Secondary Logo

Journal Logo

Of Cells and Microparticles: Assets and Liabilities of HLA Antibody Detection

Liwski, Robert, S., MD, PhD1; Gebel, Howard, M., PhD, D(ABHI)2

doi: 10.1097/TP.0000000000001818

The evolution of antibody detection from cell- to bead-based technology has positively impacted the ability to allocate organs in a safe and timely manner. The devil, of course, is in the details that delineate how these assays are performed and applied and to recognize that while there have been some truly amazing technological advances (assets), they are still imperfect and subject to error (liabilities). This review identifies the strengths of HLA antibody assays, highlights their weaknesses and offers approaches for standardization.

1 Department of Pathology, Dalhousie University, Halifax, Nova Scotia, Canada.

2 Department of Pathology Emory University Hospital, Atlanta, GA.

Received 2 December 2016. Revision received 17 February 2017.

Accepted 9 March 2017.

Disclosure: The authors declare no funding or conflicts of interest.

R.L. and H.M.G. designed, drafted and critically reviewed the article.

Correspondence: Howard M. Gebel, PhD, D(ABHI), Department of Pathology, Emory University Hospital, Atlanta, GA. (; Robert S. Liwski, MD, PhD, Department of Pathology, Dalhousie University, Halifax, Canada. (

The landmark study by Patel and Terasaki1 revealed that kidney transplantation among patients with positive lymphocyte crossmatches to their respective donors frequently resulted in hyperacute graft rejection. The data were so compelling that prospective crossmatching became a mandate to kidney transplantation, the recommendation being that the crossmatch had to be negative before a transplant was performed. The underlying assumption was that the detection of antibodies binding to donor lymphocytes was a surrogate for graft loss. Subsequent studies revealed that the antibodies most often associated with hyperacute, acute and chronic kidney rejection were those that were directed to donor HLA antigens (reviewed in Terasaki and Cai2). The field of histocompatibility had a relatively quick maturation process based on the clinical need to unequivocally identify HLA antibodies and their corresponding antigens (reviewed in Gebel and Bray3).

Back to Top | Article Outline



From the beginning, it was recognized that lymphocyte crossmatching was not a perfect test to predict allograft outcome. Indeed, hyperacute rejection did not occur in 20% of patients with a positive lymphocyte crossmatch.1 The reverse was also true; the original complement-dependent cytotoxicity crossmatch (CDC-XM) was not sensitive enough to detect low level antibodies that were nonetheless strong enough to lead to hyperacute rejection (reviewed in Gebel et al4). The HLA community quickly responded to a self-imposed mandate and improved crossmatch sensitivity.

Back to Top | Article Outline


Approaches to improve the reliability of the CDC-XM were logical and systematic (reviewed in Gebel and Bray3 and Gebel et al4). First, incubation times of cells and sera were increased (“extended incubation”). Next came inclusion of “washing” steps to eliminate (or at least minimize) interference of anti-complement factors that could result in false-negative reactions. In this situation, after incubation between cells and serum, the system is flooded with media before the addition of complement. This test further evolved when an antihuman globulin (AHG) reagent was factored into the crossmatch equation. AHG enhanced cytotoxicity promoted the detection of low titer antibodies and detected antibodies that were cytotoxicity negative adsorption positive (CYNAP) and did not fix complement in vitro.5 The AHG-augmented crossmatch (AHG-XM) assay became the gold standard of crossmatch assays in North America and remained so until the emergence of the flow cytometric crossmatch (FCXM) in the mid 1980s.6,7 The FCXM represented a dramatic improvement in crossmatch sensitivity and detection of donor-specific antibodies (DSA) (reviewed in Gebel and Bray3 and Gebel et al4). Using fluorescently conjugated anti-IgG, the FCXM detects antibodies regardless of their ability to fix complement and at a much lower level than the AHG-XM. In addition, FCXM results can be interpreted in a semi-quantitative fashion by using several fluorescence scales such as median channel fluorescence or molecules of equivalent soluble fluorochrome units. These attributes greatly increased crossmatch reproducibility. Furthermore, they eliminated the subjectivity of CDC-XM assays which were deemed positive or negative by simple visual inspection. Another important advantage of the FCXM compared with CDC-XM assays was the ability to simultaneously and independently evaluate T and B lymphocytes. When numerous studies appeared in the literature reporting that patients whose AHG crossmatches were negative but FCXM positive were at a significantly increased risk for graft rejection (reviewed in 4), the FCXM supplanted cytotoxic assays as the crossmatch method of choice, at least in North America. Per the 2016 American Society for Histocompatibility and Immunogenetics (ASHI) AC-1 proficiency testing survey, 104 participating laboratories performed crossmatches using FCXM method, whereas only 39 and 28 laboratories used CDC-AHG and CDC methods, respectively.

