Literature DB >> 19480690

Automated detection of residual cells after sex-mismatched stem-cell transplantation - evidence for presence of disease-marker negative residual cells.

Jörn Erlecke1, Isabell Hartmann, Martin Hoffmann, Torsten Kroll, Heike Starke, Anita Heller, Alexander Gloria, Herbert G Sayer, Tilman Johannes, Uwe Claussen, Thomas Liehr, Ivan F Loncarevic.   

Abstract

<pan class="Gene">span class="abstract_title">BACKGROUND:pan> A new chimerism analysis based on automated interphase fluorescence in situ hybridization (FISH) evaluation was established to detect residual cells after allogene sex-mismatched <spapan>n class="Disease">bone marrow or blood stem-cell transplantation.Cells of 58 <span class="Species">patients were characterized as disease-associated due to presence of a bcr/abl-gene-fusion or a trisomy 8 and/or a simultaneous hybridization of gonosome-specific centromeric probes. The automatic slide scanning platform Metafer with its module MetaCyte was used to analyse 3,000 cells per sample.
RESULTS: Overall 454 assays of 58 patients were analyzed. 13 of 58 patients showed residual recipient cells at one stage of more than 4% and 12 of 58 showed residual recipient cells less than 4%, respectively. As to be expected, patients of the latter group were associated with a higher survival rate (48 vs. 34 month). In only two of seven patients with disease-marker positive residual cells between 0.1-1.3% a relapse was observed. Besides, disease-marker negative residual cells were found in two patients without relapse at a rate of 2.8% and 3.3%, respectively.
CONCLUSION: The definite origin and meaning of disease-marker negative residual cells is still unclear. Overall, with the presented automatic chimerism analysis of interphase FISH slides, a sensitive method for detection of disease-marker positive residual cells is on hand.

Entities:  

Year:  2009        PMID: 19480690      PMCID: PMC2696465          DOI: 10.1186/1755-8166-2-12

Source DB:  PubMed          Journal:  Mol Cytogenet        ISSN: 1755-8166            Impact factor:   2.009


Background

<pan class="Gene">span class="Disease">Malignant hematological diseasespan> represent 5.5% of all <spapan>n class="Disease">cancers in Germany [1]. One way to cure these fatal diseases is allogenic <span class="Disease">bone marrow or blood stem cell transplantation. In case of a male donor and female recipient (and vice versa) we talk of a sex-mismatched transplantation. In such a setting it is relatively simple to classifiy donor and acceptor cells in the bone marrow or blood cell system. The existence of 100 percent donor cells is called complete chimerism, in contrast a mixture of both donor and acceptor cells mixed chimerism. Chimerism analysis is done on these sex-mismatched transplants to monitor minimal residual disease and to plan further immunotherapy like donor lymphocyte infusion (DLI) [2]. In routine diagnostics, fluorescence in situ hybridization (FISH) is frequently applied for chimerism analysis [3-6], which demands manual time-consuming counting of cells. An experienced technician needs about 2.5 hours for approximately 3,000 cells. Therefore, an automatic FISH chimerism analysis is extremely valuable for diagnostics and correct treatment of affected patients, as it can be carried out in a fraction of time. Thus, the presented single cell based approach becomes now competitive in comparison to PCR based chimerism analysis [7]. Frequently observed disease-markers are the <n class="Gene">span class="Gene">bcr/abl-fusion-gene as present in more than 95% of <span class="Disease">chronic myeloid leukemia (CML) cases [8,9], and trisomy 8 found in 11% of acute myeloid leukemia (AML) [10]. The simultaneous detection of the gonosomal constitution and a tumor marker enables the identification of residual tumor cells. The latter was already proposed 1994 by Nagler and coworkers [11], however, it was not often carried out before [12-14], and not studied under routine conditions. Here we tested an automated interphase FISH analysis for the characterization of chimerism in 58 patients after allogenic stem cell transplantation with different hematological malignancies.

