Cord Blood Stem Cells

Identification of molecular markers for pre-engraftment immune reactions after cord blood transplantation by SELDI-TOF MS

Abstract

Cord blood transplantation (CBT) is frequently associated with pre-engraftment immune reaction (PIR), which is characterized by high-grade fever that peaks around day 9 of transplantation. PIR mimics hyperacute GVHD or engraftment syndrome; however, it is considered to be of different etiology as it occurs before engraftment. Proteomic patterns have been studied in the fields of transplantation, but no specific marker has been identified. As there are no data to confirm the mechanism of PIR, we used a surface-enhanced laser desorption/ionization time-of-flight mass spectroscopy (SELDI-TOF MS) system to identify a specific marker for PIR. The protein expression profile of serum samples from CBT patients was analyzed with a SELDI-TOF MS system. A protein peak that commonly predominated in PIR was purified by an anion exchange column, isolated by SDS-PAGE, and identified by in-gel trypsin digestion, and mass fingerprinting. A 8.6-kDa protein and 11-kDa protein that increased by 10- to 100-fold in the serum of patients during PIR was identified as anaphylatoxin C4a and serum amyloid A. SELDI-TOF MS system in combination with other proteomic methods could serve as a potential diagnostic tool in discovering biomarkers for PIR after CBT.

Introduction

High-grade fever before engraftment without any other obvious signs of infection, which mimics hyperacute GVHD or engraftment syndrome, is frequently observed in patients who undergo cord blood transplantation (CBT).1, 2 In previous reports, when patients with no evidenceof infection or adverse effects of medication exhibited skin eruption, diarrhea, jaundice or body weight gain greater than 10% of baseline, these conditions were defined as ‘immune reactions.’ These reactions were classified as ‘pre-engraftment immune reaction (PIR)’ if they developed 6 or more days before engraftment, whereas those within 5 days of engraftment were defined as ‘engraftment syndrome’ (1). The reported incidence of PIR has ranged from 78–83% (1–2). This PIR peaks at around day 9 of CBT, and is often accompanied by high-grade fever. Although PIR responds well to corticosteroid therapy, the prolonged use of steroid often causes an increased incidence of infectious complications, leading to significant treatment-related mortality, particularly in the elderly. GVHD prophylaxis with tacrolimus, compared with CsA, is less likely to be associated with PIR3, 4 and the addition of MTX may further reduce the risk.5, 6 It has been speculated that cytokines induced by the initial immune/inflammation reaction are the primary cause of PIR, but no data are available to confirm this supposition. To clarify this question, we evaluated the protein expression profile of serum in CBT recipients using a surface-enhanced laser desorption/ionization time-of-flight mass spectroscopy (SELDI-TOF MS) system and found potential markers for PIR.

Materials and methods

Study patients and samples

Patients who received treatment for hematological malignancies at the National Cancer Center Hospital or Toranomon Hospital between February 2002 and May 2005 were included in this study. The study was approved by the Ethics Committee, and written informed consent was given by all patients. A total of 78 peripheral blood samples taken from 57 patients, including 34 samples taken from 13 patients who had undergone allogeneic CBT, were eligible for the analysis. Samples from CBT patients were taken on three different occasions, that is, (1) afebrile period before PIR onset: the median of day 3 (1–6) post transplant; (2) onset of fever: the median of day 8 (6–13); and (3) after resolution of fever: the median of day 26.5 (15–60). To analyze the protein profile that was specific to PIR, samples taken from patients with documented infection or those who were suffering from engraftment syndrome were excluded from the analysis. All 13 CBT patients received reduced-intensity conditioning, and graft rejection occurred in 2 patients (16%). As for the treatment and its outcome for PIR, six patients responded well to corticosteroid and seven patients improved without any treatment or empiric antibiotics alone. One of the patients who developed graft failure received corticosteroids for the treatment of PIR. The mean neutrophil count at PIR was 15 (0–100)/μl. The patients' characteristics are shown in Table 1.

Table 1 Characteristics of 13 patients

SELDI-TOF MS analysis

The relative protein expression levels were determined as previously described with the following modifications using a SELDI TOF-MS system (Bio-Rad Laboratories, Hercules, CA, USA).7, 8 The protein was processed using a Biomek 2000 Laboratory Work Station (Beckman Coulter, Fullerton, CA, USA). Samples were analyzed in duplicate and 28 spectra were obtained from five serum fractions with four kinds of chips (IMAC30, CM10, H50, Q10), four different binding buffers, two kinds of energy absorption molecules and two focus mass ranges.