A seismic shift in the approach to HLA antibody analysis occurred with the development of solid phase antibody detection assays, which use purified class I or class II HLA attached to fluorescently labeled microparticles.8 Antibodies are detected with fluorescently labeled anti-IgG using either a standard flow cytometer or, more commonly, Luminex technology. With the Luminex platform, antibody levels can be estimated in a semi-quantitative fashion using the mean fluorescence intensity (MFI) values with sensitivity similar to or exceeding the FCXM assay. Different versions of solid phase assays are currently in use. These include: (1) a screening assay wherein each bead in the panel is coated with either class I or class II antigens from several different donors; and (2) antibody identification assays using phenotype panels where each bead contains HLA antigens from a single donor, or single-antigen beads (SAB), where each bead is coated with a single recombinant HLA allele.8 The SAB assay detects and characterizes HLA antibodies with unprecedented specificity and precision and has become the most common method to identify HLA antibodies in both pretransplant assessment of immunological risk and posttransplant antibody monitoring.3,8-12 Solid phase HLA antibody detection assays encouraged the routine application of the so-called virtual crossmatch (VXM), wherein information garnered from the SAB assay is correlated with donor and recipient HLA typing at all HLA loci (HLA-A, B, C, DRB1/3/4/5, DQB1, DQA1, DPB1, and DPA1) and collectively used to predict the outcome of a physical crossmatch (ie, positive or negative). Virtual crossmatching has positively impacted organ allocation, organ sharing, and national and international kidney paired exchanges.13,14 Currently, some centers proceed directly to transplant (omitting prospective lymphocyte crossmatching), when SAB assay testing documents complete absence of DSA.15 Similarly, some centers have the confidence to proceed to transplant when a FCXM is positive but devoid of DSA (as determined by the SAB assay), attributing the positive crossmatch to non-HLA reactivity.16

Back to Top | Article Outline


Limitations of Crossmatching

The major limitation of a lymphocyte crossmatch is its relatively poor specificity that results from both false-positive and false-negative reactions (Table 1). In addition to HLA antigens, lymphocytes express a multitude of surface molecules (eg, Fc receptors, adhesion molecules, homing receptors, transferrin receptors), some of which can bind circulating immunoglobulins independent of their antibody specificity. Such binding leads to a positive crossmatch of no clinical significance,4,16 but is indistinguishable from a crossmatch resulting from HLA antigen/antibody interactions. It is for these reasons that a positive crossmatch should not be interpreted as a stand-alone result but only after correlation with solid phase antibody detection methods.8,16 False-positive crossmatch reactions can also occur due to autoantibodies.17 Thus, in select cases, performance of autologous crossmatches may be appropriate to help interpret whether a positive allogeneic crossmatch is clinically relevant.



