Leukemia Research 30 (2006) 745–750

Brief communication

The bcl-2/IgH rearrangement in a population of 204 healthyindividuals: Occurrence, age and

gender distribution, breakpoints, and detection method validity

Christina Schmitt a,1, Brigitta Balogh a,1, Alexander Grundt b,1, Christian Buchholtz a,Albrecht Leo c, Axel Benner d, Manfred Hensel a, Anthony D. Ho a, Eugen Leo a,∗

a Department of Hematology–Oncology, University of Heidelberg Medical Center, Im Neuenheimer Feld 410, 69120 Heidelberg, Germanyb Department of Medicine, University of Heidelberg Medical Center, Heidelberg, Germany

c Institute of Immunology and Blood Bank, University of Heidelberg Medical Center, Heidelberg, Germanyd Central Unit Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany

Received 1 October 2005; accepted 5 October 2005Available online 16 November 2005

Abstract

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This study assessed prevalence, frequency, age and gender distribution and breakpoint locations, and detection method validity for thecl-2/IgH rearrangement in 204 healthy individuals. For this purpose, both classic two-step, nested, semi-quantitative PCR as well as aewly established sequence-specific, hybridization probe-based real-time quantitative PCR (RQ-PCR) were employed and tested for theirensitivity and specificity for detecting t(14;18) positive cells in healthy blood donors. Interestingly, almost a quarter (24%; 39/204) of allealthy individuals carried the translocation, confirming data of one large prior report [Summers KE, Goff LK, Wilson AG, Gupta RK, ListerA, Fitzgibbon J. Frequency of the Bcl-2/IgH rearrangement in normal individuals: implications for the monitoring of disease in patientsith follicular lymphoma. J Clin Oncol 2001;19(2):420–4]. Regarding presence as well as frequency of the translocation, no correlation to

ge (mean frequency 2.0:104, with a median of <l:104, for <40 years, and mean frequency 1.9:104, with a median of <l:104 for individuals40 years) nor gender was detected. Comparing the two PCR approaches, a 95.1% concordance (194/204) regarding t(14;18) detectionas determined for nested and RQ-PCR, with nested PCR being slightly more sensitive (reproducible detection limit l:105 cells versus:104; maximum detection limit l:106 versus 1:105). Sequence analysis confirmed individual breakpoints for all samples analyzed (29/29),ndicating detection validity for both PCR approaches and ruling out contamination. The breakpoint location distribution pattern appeared toe comparable to the pattern seen with follicular lymphoma (FL) patient collectives.

In conclusion, clonal bcl-2/IgH rearrangements are indeed a very frequent observation in healthy individuals, and appear to be independentf age and gender in regard to presence and frequency. This represents a conflicting finding in context of potential biological significance,nd presents a potential disruptive factor for minimal residual disease (MRD) monitoring in FL patients. Prospective future trials will have tolarify the biological significance of this important observation.

2005 Elsevier Ltd. All rights reserved.

eywords: Healthy individuals; t(14 ;l8); Real-time PCR; Nested PCR; Follicular lymphoma

. Introduction

The translocation t(14;18) involving the bcl-2 gene is onef the most extensively examined genetic events and is the

∗ Corresponding author.E-mail address: eugen.leo@web.de (E. Leo).

1 These authors contributed equally.

cytogenetic hallmark of follicular lymphoma (FL). The clin-ical usefulness and significance of detecting the bcl-2/IgHrearrangement in peripheral blood as predictive factor for thepatient’s outcome is impaired by (a) the fact that t(14;18)positive cells can still be found in patients who experiencedmajor clinical responses [2,3] and, even more disturbing (b),that the same aberration can be detected in healthy individ-uals [4,5]. The biological significance of this latter finding

145-2126/$ – see front matter © 2005 Elsevier Ltd. All rights reserved.oi:10.1016/j.leukres.2005.10.001

746 C. Schmitt et al. / Leukemia Research 30 (2006) 745–750

remains unresolved. Furthermore, as of today, there are quiteconflicting results concerning prevalence and frequency ofthis translocation in healthy populations, with most studieshaving examined comparatively small numbers of individu-als (<50), and the influence of age and gender on the presenceand frequency has not been fully elucidated. Depending onthe PCR technique applied, t(14;18) presence was stated for8–88% of healthy blood donors [6,7]. In this study, we reportthe results of a t(14;18) analysis of peripheral blood samplesof 204 healthy blood donors by two independent PCR tech-niques, analyzing also impact of age and gender apart fromrelative and absolute frequency of the bcl-2/IgH rearrange-ment in this healthy population.

