Allogeneic hematopoietic stem cell transplantation (HSCT) offers a potential cure for a variety of hematological malignancies. Patients without an HLA matched sibling donor can turn to unrelated ...donor registries to identify a suitably HLA matched donor. In the case where a fully HLA-A, -B, -C, -DRB1 and -DQB1 (10/10) matched donor is unavailable, there are often multiple 9/10 matched donors to select from. However, the prioritization and identification of permissive HLA mismatches in the 9/10 matched setting have proven elusive. Fetal exposure to non-inherited maternal antigens (NIMA) imparts lifelong immune modulating effects leading to tolerance to these antigens. Prior studies have found that matching for non-inherited maternal antigens (NIMA) can lead to lower rates of acute graft versus host disease (aGVHD) and lower treatment-related mortality (TRM) in cord blood HSCT (J.J. van Rood et al., Blood 2002; J. J. van Rood et al., PNAS, 2009; V. Rocha et al., BBMT, 2012). Patients undergoing mismatched HSCT with adult unrelated donors could benefit from NIMA matching by introducing maternal HLA testing during confirmatory typing of the donor and using NIMA matching as a criterion for mismatched donor selection.
This joint EBMT-CIBMTR retrospective analysis was designed to evaluate the influence of NIMA matching in HSCT with mismatched adult unrelated donors. Matching criteria were based on HLA-A, -B, -C, -DRB1, -DQB1 at high resolution. Included donor-recipient pairs had 5 loci HLA typing and a minimum of one year follow-up recorded at EBMT or CIBMTR and donors were registered with DKMS German Bone Marrow Donor Center. To obtain maternal HLA typing information, DKMS contacted the respective donors by mail to inform about the study and to provide detailed information, a buccal swab kit and an informed consent form to the donor's mother that the donor could send on. SBT-based HLA typing was performed at the DKMS Life Science Lab, Dresden, Germany once signed informed consent and samples were received. A total of 1735 donors were contacted and maternal samples could be retrieved for 803 cases (46%). A total of 50 NIMA matches (6%) were found reflecting the rate expected from previous studies.
Multivariate analyses were performed using Cox proportional hazards models adjusting for significant co-variates for overall survival (OS), disease free survival (DFS), relapse, TRM and acute and chronic GVHD comparing NIMA matched to NIMA mismatched cases.
The final analysis population was restricted to 9/10 matched cases (N=452) transplanted for acute myeloid leukemia (N=307) and acute lymphoblastic leukemia (N=145) using myeloablative (N=307) or reduced intensity (N=145) conditioning from 1999-2013. The NIMA matched (N=32) and mismatched (N=420) groups were well balanced for all disease, patient, transplant and donor characteristics. The groups differed by mismatched HLA locus with the NIMA matched group skewed towards more HLA-C mismatches (66% vs. 35%). Univariate analyses did not find any significant differences between the NIMA matched and mismatched groups for any outcomes. TRM rates were similar between the groups at 1 year with 23% (95% CI: 10-40%) and 23% (95% CI: 19-28%) in the NIMA matched and mismatched groups, respectively. No significant associations were observed in multivariate analyses of the NIMA matched versus mismatched groups (Table).
In contrast to prior studies of NIMA matched HSCT, no significant associations were found between NIMA matching and any outcomes. However, our findings may be due to the fact that the current study was underpowered to detect the expected difference in TRM observed in prior studies. Investigation on a larger cohort or a prospective trial would be needed.
We thank Carlheinz Müller from the German unrelated donor registry ZKRD for providing additional HLA information and the donors and their mothers for their cooperation in this study.
Table. Multivariate analysis results of NIMA matched versus mismatched (used as reference) HSCT Table 1OutcomeHR95% CIp-valueOS0.890.54-1.480.653DFS0.880.53-1.430.598TRM0.740.35-1.600.447Relapse0.890.45-1.750.737aGVHD II-IV0.970.53-1.800.935aGVHD III-IV0.590.19-1.910.382cGVHD1.770.99-3.160.053
Lee:Bristol-Myers Squibb: Consultancy; Kadmon: Consultancy. Nagler:Biokine LTD: Consultancy.
1010-lbp Sauter, Jürgen; Solloch, Ute; Hofmann, Jan ...