Even when donor specific HLA antibodies are identified in a solid phase assay, there are many factors that can compromise their detection in a cell based crossmatch assay (eg, a FCXM assay). Preanalytical variables such as source of the cells (living vs deceased donor; blood vs spleen vs lymph node18), and/or donor treatment with medications (such as statins19) can each influence the level of HLA expression on donor lymphocytes and consequently impact the detection of DSA. Decreased expression of HLA antigens can result in insufficient targets onto which antibodies can bind, meaning that what should be a positive crossmatch will be misleadingly negative. In a similar fashion, how donor lymphocytes are isolated and prepared impacts the outcome of a FCXM. For example, treatment of lymphocytes with pronase (which removes Fc gamma receptors and minimizes nonspecific binding of IgG), can convert a B-cell crossmatch from negative to positive and totally redefine whether the presence of a DSA is considered relevant or irrelevant.20 Furthermore, pronase removes CD20 receptors on B cells thereby minimizing or eliminating B cell–positive reactions occurring due to rituximab treatment.21 This allows for immunologic monitoring using a FCXM assay in patients being treated with this monoclonal antibody. Although many laboratories incorporate pronase digestion of lymphocytes as part of their standard operating protocol, others deliberately avoid this enzymatic treatment for fear that, in addition to removal of Fc receptors, pronase will strip HLA molecules from the cell surface, which could result in false-negative crossmatches.22 Another concern with pronase treatment is the potential exposure of cryptic T-cell epitopes recognized by autoantibodies present in some patients.23 This can lead to false-positive T-cell FCXM reactions, especially in patients infected with human immunodeficiency virus whose sera commonly express such autoantibodies.24 Suboptimal lymphocyte purity can also compromise DSA detection in a FCXM assay, presumably because contaminating cells (primarily neutrophils) “soak-up” HLA antibodies.25 Each of these above issues underscore that, although all laboratories supporting solid organ transplant programs perform lymphocyte crossmatches and would argue that a standardized protocol is being followed,7 crossmatch procedures are not identical from laboratory to laboratory. A recent flow crossmatch proficiency testing study involving 13 HLA laboratories in Canada revealed a significant variability in flow crossmatch results which could be explained by numerous unrecognized protocol differences.26 These included reduced crossmatch sensitivity in laboratories using: (1) higher number of target cells, (2) lower serum to cell volume ratio, and (3) nonpronased lymphocytes. Additionally, false-negative reactions could be attributed to poor washing technique wherein serum immunoglobulin was incompletely removed. In these situations, the remaining immunoglobulin could bind to and “tie up” fluorescently labeled anti-IgG. Importantly, assay sensitivity and concordance of results were greatly improved when an optimized and standardized FCXM method (The Halifax protocol; manuscript in preparation) was used across the 13 laboratories.27

Unfortunately, even if crossmatch protocols were standardized, FCXM results could still vary from laboratory to laboratory depending on: (1) the selection of a negative control (eg, pooled AB blood group unsensitized healthy male sera vs pooled sera from unsensitized waitlisted candidates), (2) choice of fluorescence units for reporting purposes (linear values such as MFI or molecules of equivalent soluble fluorochrome vs log channels), (3) cutoff values below or above which a crossmatch is considered negative or positive, respectively and how these cutoffs are derived. In our experience, pooled negative control sera from healthy unsensitized AB blood group males typically exhibit reduced background reactivity compared with an average waitlisted candidate. Consequently, cutoff values are underestimated because the negative control serum reactivity is the baseline from which the cutoff is established. Low cutoff values correspond to an increased likelihood of false-positive reactions. When establishing crossmatch cutoffs, most laboratories typically test the reactivity of only a single negative control serum against several different donor cell targets and then calculate the standard deviation. This approach only captures the variability inherent to a single serum and is not representative of the variability seen with waitlisted candidates without DSA (or even no HLA) antibodies. In our experience, cutoffs determined with a single negative control are too narrow and result in a significant increase in false-positive reactions (up to 11%) when compared with cutoffs derived from testing several sera from un-sensitized waitlist patients with multiple donor cells (<2% false-positive rate; manuscript in preparation). Importantly, many, if not most, laboratories in North America follow ASHI recommendations and use a single negative control. This likely explains the data in recent studies that reported false-positive FCXM rates as high as 16%.16,28 Another factor leading to an increased incidence in false-positive crossmatches can be attributed to some unfortunate wording in the ASHI manual which states that laboratories “have an option” to add either 2 or 3 SD to the mean to establish cutoff values. Thus, the same cell-serum combination could be called positive or negative depending on whether 2 or 3 SD were used. In our experience, the highest correlation between predicted and observed FCXM was achieved when 3 SD was used for calculations. In this regard, each laboratory should develop a system to minimize the incidence of false-positive crossmatches.