Serum fractionation

The serum samples were centrifuged at 20 000 × g and the supernatant was vigorously mixed with denaturation buffer U9 (9 M urea: 2% CHAPS: 50 mM Tris-HCl, pH9) for 20 min. Serum samples were fractionated into four fractions by the following methods. Briefly, the strong anion exchange resin BioSepra Q Ceramic HyperD F (Pall, NY, USA) was equilibrated with 50 mM Tris-HCl, pH 9, in advance, and 180 μl per well was loaded onto a filter plate. The loaded resin was equilibrated three times with 200 μl of U1 buffer (U9 buffer diluted 1:10 with 50 mM Tris-HCl). Denatured serum was added to the resin, the sample well was washed with 50 μl of U1 buffer, and the sample was incubated for 30 min at 4 °C. The non-binding fraction was collected, and protein was eluted by a phased pH gradient at pH 5.8, pH 4 and below pH 4.

Protein binding

IMAC30 (immobilized metal affinity capture), CM10 (cation exchange), H50 (reverse-phase) and Q10 (anion exchange) ProteinChip arrays were used for the analysis. To immobilize copper ion on the IMAC30 surface, each spot was incubated with 50 μl of 100 mM copper sulfate for 10 min at room temperature. Excess copper was removed by washing twice with distilled water and incubated with 50 μl of 100 mM sodium acetate (pH 4) for 5 min at room temperature. Each spot was rinsed twice with distilled water before the analysis step.

The following buffers were used for binding and dilution of the samples: 100 mM sodium acetate (pH 4) or 50 mM HEPES (pH 7) for CM10, 100 mM sodium phosphate (pH 7)+0.5 M NaCl for IMAC30, 50 mM HEPES (pH 7) for H50, and 50 mM Tris-HCl (pH 8) for Q10. The following procedure was commonly used for all chip analyses: (1) Each spot was equilibrated twice with 150 μl of binding buffer on a shaker for 5 min, and excess buffer was removed. (2) The fractionated and unfractionated samples were diluted 10-fold with binding buffer. The diluted samples were loaded onto a chip, and incubated on a shaker for 30 min at room temperature. (3) The chip was washed three times on a shaker for 5 min with 150 μl per spot of buffer. (4) The chip was rinsed twice with 200 μl of distilled water and dried. (5) Each spot was treated with two kinds of energy absorption molecules: 50% saturated sinapinic acid and α-cyano-4-hydroxycinnamic acid.

Protein detection

Captured proteins were detected using a ProteinChip SELDI system (PCS4000 Enterprise, Bio-Rad Laboratories). The maximum detection range was 100 000 with a focus mass range of 3000–10 000 for low MW, and 200 000 with a focus mass range of 10 000–30 000 for high MW. Quantitative analysis of proteins was performed using ProteinChip Software version 3.2 and ProteinChip Data Manager Software (Bio-Rad Laboratories).

Protein purification and identification

The serum samples were denatured with urea and fractionated by an anion exchange column (ProteinChip Q Spin Columns, Bio-Rad Laboratories) to remove albumin by binding it to the column. The fraction that passed through the anion exchange column at pH 9 was collected. The sample was diluted threefold with 50 mM Tris-HCl (pH 8) and loaded onto an anion exchange column to bind the objective peak protein. The protein was eluted in a phased manner with 50–300 mM NaCl. After demineralization and concentration, the proteins were separated by SDS-PAGE and stained with Coomassie Brilliant Blue. In-gel digestion by Trypsin was performed on the objective band. The protein was determined by mass fingerprinting of the digested peaks against the ProFound database (Rockefeller University edition), and the amino-acid sequence was determined using the PCI-QSTAR MS/MS search engine.

Statistical analysis

Data were analyzed using ProteinChip Data Manager Software. After baseline correction, MW calibration was performed using eight standard protein molecules followed by a total ion current normalization process. To identify distinct and significant peaks, we used a signal-to-noise cutoff of 2 (s/n>2), which selects peaks with a signal level that is significantly above the calculated background noise.

For the statistical analysis, the Kruskal–Wallis H-test was used to compare differences among three groups. The differences between the two groups were compared with the Wilcoxon–Mann–Whitney U-test. Probabilities of P<0.05 were defined as statistically significant.

Results

Protein profiles

A total of 3005 protein peaks for which s/n >2 were detected. Of these, 743 showed a significant difference between the febrile and afebrile periods. After we further excluded noise peaks, 469 peaks still showed a significant difference, and after excluding variations between individuals, 19 candidate peaks that were commonly elevated at PIR in more than 11 patients (84.6%) were selected. Reproducibility was tested, and six protein peaks that commonly increased at the time of PIR, with molecular masses of 8611, 8642, 11452, 11512, 11539 and 11669 Da, were identified (Figure 1). The assay conditions under which the proteins were identified are shown in Table 2.

Figure 1
figure1

(a) Peak intensity levels of six protein peaks that commonly increased at the time of PIR. (b) Typical response pattern of the 11-kDa protein peak in 13 patients, in a trace view.