2. Materials and methods

2.1. Cell line, blood samples and DNA samplepreparation

The human B-cell lymphoma line Karpas-422 wasused for preparing standard curves as described previously(Schmitt et al., submitted for publication). Total cellular DNAof 204 peripheral blood samples from healthy individuals andDNA of the cell line were extracted using the QIAamp DNABlood Maxi Kit (Qiagen, Hilden, Germany). All individualsitiD

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was 1:104, equivalent to 10 t(14;18)-positive cells per reac-tion.

2.3. Sequence analysis of bcl-2/IgH rearrangements

Electrophoretic separated PCR products of 29 blooddonors were isolated with an agarose gel extraction kit(NucleoSpin Extract, Machery-Nagel GmbH, Duren, Ger-many). For sequencing we used the nested PCR inner primersand Big Dye Terminator Kits (Applied Biosystems, FosterCity, USA).

2.4. Statistical analysis

To measure agreement between two independentobservers Spearman’s rho was used for continuous data.Cohen’s kappa coefficient (Cohen, 1960) was used for cate-gorical data. A value of 0 for kappa indicates no agreementbeyond chance and a value of 1 indicates perfect agreement.Kappa values below 0.4 were considered as poor agreement,values between 0.4 and 0.75 as fair to good agreement andvalues above 0.75 as excellent agreement. The statistical anal-ysis of PCR data uses frequencies of PCR positivity.

McNemar’s test was used to compare nested PCR and real-time PCR results for bcl-2/JH rearrangement detection on thesgvasittt

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nvestigated gave written informed consent before enteringhe study. The study was conducted according to good clin-cal and laboratory practice rules and the principles of theeclaration of Helsinki.

.2. PCR

For both PCR approaches, primers were localized atpposite ends of the breakpoint fusion region. RQ-PCRnalysis was carried out with two juxtaposed sequence-pecific hybridization probes, one 3′-labelled with fluores-ein, serving as donor fluorochrome, and one 5′-labelled withCRed640, serving as acceptor fluorochrome. The majorreakpoint region (MBR) of the t(14;18) translocation wasmplified by a two-step nested PCR with 500 ng/reactionNA as described previously (Schmitt et al., submitted forublication). PCR was carried out in duplicates by three inde-endent observers. Using standards with known numbers of(14;18) copies, nested PCR showed a reproducible detec-ion limit of one t(14;18) copy in 105 cells (1:105), and a

aximal detection limit of l:106. RQ-PCR analysis was per-ormed in duplicates by two independent observers usinghe Lightcycler® instrument (Roche Diagnostics GmbH,

annheim, Germany) with 300 ng/reaction DNA. Amplifi-ation was carried out for the MBR bcl-2/IgH rearrangement,ogether with the bcl-2 gene as endogenous reference asescribed previously (Schmitt et al., submitted for publica-ion). RQ-PCR had a detection limit of one t(14;18) positiveell in 105 cells, representing the maximal sensitivity of thessay. However, the reproducible sensitivity of real-time PCR

ame samples. The dependency of PCR positivity on age andender were tested by logistic regression. Confidence inter-als for proportions were given by Wilson’s method (Agrestind Coull, 1998). An effect was considered to be statisticallyignificant if the corresponding p-value was 0.05 or less. Forllustration purposes the age distribution was split accordingo the median age of 39 as “age <40” versus “age ≥40” inables shown. The statistical analyses were performed usinghe statistical software package R, version 2.1.1.

. Results

A total of 204 peripheral blood samples of healthy indi-iduals were investigated. Median age was 39 years (range0–67 years), 95 were female (47%), and 109 male (53%). Byested PCR, a total of 49 of 204 (24%) of healthy individ-als were assessed as t(14;18) positive. Neither prevalenceor frequency of the t(14;18) translocation (Table 1) differedignificantly by gender or age when employing this semi-uantitative method. Employing a newly established RQ-CR, a total of 39 of 204 (19%) were identified as t(14;18)ositive. This lower level of detection reflects well the knownower sensitivity of RQ-PCR as compared to nested PCR,specially when dealing with a low-copy population (see Sec-ion 2). Employing this quantitative PCR method also neitherrevalence nor frequency differed significantly regarding ager gender: Comparing age groups ≥ and <40 years, preva-ence (22.3% of individuals <40 years and 15.8% of indi-iduals ≥40 years were positive) and frequency differences