Based on the collective data described above, it is not surprising that the clinical reliability and usefulness of the FCXM assay is (again) being questioned.16,29

Back to Top | Article Outline


Assay Variability

The introduction of solid phase assays revolutionized the way that HLA antibodies were identified. Because these tests are predicated on the use of purified HLA molecules, solid phase assays are more specific. The added benefit is that their application also enhanced the sensitivity of antibody detection.30 Nonetheless, the solid phase assays, particularly the SAB assay, were approved by the Food and Drug Administration as a qualitative test. Studies by Reed et al31 revealed that SAB testing lacks the precision to be quantifiable. Sources of variation include (1) lot-to-lot differences in density, orientation, and quality (native vs denatured) of antigen on the beads; (2) variability in anti–IgG-PE reagent; (3) variation in test procedures used by different laboratories; and (4) operator performance.8 Vendor-specific kit issues also contribute to the variability in MFI values and antibody classification in the SAB assay,31 ranging from differences in manufacturing practices, panel composition, secondary reagents, and recommended test protocols. In the study by Reed et al,31 a baseline coefficient of variance for the SAB assay MFI was reported as 62%, far from the 15% target value that qualifies an assay to be quantitative. However, because assay results are reported as a numeric value (MFI), the natural tendency is to interpret differences in MFIs as quantifiable data. That the units are not truly quantifiable underscores the challenges faced by the transplant community when comparing HLA antibody test results and MFI cutoffs, whether it be among the same patients at different time points in the same laboratory, between different laboratories testing the same samples, or assessing different clinical studies. Although protocol standardization can greatly improve the precision of the SAB assay MFI,31 the SAB assay should still not be considered quantifiable. Recent studies by Tambur and colleagues32 suggest that antibody titer may be a better measure of HLA antibody levels compared with MFI. However, because serum titration by SAB assay is costly and laborious and there have yet been no published studies demonstrating improved interlaboratory or intralaboratory concordance of results, this procedure has not been uniformly adopted for routine clinical testing.

The Achilles heel of solid phase testing is absence of common HLA alleles from the SAB assay panels. For example, C*07:02 is the only C*07 allele represented on the SAB panel by one vendor. Thus, if a patient possesses allele specific antibody against C*07:01, the antibody will be missed and a positive FCXM with a donor-expressing HLA-C*07:01 would be incorrectly interpreted as not being due to HLA antibodies. Several other very common alleles, such as HLA-A*02:02, A*02:05, A*02:06, B*35:02, B*35:08, B*39:06, C*12:02, C*12:03, DRB1*13:02 and DQB1*06:09 are missing from SAB panels by one or both vendors. Although these gaps in antibody testing can be minimized by using SAB and phenotype panels from both vendors and/or using supplemental allele panels, the vendors need to improve their SAB products by including common alleles. This issue also highlights the importance of allele level HLA typing to determine if all donor antigens were represented in the SAB panel used for antibody testing, and appropriately considered in virtual crossmatch interpretation. In cases where gaps are identified, physical crossmatches should be performed before transplantation.

Back to Top | Article Outline

Prozone Effect

Another significant limitation of the SAB assay is its susceptibility to the so-called prozone effect. In this situation, high titer complement fixing HLA antibodies exhibit significantly reduced MFI values or go completely undetected in the SAB assay.32-34 Initial reports attributed the prozone effect to competitive binding of IgM HLA antibodies to their corresponding HLA antigens on the SABs, thereby interfering with the binding of antigen specific IgG.33,34 Subsequent studies revealed that the interference is mediated through complement activation.35 Specifically, complement split products bind to the alloantibody/antigen complexes on the surface of SABs, thereby blocking the binding of PE conjugated secondary anti-IgG to the target alloantibody.36,37 Approaches to minimize the prozone effect include serum dilution,32-34 hypotonic dialysis,33 serum treatment with heat,35 dithiotreitol,33,34 or ethylenediaminetetraacetic acid,35 which eliminate/inactivate complement proteins or inhibit enzymatic activity of specific complement factors by chelating calcium, respectively.