Results

Determination of cut off levels

FISH-analysis of residual cells after sex-mismatched transplantation is mainly based on simultaneous labeling of the centromeres of the X- and Y-chromosomes. Because of possible false positive and false negative results e.g. due to background or hybridization problems, it was necessary to determine the cut off level. Therefore, a total of 26,633 cells from 10 healthy female and 35,783 cells from 11 healthy male were analyzed with the described automated system. The automated analysis showed in the female controls 257 cells with apparent male signal constellation (XY), and the male controls had 142 cells with apparent female signal constellation (XX). To control these automated results we investigated all questionpan class="Gene">able cells; only 38 out of 257 and 27 out of 142 could be confirmed to be real XY-positive cells or in the male case XX-positive cells. This corresponds to a false positive rate of 0.14% in female and 0.08% in male. An additional random control of 4,841 XX cells in female and of 4,535 XY cells in male showed that there was no further failure of automatic counting. As the cut off level depends on the amount of analyzed cells, all mentioned female and male cells were listed in spreadsheets with random order and arranged in blocks of 50, 100, 200, 400, 800, 1,500, 2,000, 2,500, 3,000 and 4,000 cells. Subsequently, the mean and standard deviation was assessed for each block. The cut off level was defined as the mean plus twice the standard deviation. The respective cut of levels for each block size were fitted by a trend line enpan class="Gene">abling the calculation of cut off levels for arbitrary cell numbers up to 4000. Fig. 1 shows the determined/calculated cut off values for female and male cells including trend lines.
Figure 1

Cut off level in dependence of the number of evaluated cells (n) in female (gray line, diamonds) and male (black line, triangles).

Cut off level in dependence of the number of evaluated cells (n) in female (gray line, diamonds) and male (black line, triangles). In order to determine the false positive rate for trisomy 8 another 15,882 cells from 5 healthy <pan class="Gene">span class="Species">peoplepan> were analyzed with centromere 8 probes. The mean false positive rate was 1.2%. In the same manner 11,453 cells of 11 healthy controls were investigated using the LSI-probe against the <spapan>n class="Gene">bcr/abl-fusion gene. The mean false positive rate for the <span class="Gene">bcr/abl-probe was 0.7%. For estimating the cut off level for XX/XY in combination with trisomy 8 (XX or XY+trisomy 8) or bcr/abl (XX or XY+bcr/abl) the 95-quantil with the following formula was used: Thus, the cut off level was as follows: • for XX+trisomy 8 and XX+<n class="Gene">span class="Gene">bcr/abl = 0.005% • for XY+trisomy 8 and XY+<n class="Gene">span class="Gene">bcr/abl = 0.003%.

Minimum number of cells to be analyzed in a blood sample

Two statistical aspects of the present study were further assessed. First, the minimum number of cells to be analyzed was determined in order to achieve a predefined accuracy for the estimated fraction of acceptor cells in the total blood of the <pan class="Gene">span class="Species">patientpan>. Given the total blood of a transplanted <pan class="Gene">span class="Species">patientpan> consists of N cells of which NA are acceptor cells, the fraction of acceptor cells in the <spapan>n class="Species">patient is PA = NA/N. A blood sample contains fewer than N cells and the fraction of acceptor cells in the sample pA can only be an estimate for the true fraction PA. But how many cells must be analyzed in a blood sample in order to achieve a predefined accuracy? The probability of finding MA acceptor cells in a blood sample of size M drawn from a total of N blood cells of which NA are acceptor cells is given by a hypergeometric distribution. However, the sample size M is generally much smaller than the total number of cells N. Thus, the true fraction of acceptor cells PA can be assumed to be the same before and after the blood sample has been drawn from the <span class="Species">patient. The hypergeometric distribution is then well approximated by the binomial distribution . In the present case the exact value of PA = NA/N is unknown but is to be estimated by the sample ratio pA = MA/M. The mean and standard deviation of the random variable pA are given by , respectively. For determining the minimal number of cells to be analyzed in a blood sample we use the order of magnitude estimate PA = 0.01 according to the measurements. The coefficient of variation (equivalent to the relative standard deviation given in %) is then given by the ratio of standard deviation and mean . For the relative standard deviation to be smaller than q the sample size must exceed M* = 99/q2. Hence, for q = {100%, 50%, 25%} the required sample sizes must be larger then M* = {99, 396, 1584}, respectively.

Error bounds for the fraction of acceptor cells due to classification errors of the automated cell recognition device

Second statistical aspect, the error bounds for the fraction of acceptor cells in the blood sample were calculated with respect to classification errors introduced by the automated cell recognition device. The measured number of acceptor cells may not reflect the real number of acceptor cells in the sample due to measurement errors of the automated device. In order to assess the error rate of the device we classified 10 and 11 samples from healthy females and males, respectively, and obtained histograms for the fraction of misclassified cells. These were similar for females and males and thus pooled in a single distribution as shown in Fig. 2. Using this error distribution we calculated the probability density function for the true number of acceptor cells in the sample as described in the following paragraph. The resulting probability density function indicates that the measurements rather overestimate the number of true acceptor states.
Figure 2

Histogram for the misclassification error as estimated from the number of wrongly classified cells per sample. Blood samples were obtained from 10 healthy females and 11 healthy males. The histogram is fitted by a sum of two beta distributions.

