for minimal residual disease quantitation in multiple myeloma using real-time PCR. Leukemia 17, 1051–1057 (2003) doi:10.1038/sj.leu.2402937

Download citation

Keywords

  • multiple myeloma
  • immunoglobulin heavy-chain rearrangements
  • real-time quantitative PCR
  • minimal residual disease
  • somatic hypermutation

Further reading