The prevalence of prozone has not been well studied. Tambur and colleagues32 reported that 71% of patients in their cohort of sensitized patients demonstrated the prozone effect in at least 1 HLA specificity. In our experience, prozone-positive specificities are present in 40% to 50% of highly sensitized patients (calculated panel reactive antibody, > 95%), most of whom (>80%) received previous transplants. The remaining patients typically have a history of several pregnancies and/or blood transfusions. Using ethylenediaminetetraacetic acid to treat prozone-positive sera, we found approximately one third of prozone-positive specificities are below 2000 MFI and invariably lead to a strong positive FCXM against donor cell targets expressing relevant antigens (manuscript in preparation). This represents another flaw in SAB testing. When SAB MFI values are below 2000, many laboratories would consider the corresponding specificity(ies) to be either negative or confer low clinical risk. Obviously, a negative VXM may incorrectly be assigned when a donor expresses that antigen. Thus, failure to recognize specificities that exhibit the prozone effect in highly sensitized patients could have serious clinical impact, such as allocating and transporting organs from long distances based on a negative VXM whose FCXM will be positive. Based on such repercussions, it is strongly recommended that laboratories incorporate strategies that detect prozone-positive sera.

Clearly, the prozone effect can markedly underestimate the MFI values in the SAB assay. Unfortunately, most published studies that investigated the effect of either pretransplant or posttransplant DSA MFI on clinical outcomes appeared in the literature before the identification of the prozone phenomenon. As such, modalities to mitigate the prozone effect were not incorporated and very likely influenced how the data were interpreted. For example, Gloor et al,38 upon studying a cohort of sensitized patients with positive pretransplant cytotoxicity and/or flow crossmatches, found no difference in the rate of antibody mediated rejection between the subgroups with low MFI (<5000) vs moderate MFI (5000-10 000) DSA. One possible explanation of why no difference was seen is that the patients with early AMR in the low MFI subgroup had DSA with much higher MFI that were masked by the prozone effect.

Back to Top | Article Outline

Denatured Epitopes

Several studies have reported that sera from healthy male patients with no prior allosensitization history show reactivity with HLA antigens in the SAB assay.39-41 It is believed that these so called “natural” antibodies are directed against cross-reactive epitopes found in microorganism or polypeptides from ingested proteins.40 Epitope mapping demonstrated that most of these antibodies are directed against cryptic epitopes on denatured class I HLA antigens, which are exposed due to conformational changes that occur when β2 microglobulin and peptide within the peptide binding groove are dissociated from some of the HLA molecules during the manufacturing process.39 The nature of reactivity against class II HLA antigens has not been studied as extensively; however, based on recent absorption/elution studies, it is believed that in many cases denatured epitopes are targeted.42

One strategy to distinguish between antibodies targeting denatured vs native class I HLA epitopes is to treat SABs with acid, thereby denaturing all HLA molecules. Antibodies that do not react with acid-treated beads are presumed to target native epitopes, while those that continue to react or increase in reactivity are directed against denatured epitopes. Another approach was to use a modified SAB product devoid of denatured class I HLA (iBeads, OneLambda), which presumably only bound antibodies that targeted native epitopes.43 Unfortunately, iBeads are no longer marketed.

Studies using the above approaches demonstrated that most antibodies directed against denatured epitopes do not react with native HLA antigens in a flow crossmatch assay,44,45 which led to obvious questions about whether such antibodies were clinically relevant. Indeed, transplant recipients with DSA targeting denatured epitopes on class I HLA molecules have been shown to exhibit similar graft survival to patients with no DSA.46,47 In this context, it is important to note that antibodies targeting denatured class I HLA are very common, occurring in 21%45 to 39%44 of waitlist candidates. Listing these specificities as unacceptable antigens can significantly increase calculated panel-reactive antibody in many candidates44,45 and negatively impact their access to transplantation. For this reason, laboratories should implement strategies to distinguish such antibodies from those targeting native HLA epitopes. Both acid treatment of SAB and physical crossmatching should be used as some patients have antibodies targeting both native and denatured epitopes expressed on the same antigen.48 Again, vendors are urged to improve their manufacturing processes to minimize the level of denatured antigens on the beads, perhaps reintroducing products such as iBeads.