Histogram for the misclassification error as estimated from the number of wrongly classified cells per sample. Blood samples were obtained from 10 healthy females and 11 healthy males. The histogram is fitted by a sum of two beta distributions.

Probability density function for the true number of acceptor cells in the sample

In order to assess the error introduced by the measuring device we calculated the probability distribution for the true number of acceptor cells MA in the sample given the number of measured acceptor cells M*A. First note that for a given misclassification probability b the number of correctly measured acceptor cells M*AA is binomial distributed with total number of cells MA and probability 1-b. Accordingly, the number of <pan class="Gene">span class="Species">donorpan> cells erroneously measured as acceptor cells M*AD is binomial distributed with total number of cells MD and probability b. As shown in Fig. 2 the misclassification probability b itself is β-distributed. Thus, b-averaged binomial probability distributions are obtained by integration according to the β-distribution, i.e. The probability of measuring M*A acceptor cells conditional on the fact that MA true acceptor cells are present in the sample is given by the sum of probabilities consistent with the conditions M*A = M*AA + M*AD and M = MA + MD. It reads in which the product is implied by the fact that the events 'M*AA out of MA' and 'M*AD (= M*A - M*AA) out of MD (= M - MA)' are independent and must occur at the same time. The probability for the true number of acceptor cells MA in the sample conditional on M*A acceptor cells having been measured is given according to Bayes' theorem From the pooled experimental data the a priory probability for the number of measured acceptor cells was estimated to be a sum of two exponentials. In the present medical context the prior for the number of acceptor cells in the sample f(M) is best chosen to be uninformative (i.e. constant) in order not to bias the results towards low MA values, which would conflict with the interest of the <pan class="Gene">span class="Species">patientpan>. Another choice would be to equate . Since is strongly peaked for zero measured acceptor cells the resulting is biased towards low MA-values, especially for small sample sizes M. This choice could be more interesting for e.g. insurance companies. Sample plots of the conditional probability distribution are shown in Fig. 3 for the empirical prior. From these plots it becomes clear that the number of acceptor cells is rather overestimated by the measurements since the great majority of cells are <pan class="Gene">span class="Species">donorpan> cells that are occasionally classified as acceptor cells. The opposite case, i.e. acceptor cells being classified as <spapan>n class="Species">donor cells, is very rare simply because there are only very few acceptor cells.
Figure 3

Sample plots for the conditional probability distribution . The prior is uninformative. The different curves correspond to different measured values M*A as indicated in the legends. These values correspond to 0%, 1%, 2% and 3% of the corresponding sample size. The distributions are biased to lower values of MA (see text).

Sample plots for the conditional probability distribution . The prior is uninformative. The different curves correspond to different measured values M*A as indicated in the legends. These values correspond to 0%, 1%, 2% and 3% of the corresponding sample size. The distributions are biased to lower values of MA (see text).

Quantification and characterization of residual cells in patients after sex-mismatched transplantation

Overall 454 samples of 58 <pan class="Gene">span class="Species">patientspan> were investigated with X- and Y-chromosome specific probes as described in detail in Tab. 1. 33 <spapan>n class="Species">patients had a complete chimerism (posttransplant 290 samples) and therefore no residual <span class="Disease">cancer cells. 25 had a mixed chimerism (47 of 163 posttransplant samples). In order to see the clinical relevance of residual cells, patients with mixed chimerism were divided in two groups, one with less than 4% sexmismatch to the donor (13 patients) and the other with more than or equal 4% sexmismatch (12 patients). Both groups show no correlation with the time since transplantation. Patients with < 4% residual cells were transplanted between 10–55 years (median = 46), patients with ≥ 4% residual cells between 0–66 years (median = 49). <pan class="Gene">span class="Species">Patientpan> characteristics m = male, f = female, SAM = severe <pan class="Gene">span class="Disease">aplastic anemiapan>, ALL = <spapan>n class="Disease">acute lymphatic leukemia, AML = <span class="Disease">acute myloid leukemia, CLL = chronic lymphatic leukemia, CML = chronic myeloid leukemia, Lym = lymphoma, MDS = myelodysplastic syndrome, MM = multiple myeloma, NHL = Non-Hodgkin lymphoma, OP = osteopetrosis, n.k. = not known, C = classical, M = metakin, BMT = bone marrow transplantation, PBSCT = peripheral blood stem-cell transplantation. <pan class="Gene">span class="Species">Patientspan> after dose reduced conditioning treatment prior to transplantation (RC) showed a tendency to develop ≥ 4% residual cells whereas in myeloablative repertoire regimes (MRR) <spapan>n class="Species">patients trend to develop < 4% residual cells. In detail 54% of <span class="Species">patients with ≥ 4% residual cells underwent MRR and 38% RC conditioning. In contrast, 25% of patients with ≥ 4% residual cells underwent MRR and 67% RC conditioning. The survival rate of all three groups (complete chimerism, < 4% residual cells and ≥ 4%) is shown as a Kaplan-Meier-plot in Fig. 4. For a detailed compilation of causes of death see in Table 1.
Figure 4