C. Schmitt et al. / Leukemia Research 30 (2006) 745–750 747

Table 1Prevalence of t(14;18) positivity by two different PCR methods

Overall <40 years ≥40 years

Nested PCRTotal 49 (24.0%) 27 (26.2%) 22 (21.8%)Female 20 (21.0%) 12 (23.1%) 8 (18.6%)Male 29 (26.6%) 15 (29.4%) 14 (24.1%)

RQ-PCRTotal 39 (19.1%) 23 (22.3%) 16 (15.8%)Female 16 (16.8%) 10 (19.2%) 6 (14%)Male 23 (21.1%) 13 (25.5%) 10 (17.2%)

Overall and by gender and age (</≥40 years) in a population of 204 healthyblood donors (103 (50.5%) <40 years; 101 (49.5%) ≥40 years; 109 (53%)male; 95 (47%) female).

for t(14;18) (ranging from <1:104 to 5.5:103 cells in individ-uals <40 years of age (mean 2.0:104, median <l:104), andfrom<l:104 to 5.5:103 cells in individuals ≥40 years (mean1.9:104cells, median <l:104) remained non-significant.

For the RQ-PCR method a good correlation existedbetween different investigators (Spearman’s rho = 0.86, twoindependent observers), and for nested PCR a good to excel-lent agreement between three observers (Cohen’s kappa coef-ficient = 0.64/0.67/0.78, respectively, for observers 1 versus2, 1 versus 3, and 2 versus 3, respectively).

Overall, a 95.1% concordance (194/204; 95% confidenceinterval 91.2–97.3%) was determined for nested and RQ-PCR (Fig. 1). A significant difference in the probabilitiesof discordant results from the two methods was observed(P = 0.004, McNemar’s test; Table 2). Both nested and RQ-PCR detected no translocations in a total of 155 cases. 10additional samples were t(14;18) positive in nested PCR andnegative in RQ-PCR. Of these samples, 9 were scored as1+ (1:105–106) in nested PCR revealing inconsistent resultsof RQ-PCR at very low t(14;18) frequencies as shown for

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Table 2Comparison of nested PCR with a newly established RQ-PCR for the detec-tion of t(14;18) positive cells in peripheral blood samples of healthy blooddonors

Real-time PCR Total

+ −Nested PCR

+ 39 10 49− 0 155 155

39 165 204

Total concordance: 95.1% (234/246; 95% confidence interval 91.2–97.3%),but significant difference in the number of discordant pairs (P = 0.004,McNemar test).

the t(14;18) standard curve as well as noted in previousstudies.

About 29 samples of 29 t(14;18) positive healthy blooddonors were accessible for sequencing, allowing to identifypotential differences in breakpoints and N-insertions, helpingto exclude (potential) contaminations, and making compar-ison to FL patient collective data possible. In 29 samplesanalysed, 29 different breakpoint locations were detected(Table 3). This assured that no false positive samples werepresent, resulting in a specificity of 100% for both meth-ods. Rearrangements contained N-insertions in more than twothirds of cases (19/29).

4. Discussion

The value of detecting t(14;l8) positive cells in the periph-eral blood of FL patients is obvious: Early recurrence aswell as presence of minimal residual disease (MRD) can bemonitored for. Various publications have shown the valueof this method for these purposes. Yet, finding the same bcl-2/IgH rearrangements in healthy individuals raises numerousquestions and concerns. Apart from the potential biologicalsignificance associated with this finding, the pure presenceof this translocation in healthy individuals may hamper anyMgv

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ig. 1. Correlation between nested and RQ-PCR. Results from RQ-PCRx-axis) are depicted against results from nested PCR (y-axis). n = 204. Spear-an’s rho is estimated as 0.90.

RD monitoring in patients and raise questions towards theenuine significance of PCR positivity—be it in healthy indi-iduals or successfully treated patients.

Prior reports state presence of t(14;18) positive cells in–88% of healthy blood donors [6,7]. This wide range raisesuestions regarding the significance and potentially also qual-ty of such data. The largest study published so far examined81 healthy individuals by real-time PCR and reported 23%f probands to be positive for t(14;18) [1]. Yet, not all posi-ive samples were subjected to sequencing in this study andhe level of reliable sensitivity was exceeded in over 60% ofositive samples.