Back to Top | Article Outline


Although the limitations of current HLA antibody testing assays are undeniable, the advances in understanding why these limitations exist and the development of strategies to overcome them are nothing short of remarkable. For example, many laboratories now routinely use one of several serum treatment methods or serum titration on the SAB assay to avoid false-negative reactions due to the prozone effect. The awareness that antibodies detected in the SAB assay can be directed against denatured HLA epitopes is expanding and many laboratories have developed algorithms to identify and distinguish these antibodies (eg, pattern reactivity such as MFI values >20 000 on SAB testing with no detectable activity on FlowPRA, acid treatment of SABs, parallel use of additional solid phase assay kits, physical crossmatching with cell targets expressing native HLA antigens as well as software programs such as HLAMatchmaker and the epitope registry to help determine if the reactivity pattern makes biological sense) from antibodies to native epitopes. Vendors are actively working to improve their manufacturing process, quality control and testing protocols. Advances in molecular HLA typing technology have led to enhanced typing resolution at all HLA loci, improving the accuracy of virtual crossmatching, minimizing the incidence of unexpected positive physical crossmatch reactions and optimizing organ allocation. Adoption of improved techniques for lymphocyte isolation and flow cytometry crossmatch protocols will significantly improve the precision and reliability of lymphocyte crossmatch assays.

Efforts are already underway worldwide to standardize the intricate and complex aspects of HLA antibody testing and interpretation. Widespread use of the strategies discussed herein is predicted to significantly improve patient access to transplantation as well as their clinical outcomes. It is conceivable that contradictory outcomes reported by different centers can be explained by lack of standardized approaches to antibody identification. Design of new clinical studies must include test standardization strategies to limit variability and optimize results. With such approaches, conclusions regarding the impact of HLA antibodies on outcomes can be made with confidence. Time will tell.