Survival rates of 33 patients without residual cells (line a), 13 patients with residual cells < 4% (line b) and 12 patients with residual cells > 4% (line c).

Table 1

Patient characteristics

patientsexprimaryTxconditioningPBSCT/deathreasoncytogeneticnumber analysed
no.diseaseageBMTdeath/daymarkerprobes
1mSAA10n.k.PBSCTyesn.k./+1681
2fAML62MPBSCTno6
3fCML51CPBSCTyesGvHD/+575bcr/abl2
4mMDS37MPBSCTno5
5fAML44MPBSCTno3

6fALL43CBMTno5
7fNHL39MPBSCTno19
8fCML25CPBSCTno21
9fAML49CPBSCTno3
10fMM57CPBSCTno7

11fCML12n.k.PBSCTyesn.k./+1103
12fCML43n.k.PBSCTno1
13mOP0n.k.BMTno4
14fAML41MPBSCTnotrisomy 817
15mSAA49MPBSCTno18

16fAML55MPBSCTyesinfection/+4583
17mMM40MBMTyesrelapse/+2788
18fAML48MPBSCTyesrelapse/+1253
19mMM60MPBSCTyesinfection/+822
20fAML25MPBSCTno15

21mALL34CPBSCTyesGvHD/+1171
22mCML39CPBSCTnobcr/abl3
23fMDS52MPBSCTno15
24fCML1n.k.BMTno3
25fALL14CPBSCTyesn.k./+3612

26mAML89MPBSCTno4
27fAML49CPBSCTno14
28fAML48MPBSCTyesinfection/+1442
29mCML49CPBSCTyesGvHD/+833bcr/abl16
30mAML58MPBSCTno8

31fCML46CPBSCTnobcr/abl14
32mALL42MPBSCTno11
33mCML46CPBSCTno6
34mCML51MPBSCTnobcr/abl3
35mAML48MPBSCTyesrelapse/+321trisomy 87

36mCML43MPBSCTnobcr/abl22
37fCML38CPBSCTnobcr/abl14
38fAML34CPBSCTno21
39fAML53MPBSCTno12
40fAML59MPBSCTno24

41mCML50MPBSCTyesrelapse/+62bcr/abl3
42fAML58MPBSCTno7
43mAML27CPBSCTyesrelapse/+4367
44mCML52MPBSCTnobcr/abl9
45fCML44CPBSCTnobcr/abl9

46mAML46CPBSCTno6
47mAML40CPBSCTyesrelapse/+4847
48mAML50MPBSCTnotrisomy 817
49fAML50MPBSCTno9
50fAML61MPBSCTyesrelapse/+2865

51mALL66MPBSCTyesrelapse/+7013
52mCLL58MPBSCTyesinfection/+5994
53mMM49MPBSCTno5
54mLym45CPBSCTyesrelapse/+4023
55mSAA35CPBSCTno3

56mCML37CPBSCTno2
57fAML20CPBSCTno3
58fALL26CPBSCTno4

m = male, f = female, SAM = severe aplastic anemia, ALL = acute lymphatic leukemia, AML = acute myloid leukemia, CLL = chronic lymphatic leukemia, CML = chronic myeloid leukemia, Lym = lymphoma, MDS = myelodysplastic syndrome, MM = multiple myeloma, NHL = Non-Hodgkin lymphoma, OP = osteopetrosis, n.k. = not known, C = classical, M = metakin, BMT = bone marrow transplantation, PBSCT = peripheral blood stem-cell transplantation.