Human immunology,
06/2014, Volume:
75, Issue:
6
Journal Article
Peer reviewed
Aim The heterogeneous nature of HLA information (missing loci, various typing resolutions) in current donor registries may hamper unrelated donor searches. In our study, we estimated the probability ...of “worst-case searches”, that happen when registered donors who are 10/10 allele-level matches to patients in need of a transplant are not identified in the search process. Methods For that purpose, we generated a virtual donor file with d = 2,600,000 donors based on 5-locus high-resolution (HR) haplotype frequencies (HF) of the German population. HF had been estimated from a very large sample ( n = 370,856). Each virtual donor was assigned randomly to one of 5 typing levels, ranging from level 1 (28% of all donors, HLA loci A, B, C, DRB1 and DQB1 typed at HR) to level 5 (17%, only HLA-A and -B typed at low resolution). The resulting file is a simplified model of DKMS Bone Marrow Donor Center (reference model). With the same HF, we also generated p = 10,000 virtual patients. Within donor searches for these patients, virtual HLA typings of incompletely typed donors could be requested based on matching probabilities. As typing result, the donor’s known HLA information was uncovered. To assess their importance, we varied input parameters of our simulation, such as the number of allowed virtual typings and of donors in the file, the distribution of typing levels, and the diversity of the HF-distribution. Results In the reference model, no HLA-matched donor(s) could be identified for 2.7% (1.8%) of the patients if 3 (10) virtual typings were allowed. We found that these ratios are most strongly influenced by the distribution of typing levels and least by the donor file size. We also observed that when donors of level 5 are ignored during virtual typings, some patients remain without donors irrespective of the number of virtual typings allowed. Conclusions In order to minimize the number of “worst-case searches”, registries should type new donors with the highest resolution available and for all relevant HLA-Loci.
The heterogeneous nature of HLA information (missing loci, various typing resolutions) in current donor registries may hamper unrelated donor searches. In our study, we estimated the probability of ...“worst-case searches”, that happen when registered donors who are 10/10 allele-level matches to patients in need of a transplant are not identified in the search process.
For that purpose, we generated a virtual donor file with d=2,600,000 donors based on 5-locus high-resolution (HR) haplotype frequencies (HF) of the German population. HF had been estimated from a very large sample (n=370,856). Each virtual donor was assigned randomly to one of 5 typing levels, ranging from level 1 (28% of all donors, HLA loci A, B, C, DRB1 and DQB1 typed at HR) to level 5 (17%, only HLA-A and -B typed at low resolution). The resulting file is a simplified model of DKMS Bone Marrow Donor Center (reference model). With the same HF, we also generated p=10,000 virtual patients. Within donor searches for these patients, virtual HLA typings of incompletely typed donors could be requested based on matching probabilities. As typing result, the donor’s known HLA information was uncovered.
To assess their importance, we varied input parameters of our simulation, such as the number of allowed virtual typings and of donors in the file, the distribution of typing levels, and the diversity of the HF-distribution.
In the reference model, no HLA-matched donor(s) could be identified for 2.7% (1.8%) of the patients if 3 (10) virtual typings were allowed.
We found that these ratios are most strongly influenced by the distribution of typing levels and least by the donor file size. We also observed that when donors of level 5 are ignored during virtual typings, some patients remain without donors irrespective of the number of virtual typings allowed.
In order to minimize the number of “worst-case searches”, registries should type new donors with the highest resolution available and for all relevant HLA-Loci.
Aim Killer cell immunoglobulin-like receptors (KIRs) are expressed on cells of the innate immune system. The KIR system has been found to be important in donor selection for hematopoietic stem cell ...transplantation in certain circumstances (Cooley et al. Blood, 2010). In addition to the frequency of these 17 KIR loci in donors of German, Polish, and Turkish descent, we present the most common KIR genotypes in these ethnic groups as well as the frequency of KIR haplotypes. Methods More than 82,000 donors have been recruited from January through April 2015 by DKMS in Germany and typed for absence or presence of 17 KIR genes and pseudogenes using an NGS-based amplicon approach targeting exons 4, 5, and 7 of the respective genes. While KIR2DL5A and KIR2DL5B genes are not distinguished, KIR2DS4 and KIR2DS4N are reported separately, as null alleles are not biologically functional. Frequencies are given by the relative fraction of typing results. Results 70,411 of the donors recruited indicated to be of German descent, 4989 of Turkish and 860 of Polish descent. The most common KIR genotype in all 3 ethnicities includes the presence of only 2DL1, 2DL3, 2DL4, 2DP1, 2DS4N, 3DL1, 3DL2, 3DL3, and 3DP1 genes. For all populations, the most frequent KIR genotype, according to the classification of Cooley et al., is B/2, while B/4 is most rare.