Therefore, to assess the frequency of the bcl-2/IgH rear-angement in healthy individuals 204 persons of both gendersnd a wide age range were examined for prevalence and fre-uency of t(14;18). Both a sequence-specific, hybridizationrobe-based RQ-PCR, representing the current standard for

748 C. Schmitt et al. / Leukemia Research 30 (2006) 745–750

Table 3Sequence analysis of t(14;18) translocation from healthy blood donors

Sample bcl-2 MBR breakpoint de novo sequence JH breakpoint Fragment size [bp]

K442 3115 AGGACC 1488-JH4 16521 3161 C 1488-JH4 20622 3095 ACAGTCAGNGGTGCTTACAGAC 1488-JH4 16128 3138 AAGCCAGACCTCACCGATCATCCNNAGG 1487-JH4 21129 3114 1488-JH4 15830 3162 322- JH1/1513-JH 4/1914-JH5 18131 3162 1919-JH5 17639 3044 2505-JH6 8850 3159 324-JH1/1515-JH 4/1916-JH5 17666 3160 ACTGCNNTAACGN 2488-JH6 23470 3155 324-JH1/1515-JH 4/1916-JH5 17296 3159 ACCCGGGGA 1883-JH5 218107 3115 322-JH1/1513-JH 4/1914-JH5 134109 3163 GGGA 1883-JH5 217117 3158 1513-JH4/1914-JH5 177120 3112 TTCGCCCCCCTAGGTTTATGGGGGGG 1882-JH5 189121 3161 TTTCTTTCCGG 2483-JH6 238126 3115 ATGACCNACNCCTGTGGCNNCCAG-

AANNCNNTNCACACCNTCTACAGA1488-JH4 208

134 3164 ATCGTGGATGAGAGGATGAAGGCAAGA 1880-JH5 244144 3115 GAGG 2492- JH6 176153 3162 TTAGAAATCGACGTGGCGTCGGGGG 1484-JH4 235158 3115 CCC 1492- JH4 158164 3096 AACCCNGACCCA 1515-JH4/1916-JH5 125165 3117 GCT 1886-JH 5 167186 3101 1490-JH4 142187 3110 523-JH2 136192 3146 ATTAGGGGGG 1495-JH4/1896-JH5 193193 3088 GGG 1880-JH5 143195 3111 CCCTGGTACOCCGAA 2484-JH6 191198 3115 AGGA 1888-JH-5 164

Shown are nucleotide sequences of the t(14;18) breakpoint junctions. Positions of breakpoints were determined in relation to bcl-2 sequence accession numberM14745 and IgH sequence accession number X86359. N indicates nucleotide not readable. Sample no. 21 to 121 <40 years, sample no. 126 to 198 ≥ 40 years.

monitoring for the bcl-2/IgH rearrangement in patients withFL as well as a classic, two-step nested PCR were employedfor this purpose. The latter PCR technique is known to pos-sess the highest reproducible sensitivity (according to themajority of publications comparing PCR methods for MRDmonitoring) and therefore provided the most accurate resultson prevalence, whereas the real-time approach allowed quan-tification. Biagi and Seymour [5] revealed overall rates fort(14;18) in peripheral blood of 28.7% by screening publica-tions using conventional (semi)nested PCR methods in mostcases that, in general, have been shown to have a higher sen-sitivity than RQ-PCR [4]. This is confirmed by our study.One reason for this could be that the RQ-PCR approachrequires a minimum of 10 t(14;18) copies per reaction fora reproducible detection, thereby increasing the risk of false-negative results. The prevalence detected in this study is tosome degree lower than has been reported in several otherstudies [6,8]. Yet, all these studies investigated a significantlysmaller population as compared to our report. Two studiestested comparable numbers of individuals: (1) Summers et al.[1] found a prevalence of 23% in 481 individuals (real-timePCR, not all positives sequenced) and (2) Dolken et al. [9]tested 131 healthy persons for the presence of t(14;18) stating55% positivity (real-time PCR). This may be explained by the

exclusive examination of males that seem to show a higherprevalence for the t(14;18) translocation in some studies [10](but not ours). Furthermore, choice of tissue, differences insample processing, multiple PCR techniques with the useof different primer sequences and variable amounts of DNAmay contribute to these differences. E.g., it has been shownthat the detection of t(14;18) positive healthy individuals isstrongly correlated to use of peripheral blood mononuclearcells (PBMNC) or B-lymphocytes versus whole blood [4].In comparison to several other reports, a relatively moder-ate initial template DNA amount was used in our study forboth assays (300 and 500 ng/reaction for RQ and nested PCR,respectively), whereas other groups employ up to 10 �g DNA[11], thereby increasing the sensitivity by testing plenty ofreplicates of a sample. Yet, this increases in parallel techni-cal complexity and error probability.