Survival rates of 33 <pan class="Gene">span class="Species">patientspan> without residual cells (line a), 13 <spapan>n class="Species">patients with residual cells < 4% (line b) and 12 <span class="Species">patients with residual cells > 4% (line c). In 12 <pan class="Gene">span class="Species">patientspan> cytogenetic disease-markers were detected before transplantation (<spapan>n class="Gene">bcr/abl-fusion (n = 9); trisomy 8 (n = 3)). For these cases a simultaneous hybridization of the centromeres X and Y together with the <span class="Gene">bcr/abl- or centromere 8-probe was performed. As shown above it is possible to decrease the cut off level for acceptor cells by targeting gonosomes and tumour specific genome alterations in a single hybridization. 55 samples of twelve patients were investigated. In nine of these samples residual cells were found in a range of 0.1–3.3%. In two of those nine patients (cases 3, 14) the detected sexmismatch cells were not disease-marker positive, whereas in the other seven patients (cases 29, 31, 35, 36, 37, 41, 45) disease-marker positive residual cells were detected (in total 25 cells). Two specimen of disease-marker negative and disease-marker positive residual cells are shown in Fig. 5.
Figure 5

Bcr/abl negative cell (left) and bcr/abl positive cell (right). The right cell shows the bcr/abl-gene-fusion (arrowhead). The LSI ES bcr/abl probe of Vysis/Abbott was applied here.

<n class="Gene">span class="Gene">Bcr/abl negative cell (left) and <span class="Gene">bcr/abl positive cell (right). The right cell shows the bcr/abl-gene-fusion (arrowhead). The LSI ES bcr/abl probe of Vysis/Abbott was applied here. In these remaining groups with small numbers of <pan class="Gene">span class="Species">patientspan> the disease-marker gave no additional information. The amount of disease-marker-positive or negative residual cells showed no correlation with clinical outcome like relapse or <spapan>n class="Disease">death. Table 2 shows the course of 9 <span class="Species">patients with residual cells with known disease-marker.
Table 2

Nine patients with disease-marker positive and disease-marker negative residual cells

patientmonth
no.1234567891011
4U3,0%(2,8%/0%)
15U1,7%U1,7%U1,7%U1,7%U1,7%U2,3%
30U2,1%3,5%(1,5%/90%)U0,9%U0,9%
32U2,4%U1,7%(0,2%/100%)U2,1%U2,6%U2,2%U2,2%U2,1%U2,2%
37(0,2%/100%)U1,2%U1,3%U1,4%2,5%39%U1,1%+
38(0,4%/25%)U0,9%U0,9%U1,2%U1,1%U0,9%U0,9%U1,2%U0,9%
39U2,7%(0,1%/100%)U1,7%(0,2%/50%)U2,6%
43(0,8%/100%)(6%/0%)64%+
48U1,7%U1,7%(0,3%/100%)U1,7%U1,7%U1,7%U2,4%

patientmonth
no.1213141516171819202122

4+
15(3,3%/0%)U2,2%U1,7%U1,7%U1,7%U1,7%U1,7%U1,7%
30U1,5%U1,5%U1,5%U1,5%U1,4%U1,5%U1,3%
32U1,7%U2,2%U2,2%U2,2%
37
38U1,3%U0,9%U1,3%U1,2%U1,2%U1,3%U1,2%
39U2,6%U2,5%U2,4%U2,5%
43
48U1,7%U2,2%

patient
no.2324*/25262829*/3032333538*/3948

4
15U2,2%*U2,2%*U2,2%
30U1,3%U0,9%U0,9%U1,3%+
32U0,9%*
37
38U1,1%U1,1%U1,1%U1,1%U1,3%U1,2%*
39U2,5%U2,3%U1,7%U2,2%
43
48

UX% = under cut off level of X%, in brakets are samples were simultaneous hybrization of gonosomes and disease-marker probes was applied, first percentage = amount of residual cells, second percentage = fraction of disease-marker positive residual cells.

Nine <pan class="Gene">span class="Species">patientspan> with disease-marker positive and disease-marker negative residual cells pan class="Chemical">UX% = under cut off level of X%, in brakets are samples were simultaneous hybrization of gonosomes and disease-marker probes was applied, first percentage = amount of residual cells, second percentage = fraction of disease-marker positive residual cells.