KIR genes are recognized to play an important role for stem cell transplantation. The high polymorphism of these genes makes it difficult to achieve high resolution typing results.Based on paired-end ...short amplicon next generation sequencing (NGS) data from the Ilumina Miseq and HiSeq systems, neXtype was adapted to type KIR on allelic level. neXtype reports KIR allele typing results in the genotype list (GL) string format and implicitly provides gene copy numbers.neXtype copes with KIR typing challenges in several consecutive steps:In a first step based on the IPD-KIR library, each read is assigned the best matching known exon sequence using the tree-concept of neXtype. In a second step, the copy numbers of the identified allelic variants per exon are determined for a given primer batch. This estimated exon copy number is subsequently required for the scoring system. As a third step, combination of exon-specific results determines KIR alleles present in the sample. The number of valid exon combinations per gene yields the gene copy number. Currently, neXtype uses exons 3, 4, 5, 7, 8, and 9. The assignment of reads to a specific gene is a priori not possible as some alleles of different genes share identical exon DNA sequences. Therefore, valid combinations for those gene-bridging exons must be analyzed simultaneously. neXtype uses a scoring system based on the difference between the copy number as given by valid exon combinations from step three and the estimated exon copy number from step two. The exon combination with the lowest score is taken as the typing result and presented as a GL string.With this algorithm, samples with pre-known typing results were confirmed. In summary, we show that cost efficient high-throughput NGS data can be used for allele level KIR typing. As a consequence, allele level KIR typing could be included into the standard typing profile of newly registered stem cell donors, thus allowing for refined donor selection algorithms.
Abstract 2046▪▪This icon denotes a clinically relevant abstract
Donor search is a major challenge once the indication for allogeneic hematopoietic stem cell transplantation (HCT) has been ...established. For those patients who lack an HLA-identical sibling, unrelated donor search (UDS) needs to be initiated. Only if UDS is not successful, alternative stem cell sources like cord blood (CB) or alternative concepts like haploidentical HCT have to be considered. Since UDS is a time consuming process it is important to assess the probability to find a matched unrelated donor (UD) during prolonged UDS. Yet, very few data on the required times and the success rates of unrelated donor searches are available. Furthermore, information on the probability to find a donor within short time is crucial in the context of early allogeneic transplantation including HCT in aplasia after induction chemotherapy in AML or for the interpretation and planning of clinical trials employing donor versus no donor comparisons. Therefore, we have retrospectively analyzed the duration of UDS for a large cohort of patients.
All unrelated donor searches of one large search unit, which were initiated between January 2004 and July 2010 were analyzed retrospectively. Throughout that period blood from all donor-recipient pairs has been typed for HLA-A, -B, -C, -DRB1 and –DQB1 at the allele level (4 digits). A full match was defined by HLA-identity for HLA-A, -B, -C and DRB1 (8/8), while a partial match was defined as a single mismatch in the HLA-A, -B, -C or DRB1 locus without additional DQB1 mismatch (9/10). The duration of UDS was calculated from the date of data entry to the date of receipt of confirmatory typing (CT) of the first 8/8 HLA-matched donor or the first 9/10 HLA-matched donor. When given as reasons for the termination of the search, poor clinical condition or death of a patient were considered as competing events. Unsuccessful searches were censored at the day of the receipt of the last typing request or when UDS was stopped for other reasons. Cumulative incidences of successful UDS were calculated with competing event statistics. Approximative 95% confidence intervals are provided for point estimates.
In the respective time period 852 UDS comprising 8477 donor requests were performed. In the Caucasian population, an HLA compatible UD (8/8) has been found for 29% (95% CI, 26% to 32%) of the patients within two weeks, 54% (95% CI, 51% to 58%) of patients within 4 weeks, and 61% (95% CI, 57% to 64%) of patients within 6 weeks (Figure 1). In high risk diseases and high urgent indications for allogeneic transplantation one antigen or allele mismatch may be acceptable. Therefore, we calculated the probabilities to find an HLA matched UD (8/8) or a partially matched UD (9/10) within defined times. The resulting probabilities of finding an acceptable donor who met these criteria for Caucasian patients were 35% (95% CI, 32% to 39%), 66% (95% CI, 63% to 70%) and 75% (95% CI, 72% to 78%) at two, four, and six weeks respectively. After six weeks of UDS the probability of finding a donor declined. Between the six week landmark and the 12 week landmark 8/8 HLA matched unrelated donors have been identified only for additional 4% of the patients. Extending UDS up to one year resulted in additional 3% HLA matched donors (8/8). The incidence of the competing events (death or deteriorated condition of the patient) was 10% (95% CI, 6.6% to 13.8%) at one year when the aim was to find an 8/8 HLA matched UD. Eight UDS (1%) were started for non-Caucasian patients. Only for one of the eight non-Caucasian patients an HLA-compatible donor (8/8) was found.