Back to Top | Article Outline


1. Patel R, Terasaki PI. Significance of the positive crossmatch test in kidney transplantation. N Engl J Med. 1969;280:735–739.
2. Terasaki PI, Cai J. Human leukocyte antigen antibodies and chronic rejection: from association to causation. Transplantation. 2008;86:377–383.
3. Gebel HM, Bray RA. The evolution and clinical impact of human leukocyte antigen technology. Curr Opin Nephrol Hypertens. 2010;19:598–602.
4. Gebel HM, Bray RA, Nickerson P. Pre-transplant assessment of donor-reactive, HLA-specific antibodies in renal transplantation: contraindication vs. risk. Am J Transplant. 2003;3:1488–1500.
5. Lublin DM, Grumet FC. Mechanisms of the CYNAP phenomenon: evidence in the Bw49/Bw50 model for epitopes with different spatial orientation of antibody. Hum Immunol. 1982;4:137–145.
6. Garovoy MR, Rheinschmilt MA, Bigos M, et al. Flow cytometry analysis: a high technology crossmatch technique facilitating transplantation. Transplant Proc. 1983;15:1939–1944.
7. Bray RA, Lebeck LK, Gebel HM. The flow cytometric crossmatch. Dual-color analysis of T cell and B cell reactivities. Transplantation. 1989;48:834–840.
8. Gebel HM, Bray RA. HLA antibody detection with solid phase assays: great expectations or expectations too great?. Am J Transplant. 2014;14:1964–1975.
9. Amico P, Hönger G, Mayr M, et al. Clinical relevance of pretransplant donor-specific HLA antibodies detected by single-antigen flow-beads. Transplantation. 2009;87:1681–1688.
10. Lefaucheur C, Suberbielle-Boissel C, Hill GS, et al. Clinical relevance of preformed HLA donor-specific antibodies in kidney transplantation. Am J Transplant. 2008;8:324–331.
11. Tait BD, Süsal C, Gebel HM, et al. Consensus guidelines on the testing and clinical management issues associated with HLA and non-HLA antibodies in transplantation. Transplantation. 2013;95:19–47.
12. Wiebe C, Gibson IW, Blydt-Hansen TD, et al. Evolution and clinical pathologic correlations of de novo donor-specific HLA antibody post kidney transplant. Am J Transplant. 2012;12:1157–1167.
13. Cecka JM, Kucheryavaya AY, Reinsmoen NL, et al. Calculated PRA: initial results show benefits for sensitized patients and a reduction in positive crossmatches. Am J Transplant. 2011;11:719–724.
14. Baxter-Lowe LA, Cecka M, Kamoun M, et al. Center-defined unacceptable HLA antigens facilitate transplants for sensitized patients in a multi-center kidney exchange program. Am J Transplant. 2014;14:1592–1598.
15. Taylor CJ, Kosmoliaptsis V, Sharples LD, et al. Ten-year experience of selective omission of the pretransplant crossmatch test in deceased donor kidney transplantation. Transplantation. 2010;89:185–193.
16. Johnson CP, Schiller JJ, Zhu YR, et al. Renal transplantation with final allocation based on the virtual crossmatch. Am J Transplant. 2016;16:1503–1515.
17. Aziz S, Hassantash SA, Nelson K, et al. The clinical significance of flow cytometry crossmatching in heart transplantation. J Heart Lung Transplant. 1998;17:686–692.
18. Badders JL, Jones JA, Jeresano ME, et al. Variable HLA expression on deceased donor lymphocytes: not all crossmatches are created equal. Hum Immunol. 2015;76:795–800.
19. Kwak B, Mulhaupt F, Veillard N, et al. The HMG-CoA reductase inhibitor simvastatin inhibits IFN-gamma induced MHC class II expression in human vascular endothelial cells. Swiss Med Wkly. 2001;131:41–46.
20. Vaidya S, Cooper TY, Avandsalehi J, et al. Improved flow cytometric detection of HLA alloantibodies using pronase: potential implications in renal transplantation. Transplantation. 2001;71:422–428.
21. Bearden CM, Agarwal A, Book BK, et al. Pronase treatment facilitates alloantibody flow cytometric and cytotoxic crossmatching in the presence of rituximab. Hum Immunol. 2004;65:803–809.
22. Hetrick SJ, Schillinger KP, Zachary AA, et al. Impact of pronase on flow cytometric crossmatch outcome. Hum Immunol. 2011;72:330–336.
23. Park H, Lim YM, Han BY, et al. Frequent false-positive reactions in pronase-treated T-cell flow cytometric cross-match tests. Transplant Proc. 2012;44:87–90.
24. Szewczyk K, Barrios K, Magas D, et al. Flow cytometry crossmatch reactivity with pronase-treated T cells induced by non-HLA autoantibodies in human immunodeficiency virus-infected patients. Hum Immunol. 2016;77:449–455.
25. Liwski R, Adams G, Peladeau G, et al. The impact of lymphocyte purity on flow cytometry crossmatch(FCXM) assay. It’s not purely theoretical. Hum Immunol. 2016;77:110–111.