Discussion

Advantage of automatic scanning system "Metafer"

Chimerism analysis after sex-mismatched <pan class="Gene">span class="Disease">bone marrowpan> or peripheral blood stem-cell transplantation is an important diagnostic component to monitor transplantation and minimal residual disease and DLI [15-17]. The FISH technique progresses in importance but demands high personnel skills and costs. An automatic chimerism analysis system could be the solution for that dilemma and was evaluated here. As advantage of automatic analysis using Metafer turned out, that the picture and the coordinates of each cell are memorized. Via basing points it is possible to relocate each cell for further investigation. Moreover, it is possible to analyze huge amounts of cells and to detect small subpopulations of residual cells. Automatic analysis correlates linearly with manual analysis (R2 = 0.985) [18]. This permits to compare automatic and manual chimerism analysis. Because of the small fraction of the targeted cells in the whole population one should analyze in future studies more than 1600 cells for a reasonable precision (rel. standard deviation of 25%) as described in the statistical part.

FISH vs. PCR

Comparing FISH and PCR in chimerism analysis it was shown that the results are in concordance [7]. The sensitivity of PCR is between 3–5% and allows only semiquantitative analysis [4,19] whereas FISH is more sensitive (1%) and is absolutely quantitative [20]. Because of the different sensitivities it is recommended to use just one method [21], in <pan class="Gene">span class="Species">patientspan> with complete chimerism the method with the highest sensitivity should be used for early detection of residual cells [17,22].

Evaluation of cut off levels and possible source of error

For cut off levels in XY-FISH-analysis it could be shown that they depend on the sum of evaluated cells per sample (e.g. 3,000 counted cells: cut off 1.2% and 0.6% respectively – see Fig. 3. Trakhtenbrot and coworkers [23] described a very alike cut off level in female cells. In <pan class="Gene">span class="Species">womenpan> with sons, male cells could be found 27 [24] or 38 years [25] postpartum in blood samples. The authors showed that up to 40.000 male cells could be transplanted in a normal PBSCT by female <spapan>n class="Species">donors. In case male cells were found in <span class="Species">patients after transplantation this would be incorrectly interpreted as residual cells. Therefore, listing of female donors with sons is recommended in anamnesis and should be considered in chimerism analysis. Unfortunately, this information was not available for the investigated patients. In the present study in two samples residual cells were arranged in conglomerates (<pan class="Gene">span class="Species">patientpan> 36, in sample 20 and 26 month after transplantation). The histological origin of these cells was not investigated. Potentially these cells resembled endothelial cells that derived from injury of the endothelium. To prevent contamination with endothelial cells samples from the third aspiration of a single venous puncture is recommended for the cytogenetic analysis. The false positive rate of 1.2% for trisomy 8 we determined was in concordance with Jenkins et al. [26] and Cuneo et al. [27]. The <spapan>n class="Gene">bcr/abl-false positive rate of 0.7% was identical with Amiel et al. [28], Van den Berg et al. [29] and Mühlmann et al. [30]. However, overall a big variation can be found in the literature concering false positive rate of <span class="Gene">bcr/abl which is given between 2–10% [20,31-34]. Possible reasons for these differences could be: 1) different tissue samples (bone marrow vs. peripheral blood), 2) different cell cycle stage (G1, G2) or 3) different chromatin structure in healthy and moribund cells [35] and 4) different probes. With 95-quantil the cut off level for simultaneous hybridization of gonosomes and disease-markers were estimated and represent 0.005% in XX+trisomy 8/XX+bcr/abl and 0.003% in XY+trisomy 8/XY+bcr/abl. This allows detecting one disease-marker positive residual cell in 20.000 analyzed cells which was claimed already in 1994 [36]. PCR as alternative diagnostic method does not have this high sensitivity.