Furthermore, PCR analysis of identical samples in differ-ent laboratories was revealed to differ up to two logs [12],representing another factor influencing results significantly.Despite these numerous factors having an impact upon preva-lence and frequency our results are very similar to data thatwere generated with comparable methods/techniques, con-firming their robustness. Both studies [1,3] employed theconvenient and widely used whole blood DNA extraction

C. Schmitt et al. / Leukemia Research 30 (2006) 745–750 749

method and had established similar detection limits for theirPCR method, resulting in prevalences of t(14;18) in healthyindividuals of 23% and 15%, respectively, with the first studyrepresenting in parallel the single largest study done so far(n = 481).

FL is a non-Hodgkin’s lymphoma whose incidence riseswith age. The t(14;18) translocation is widely seen to bean early signal in a multi-step process leading to malig-nant B-cell transformation, also explaining for a potentiallong-lasting period between the occurrence of the t(14;18)translocation and the onset of FL. The risk of FL dependenton the occurrence of the t(14;18) translocation is supported bythe notion that differences in t(14;18) prevalence may countfor varying incidences of FL [11]. Several studies showed anincreasing incidence of t(14;18) translocations with age sug-gesting a correlation of occurrence of t(14;l 8) and the risk ofFL [10]. Other studies did not support such a concept, show-ing no age-dependent increase in t(14;18) incidence [1]. Ourdata are in concordance with the latter, raising the questionwhether additional genetic alterations required to develop FLmay be age-dependent, resulting in the higher frequency ofFL in older patients.

A few groups demonstrated in addition an age-dependentincrease in the frequency of t(14;18) positive cells [8,10]. Yet,no association with age has been shown by the majority ofother studies [1,6,7], being in harmony with our data.

tcapToitdoscaunmsromsBlTtFifi

ing (a) a potential disruptive factor for MRD monitoring inFL patients and foremost (b) staying a conflicting findingin context of potential biological significance, as of todayno link to presence of this translocation in a healthy indi-vidual and later development of FL could be established.Prospective, large, longitudinal trials in healthy individualsin the future will have to clarify the true biological signifi-cance of this observation, carefully examining for additionalgenetic events occurring in such individuals, and ultimatelyevaluating the possibility of a link between the presence oftranslocation in a healthy individual and development of FLover time.

Acknowledgements

This work was supported in part by a grant of the MedicalFaculty of the University of Heidelberg.

Contributions. Christina Schmitt contributed to exper-imental concept, data generation and evaluation, andmanuscript preparation. Brigitta Balogh contributed to datageneration and evaluation. Alexander Grundt contributed todata generation and evaluation, and RQ-PCR development.Christian Buchholtz contributed to data generation and eval-uation. Albrecht Leo contributed to sample acquisition anddHArg

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No significant differences in prevalence of the t(14;18)ranslocation according to gender could be observed, too,onfirming the majority of previous reports [6,13]. However,gain a few groups [10] state higher frequencies of t(14;18)ositive cells in male individuals as well as FL patients.he reason for this potential discrepancy is unknown, butther genetic alteration/cancer risk factors, such as smok-ng habits, could be involved. The higher frequency found inhese reports for males supports the fact that the male gen-er represents an adverse prognostic factor with a higher riskf relapse as compared to females, but this remains highlypeculative as, again, the majority of reports declines such aorrelation. In conclusion, clonal bcl-2/IgH rearrangementsre indeed a frequently observed finding in healthy individ-als. According to our data, prevalence and frequency doot appear to increase with age, being in harmony with theajority of published data. Due to its higher reproducible

ensitivity, nested PCR for the quantification of bcl-2/IgHearrangements represents a reliable method in the detectionf low levels of t(14;18) carrying cells, whereas RQ-PCRay be advantageous when precise quantification is neces-

ary, e.g., rather in the monitoring of MRD for FL patients.reakpoint region patterns similar to those of FL patient col-

ectives were seen in the examined healthy blood donors.aken together, these findings support the concept that the

(14;18) translocation is not an isolated genetic event causingL but represents rather one (though hallmark-level) event

n a multi-step process resulting in malignant B-cell trans-ormation. Yet, the presence of the translocation in healthyndividuals itself remains an enigmatic finding, represent-

ata review. Axel Benner contributed to Statistics. Manfredensel contributed to sample acquisition and data review.nthony D. Ho contributed to experimental concept, and data

eview. Eugen Leo contributed to experimental concept, dataeneration and evaluation, and manuscript preparation.

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