26. Liwski R, Pochinco D, Tinckam K, et al. Going with the flow, Canadian crossmatch standardization. Hum Immunol. 2012;73:28.
27. Liwski R, Pochinco D, Tinckam K, et al. Canada-wide evaluation of rapid optimized flow crossmatch (ROFCXM) protocol. Hum Immunol. 2012;73:26.
28. Bachelet T, Martinez C, Del Bello A, et al. Deleterious impact of donor-specific anti-HLA antibodies toward HLA-Cw and HLA-DP in kidney transplantation. Transplantation. 2016;100:159–166.
29. Przybylowski P, Balogna M, Radovancevic B, et al. The role of flow cytometry-detected IgG and IgM anti-donor antibodies in cardiac allograft recipients. Transplantation. 1999;67:258–262.
30. Gebel HM, Bray RA. Sensitization and sensitivity: defining the unsensitized patient. Transplantation. 2000;69:1370–1374.
31. Reed EF, Rao P, Zhang Z, et al. Comprehensive assessment and standardization of solid phase multiplex-bead arrays for the detection of antibodies to HLA. Am J Transplant. 2013;13:1859–1870.
32. Tambur AR, Herrera ND, Haarberg KM, et al. Assessing antibody strength: comparison of MFI, C1q, and Titer information. Am J Transplant. 2015;15:2421–2430.
33. Zachary AA, Lucas DP, Detrick B, et al. Naturally occurring interference in Luminex assays for HLA-specific antibodies: characteristics and resolution. Hum Immunol. 2009;70:496–501.
34. Kosmoliaptsis V, O'Rourke C, Bradley JA, et al. Improved Luminex-based human leukocyte antigen-specific antibody screening using dithiothreitol-treated sera. Hum Immunol. 2010;71:45–49.
35. Schnaidt M, Weinstock C, Jurisic M, et al. HLA antibody specification using single-antigen beads—a technical solution for the prozone effect. Transplantation. 2011;92:510–515.
36. Visentin J, Vigata M, Daburon S, et al. Deciphering complement interference in anti-human leukocyte antigen antibody detection with flow beads assays. Transplantation. 2014;98:625–631.
37. Schwaiger E, Wahrmann M, Bond G, et al. Complement component C3 activation: the leading cause of the prozone phenomenon affecting HLA antibody detection on single-antigen beads. Transplantation. 2014;97:1279–1285.
38. Gloor JM, Winters JL, Cornell LD, et al. Baseline donor-specific antibody levels and outcomes in positive crossmatch kidney transplantation. Am J Transplant. 2010;10:582–589.
39. El-Awar N, Terasaki PI, Nguyen A, et al. Epitopes of human leukocyte antigen class I antibodies found in sera of normal healthy males and cord blood. Hum Immunol. 2009;70:844–853.
40. Morales-Buenrostro LE, Terasaki PI, Marino-Vázquez LA, et al. “Natural” human leukocyte antigen antibodies found in nonalloimmunized healthy males. Transplantation. 2008;86:1111–1115.
41. Gombos P, Opelz G, Scherer S, et al. Influence of test technique on sensitization status of patients on the kidney transplant waiting list. Am J Transplant. 2013;13:2075–2082.
42. Grenzi PC, de Marco R, Silva RZ, et al. Antibodies against denatured HLA class II molecules detected in luminex-single antigen assay. Hum Immunol. 2013;74:1300–1303.
43. El-Awar NR, Terasaki PI, Hajeer A, et al. A novel HLA Class I single antigen bead preparation eliminates false positive reactions attributed to natural antibodies—in the sera of normal males and pre-transplant patients. Hum Immunol. 2010;71:26.
44. Visentin J, Guidicelli G, Bachelet T, et al. Denatured class I human leukocyte antigen antibodies in sensitized kidney recipients: prevalence, relevance, and impact on organ allocation. Transplantation. 2014;98:738–744.
45. Oaks M, Michel K, Sulemanjee NZ, et al. Practical value of identifying antibodies to cryptic HLA epitopes in cardiac transplantation. J Heart Lung Transplant. 2014;33:713–720.
46. Visentin J, Marroc M, Guidicelli G, et al. Clinical impact of preformed donor-specific denatured class I HLA antibodies after kidney transplantation. Clin Transplant. 2015;29:393–402.
47. Otten HG, Verhaar MC, Borst HP, et al. The significance of pretransplant donor-specific antibodies reactive with intact or denatured human leucocyte antigen in kidney transplantation. Clin Exp Immunol. 2013;173:536–543.
48. Visentin J, Guidicelli G, Moreau JF, et al. Deciphering allogeneic antibody response against native and denatured HLA epitopes in organ transplantation. Eur J Immunol. 2015;45:2111–2121.
Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.