Automatic scanning applied on sex-mismatched patients

33 <pan class="Gene">span class="Species">patientspan> out of 58 had a complete chimerism, 13 <spapan>n class="Species">patients residual cells < 4% and 12 <span class="Species">patients residual cells > 4%. As expected the detection of residual cells > 4% correlated with relapse as described in literature [37,38]. 66.7% out of patient group > 4% residual cell died because of relapse. Median survival from detection of residual cells and relapse was 6 month and is identical with the data published by Uzunel et al. [39]. Other studies could not find a correlation between mixed chimerism and relapse [40-42]. To what extend mixed chimerism gives evidence about relapse is discussed controversially. In here presented data the occurrence of residual cells was not a marker for relapse. One reason might be the retrospective analysis of patients in this work. In 12 <pan class="Gene">span class="Species">patientspan> a simultaneous hybridization of gonosomes and disease-markers was applied. 7 <spapan>n class="Species">patients had disease-marker positive residual cells. But the study showed also that disease-marker positive and disease-marker negative residual cells can be verified within a sample. The detection of disease-marker positive residual cells had no impact on relapse or survival. In contrast Führer et al. [14] could detect disease-marker positive residual cells before relapse. Thiele et al. [13] also arranged a simultaneous hybridization of gonosomes and disease-markers and assumed that cells carrying the disease-marker represent the source for later relapse. In 3 samples only disease-marker negative residual cells were found. They might represent 1) healthy (benign) leucocytes, 2) precursor <pan class="Gene">span class="Disease">tumorpan> cells which do not yet carry the disease-marker, 3) false negative disease-marker positive cells, 4) endothelial cells or 5) cells from female <spapan>n class="Species">donors with sons.

Conclusion

Automated chimerism analysis is a robust and sensitive method which can be used in routine diagnosis to detect residual cells effectively and economically. Simultaneous hybridization of gonosomes and disease-marker represent a sensitive method to detect disease-marker positive residual cells with a very low cut off level. The amount of residual cells correlates with survival. There are <pan class="Gene">span class="Species">patientspan> with residual cells < 4% without tendency of relapse. The detection of disease-marker positive residual cells up to 1.3% does not correlate with relapse. Disease-marker positive and disease-marker negative residual cells can appear at the same time in one sample. The definite origin of disease-marker negative residual cells is unclear and should be investigated in a large multicenter study.

Methods

Controls

Peripheral blood samples of 21 clinically healthy male (11) and female (10) between 6 and 67 years were studied as controls.

Patients

A total of 28 female and 30 male <pan class="Gene">span class="Species">patientspan> were analyzed retrospectively after sex-mismatched stem cell transplantation which were performed between 1995 and 2006 at the University Medical Centre Jena. As shown in Table 1, there were 24 <spapan>n class="Disease">acute myloid leukemia (AML), 16 <span class="Disease">chronic myeloid leukemia (CML), 5 acute lymphatic leukemia (ALL), 4 multiple myeloma (MM), 3 severe aplastic anemia (SAA), 2 myelodysplastic syndrome (MDS), and 1 patient each with Non-Hodgkin lymphoma (NHL), chronic lymphatic leukemia (CLL), lymphoma (Lym) and osteopetrosis (OP). Conditioning regimens were dose reduced in 30 patients or myeloablative in 23 patients [44-46] 54 patients underwent peripheral blood stem-cell transplantation (PBCST) and the remaining 4 bone marrow transplantation (BMT). The median age of the transplanted patients was 46 years (2–89 years). 12 patients showed cytogenetic disease-marker in their malignant cells, i.e. a bcr/abl-fusion in nine and a trisomy 8 in three patients. Overall, 19 patients died, either due to relapse (n = 9), a graft-versus-host-disease (n = 3) or an infection (n = 4). In 3 patients the reason of death remained unclear.

Cytogenetics and molecular cytogenetics including FISH analysis

Standard techniques were used to cultivate leukocytes out of venous blood, prepare chromosome-preparations [43], and to perform interphase FISH analysis [44]. Commercially availn class="Gene">able probes (Abbott, Wiesbaden, Germany) for LSI-ES <span class="Gene">bcr/abl, centromere 8, X and Y were applied.

Automatic chimerism analysis

For automated analysis we used an Axioplan 2 Imaging microscope (Carl Zeiss Jena, Germany) equiped with <pan class="Gene">span class="Disease">CCDpan>-camera CV-M1, 1280 × 1024 pixel (Jai Glostrup, Denmark) and a motorized stage with 8 slide positions (Märzhäuser, Wetzlar, Germany). All components were connected to a personal computer (Dell, Langen, Germany) running the Metafer/MetaCyte-Software from MetaSystems (Altlussheim, Germany). The evaluation procedure of FISH-slides was as followed: 8 slides were automatically scanned over night and the amount of residual cells was registered. Cells which did not have the characteristic signal combination for XX and XY were excluded. All detected potential residual cells were visually controlled by microscope and each valid cell was further examined wether the residual cell carried a disease-marker or not. The system allowed repositioning of all residual cells in order to visually control the group of interest. Tpan class="Gene">able 3 shows the parameters used for automated scanning.
Table 3