For Caucasian patients HLA compatible UDs (8/8) can be identified in our population for 61% of the patients within six weeks. If donors with one mismatch (9/10) are accepted the probability increases to 75% at that time. Beyond that landmark, the probability of finding donors for the remaining patients declines steeply and alternatives like haploidentical or cord blood transplantation should be considered. Since an HLA matched donor can be identified for 29% of the patients within two weeks, UDS is a valid option even for very high urgent searches like in the context of allogeneic HCT in aplasia. Unrelated donor searches for patients with non-Caucasian ancestry are much less successful. Further analyses are planned in order to define the probability to find a donor related to the haplotype frequency of the patient. Display omitted
Off Label Use: pentostatin is not licensed for use in acute GvHD.
Abstract 365
Donor follow-up is indicated to detect potential long-term risks for allogeneic stem cell donors. We sent a follow-up questionnaire to 15,456 donors of peripheral blood stem cells (PBSC) ...or bone marrow (BM) within a retrospective study design. Donors were asked for their general health conditions (question #1), hospitalization or long-term medical treatment since donation and the underlying disease (#2), prescription drugs taken regularly or for at least 4 week since donation (#3) and for their willingness to donate again (#4).
With 12,559 responses, we achieved an overall return rate of 81.3% leading to 30,777 observation years for PBSC donors (n=8,730), 23,037 for BM donors (n=3,556) and 1,414 for donors of both PBSC and BM (n=273). The median (average) time since donation of responding donors was 3.3 (4.2) years.
Most donors (95.1% of PBSC, 96.0% of BM and 92.2% of PBSC+BM donors) assessed their health conditions as very good or good (comparison of PBSC and BM donors: χ2 test, p=0.03). In univariate analysis, PBSC donors showed significantly less often indicators for health-related problems according to questions #2 and #3 than BM donors (χ2 tests, p<0.001). Multivariate analysis, however, did not confirm these differences. As the PBSC sample included significantly more male (χ2 test, p<0.001) and younger (χ2 test, p<0.001) donors than the BM group, we conclude that the observation of more health-related problems in BM donors resulted from differences in sample characteristics. The willingness to donate again was high in both PBSC and BM donors (95.4% and 95.9%, respectively; χ2 test, p=0.17).
In total, 85 malignancies were reported within the project, thereof 50 in 48 PBSC donors, 31 in BM donors and 4 in donors of both PBSC and BM. Six cases of hematological malignancies are included: 2 cases of Hodgkin's disease (both in PBSC donors), plasmocytoma (PBSC donor), AML (BM donor), Non-Hodgkin lymphoma (BM donor), CLL (donor of both PBSC and BM). Through donor center practice, we got notice of 21 further donor malignancies, 5 of those were hematological: Hodgkin's disease (PBSC donor), plasmocytoma (PBSC donor), AML (donor of both PBSC and BM), and 2 cases of CML (1 PBSC donor, 1 BM donor).
The observed standard incidence ratio (SIR) for all malignancies and all donors of 0.99 (95% confidence interval: 0.79–1.24) suggests that underreporting does not substantially affect the quality of the collected data on malignancies. Corresponding SIR values for PBSC and BM donors are 1.12 (0.82-1.50) and 0.84 (0.56-1.19), respectively.
A higher-than-expected incidence of malignant melanoma could be observed in BM donors (SIR=3.02, 95% confidence interval 1.38–5.73, based on 9 reported cases). As a correlation between BM donation and the development of malignant melanoma seems not to be plausible, a type I statistical error may be the most probable explanation for this result. Furthermore, we observed lower-than-expected incidences of lung cancer (SIR=0.15, 95% confidence interval 0.00–0.82) and malignant neoplasms of lips, oral cavity and pharynx (SIR=0.00, 95% confidence interval 0.00–0.75). A correlation between malignancy development and a lack of health-conscious behavior is well-known for these malignancies. One might, therefore, hypothesize that stem cell donors show more often health-conscious behavior than the general population.