Parameters used for automated scanning

Parameter/GroupValuesDescription
Capturing
Color ChannelsDAPISpO/SpA (X)FITC/TRITC (Y)
Max. Integration Time1.0 s0.5 s0.33 sFor capturing images with comparable signal intensities, automatic integration time adjustment was used to reach a certain saturation level in the images while the maximum integration time was limited to 0.5 s (green) and 0.33 s (red) for keeping the background level at low intensities for empty image fields (e.g. not showing signals).
Saturation Area4 μm20.7 μm21 μm2
N Focus Planes155Due to the fact that nuclei are not perfectly flattend on the glass slide by preparation but show Z dimensions within a certain range, the fluorescently labeled chromosomes may be randomly localized in the nucleus also in Z direction.
Distance0 μm0.75 μm0.75 μmTo image the FISH spots perfectly focused, for each signal channel 5 focus planes are captured with a distance of 0.75 μm (this correlates with the depth of field of the objective lens used). These focal planes are then combined to an "Extended Focus Image" which is used for analysis later.
CCD Gain400%A CCD camera gain factor was specified to reduce the integration times needed and thereby increase the scanning speed. With the value specified the electronic noise in the captured images was still negligible.
Use CS Mask during CaptYesThis parameter was activated to use the counterstain mask for integration time adjustment. As bright artifacts within the image field would usually interfere with the automatic integration time adjustment, using the counterstain mask enabled correct adjustment for image fields where such artifacts were only present outside the nuclei.

Image ProcessingMedianVMedianVAn image processing operation was applied to the signal channels to reduce the noise level without significantly reducing the sharpness of the image by vertical median filtering. This filtering was used to remove small "hot spots" of one pixel size in the images which appear in CCD camera images after long integrations or due to camera pixel defects.

Cell Selection
Obj. Threshold23%An object threshold of 23% in the counterstain channel was used to segment the cell nuclei. The value is a percentage based on the total contrast range of the captured image.
Min. Nucleus Area18 μm2The minimum/maximum area in μm2 for a single cell nucleus to be accepted for analysis was used e.g. to exclude (larger) cell clusters.
Max. Nucleus Area200 μm2
Max. Rel. Conc. Depth0.4This criterion has been used to discriminate single cells (showing a convex contour with only small concave areas) from cell clusters (which usually have large concavities). The limit is specified relative to the nucleus diameter.
Max. Aspect Ratio2.8This criterion has been used to discriminate the nuclei of interest from more elongated objects. It specifies the maximum ratio of the nucleus diameters along the long and the short principal axis.

Cell Processing
CS/R/GSBHistoMax ApplyMaskAdditional image processing was applied to reduce background/exclude image content outside nucleus contour.
Extend CS Mask0.5 μmTo correctly identify signals on the nucleus edge the counterstain mask has been extended by 0.5 μm.
Features/Spot Counting
Max. Spot Rel. Area100/100015/1000To differentiate true FISH spots from variations in the fluorescence background, an upper limit for the relative area of a spot, compared to the whole nucleus (in units of 1/1000) was defined, This was mainly of interest for the green channel (Y chromosome).
R (X)SpotCounts (5,27)The number of red FISH spots was determined. Spots were accepted (counted) if they had a minimum distance of 0.5 μm and a minimum intensity of 27% compared to the brightest spot in the same cell.
Reject if > 2Cells with more than 2 red spots were automatically rejected.
G (Y)SpotCounts (14,78)The number of green FISH spots was determined. Spots were accepted (counted) if they had a minimum distance of 1.4 μm and a minimum intensity of 78% compared to the brightest spot in the same cell.
Reject if > 2Cells with more than 2 green spots are automatically rejected.
Reject if No SpotsYesCells not showing any X signals are automatically rejected.

Most important parameters for the classifier used for analyzing the patient samples.

Parameters used for automated scanning Most important parameters for the classifier used for analyzing the <pan class="Gene">span class="Species">patientpan> samples.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

JE carried out the cytogenetic work, was involved in performing the statistical analysis and conceived the manuscript. IH and AH made substantial conclusions and performed initial tests. HS performed initial tests. MH performed the main part of the statistical analysis with help of TK and AG. HGS made substantial contributions to acquisition of data and gave final approval of the version to be published. TJ extracted the software parameters for Metafer. UC made substantial conclusions to conception and design. TL drafted the manuscipt. IFL designed the structure and coordinated the study. All authors read and approved the final manuscript.
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