No increased incidences of leukemia, non-Hodgkin lymphoma, plasmocytoma or Hodgkin's disease compared to age- and gender-adjusted incidences of the German population could be observed in PBSC, BM or PBSC+BM donors. The respective SIR values with 95% confidence intervals for PBSC donors are 0.00 (0.00-2.62), 0.00 (0.00-1.72), 3.59 (0.11-20.02) and 2.46 (0.30-8.89). Based on these data, a threefold or stronger increase of the leukemia risk through PBSC donation can be excluded with an error probability of α=0.05.
The high number of observation years supports the relevance of our study. A detailed analysis of malignancies allowed us to narrow down a potential increase of leukemia risk after PBSC donation that has been discussed in the literature. In summary, we found no evidence that PBSC or BM donation might be unsafe procedures. Our study shows that retrospective stem cell donor follow-up projects may be valuable complements to prospective donor follow-up that often suffers from high drop-out rates.
No relevant conflicts of interest to declare.
We describe 2127 new HLA alleles: 598 HLA-A, 755 HLA-B and 774 HLA-C alleles, accounting for 28.9 % of the currently known HLA class I alleles.
Buccal swabs or blood samples of newly recruited donors ...from three national DKMS donor centers were typed for HLA using sequencing-based typing (SBT) at the ASHI-accredited laboratory of HistoGenetics (Ossining, NY). New HLA class I alleles were identified after determination of DNA sequences of HLA exons 2 and 3. Comparison of the new allele sequences and their most homologous counterpart lead to detection and description of nucleotide variations in DNA sequences. Self-assessed parentage of individuals carrying new HLA class I alleles were examined.
Of the 2127 new HLA class I alleles described, 1336 (62.8%) were observed in donors from Germany, 422 (19.8%) in US donors, 213 (10.0%) in donors from Poland, and 156 (7.3%) new alleles were found in donors from at least two countries. We identified new alleles in 57 allele groups, including 192 C∗07, 144 A∗02 and 112 C∗03 alleles, The majority (93.8%) of the new alleles corresponded to single nucleotide variations. 67.0% of the new alleles comprised non-synonymous nucleotide substitutions and 30.0% silent mutations. The remaining 3.0% showed nonsense mutations identified in null alleles. New alleles were found disproportionally often in minority donors. Further, 527 new alleles (24.8%) were identified in multiple individuals.
We described 2127 new HLA class I alleles that have been identified in upfront HLA typing of newly registered DKMS stem cell donors. The occurrence of many new alleles in multiple individuals who originated partly from different populations indicates that newly identified alleles are not necessarily rare and thus may be of relevance for actual stem cell donor searches.
DKMS Life Science Lab adopted an NGS based HLA typing workflow in early 2013. Meanwhile more than a million samples have been successfully typed by NGS forming the basis for this review of the ...chances and pitfalls of such an approach.
Our NGS workflow is based on direct sequencing of PCR amplified exons on Illumina MiSeq instruments. Exons 2 and 3 of HLA-A, B, C, DRB1, DQB1 and DPB1 are amplified by PCR on Fluidigm Access Array chips. Recently the profile was extended to cover in addition ABO, Rhesus and CCR5. Amplicons of up to 768 samples are pooled for a sequencing run. Sequencing data is analysed by the in-house developed software neXtype.
The rather simple workflow proved to be very robust. Loading of the Fluidigm chips is critical and, due to the low volumes, needs careful optimization and regular maintenance of the involved liquid handlers. PCR continuously yielded sufficient product for loading on the sequencers. The MiSeqs in general produce very high quality sequence data. Low diversity samples like amplicon products pose a particular challenge to the MiSeqs but are meanwhile handled well. However, care must be taken to keep the rate of very short PCR artefacts low as those may negatively impact the overall quality. For analysis of the data care must be taken to identify crossover PCR products which may resemble true HLA alleles. In addition, due to PCR artefacts the rate of error at a particular position might be significantly higher than indicated by the q-values. When taking this into account software like neXtype can provide highly automated and accurate results at a fraction of the time of Sanger data analysis. Given adequate software we identified imbalanced amplification as the main source of error. Rigorous quality control of every reagent batch with regard to even amplification is essential. In addition samples with DNA concentrations below 3ng/μl should not be applied to 192 Fluidigm chips to avoid random loss of alleles.
Switching to NGS as the primary tool for HLA typing was highly beneficial for the lab. The NGS based workflow has proven superior to the previous Sanger based workflow in every aspect: Costs, hands on time, resolution, turnaround time, stability and scalability. We conclude that NGS technology has matured to a point where it is appropriate for everyday routine operation.
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