Table 2 Assay conditions by which marker proteins were detected

Purification and determination of target proteins

Protein peaks were fractionated by an anion exchange column, and the elution fraction at pH 9 was used for purification and identification because the albumin that overlaps the candidate peak was removed from this fraction. The protein was eluted from the column with 100–150 mM NaCl. SDS-PAGE after demineralization and concentration of the protein showed an 11-kDa band (Figure 2a). In-gel digestion was performed on the cutout band, and mass fingerprinting was performed for eight peptides with mass values of 1455, 1463, 1550, 1611, 1670, 1706, 1941 and 2097 (Figure 2b). Six of these values were consistent with serum amyloid A (SAA), which consists of 104 amino acids and has a MW of 11 622, or its isoforms, in which serine and/or arginine is deleted from the N-terminal portion (Figure 3). The amino-acid sequences of all six peptide masses were consistent with SAA by MS/MS analysis.

Figure 2
figure2

Representative data of SDS-PAGE and peptide mass fingerprinting from the sample taken during PIR. (a) SDS-PAGE showing the 11-kDa band. Coomassie Brilliant Blue (CBB) staining. (b) Peptide mass fingerprinting of the marker protein.

Figure 3
figure3

(a) Amino-acid sequences of the target protein. Six peptide sequences that matched an MS/MS database search were identical to amino acids of SAA. (b) The analyzed peak was determined to be SAA and its isoform produced by the deletion of serine and/or arginine from the N terminus.

The SAA level was measured by ELISA in the same sample that was assessed by SELDI-TOF MS. The mean SAA level measured by ELISA before fever onset was 14 (3–51) μg/ml, and this increased to 883 (40–2470) μg/ml at the time of PIR and decreased to 45 (8–126) μg/ml after resolution of the fever (Figure 4a). The data obtained by ELISA agreed with the SELDI-TOF MS peak intensity value (Figure 4b). Although the 8.6 kDa peak was not determined in this experiment, it was most likely to be anaphylatoxin C4a based on its MW (8650) and isoelectric point (9.45).

Figure 4
figure4

SAA level measured by ELISA. (a) SAA level in different conditions: Before fever, during PIR and after fever resolution in 13 CBT recipients. Documented infection including sepsis, tumor fever, drug-induced fever, GVHD in related allo-PBSCT (r-PBSCT) and GVHD in unrelated BMT (u-BMT). (b) The data obtained by ELISA correlated well with the SELDI-TOF MS peak intensity value (n=34).

Serum amyloid A value in different conditions

Seven of the 13 patients with PIR developed acute GVHD, and 2 patients had graft failure. The patients who developed graft failure showed high levels of SAA at PIR (2040 and 2390 μg/ml). The mean and median values of SAA at PIR in seven patients who developed acute GVHD were 677 μg/ml and 451 (60–2470) μg/ml, respectively, which were not significantly different from the values in the four patients without acute GVHD (432 and 506 (40–675) μg/ml) (P=0.93).

The SAA value was assessed in 24 non-transplant febrile patients: (a) 12 samples from patients with documented infection, including sepsis, (b) 6 samples from patients with tumor fever and (c) 6 samples from patients with drug-induced fever. The mean and median values and statistical significance when compared with PIR were (a) 477 μg/ml and 347 (31–1240) μg/ml (P=0.63), (b) 432 μg/ml and 248 (127–1080) μg/ml (P=0.75) and (c) 49 μg/ml and 42 (31–73) μg/ml (P=0.0013), respectively.

The SAA values during acute GVHD in other transplantation settings were assessed in 20 patients: (d) 10 samples from related allo-PBSCT recipients including 5 febrile patients and (e) 10 samples from unrelated BMT recipients including 4 febrile patients. The mean and median values and statistical significance when compared with PIR were (d) 293 and 238 (19–645) μg/ml (P=0.20) and (e) 366 and 344 (31–724) μg/ml (P=0.31), respectively (Figure 4a). The level of SAA elevation was not as high as that in PIR, but the sample size was too small to show specificity.

Discussion

Proteomic analysis has been widely used to assess the allogeneic response, including GVHD in hematopoietic SCT.8, 9, 10, 11 The two most important methods that are used to investigate biomarkers, for example, detection of early GVHD, are SELDI-TOF MS and capillary zone electrophoresis mass spectrometry (CE-MS). Although the resolution and sensitivity of SELDI-TOF MS are not as high as those of CE-MS, it has the benefits of relatively low cost and ease of use.9 It has been reported that proteomic pattern analysis by SELDI-TOF MS can be used to accurately distinguish GVHD samples from post transplant non-GVHD samples and pretransplant samples with 100% specificity and 100% sensitivity.8 Furthermore, with the CE-MS system, 16 polypeptide patterns excreted in the urine could be used to discriminate patients with GVHD from patients without complications, with 82% specificity and 100% sensitivity. In addition, 13 sepsis-specific polypeptides could be used to distinguish sepsis from GVHD, with a specificity of 97% and a sensitivity of 100%.10 The diagnosis of acute GVHD, even before a clinical diagnosis, is possible with the use of a GVHD-specific model consisting of 31 polypeptides.11

Proteomic analysis has also been applied to the analysis of an allograft response in organ transplantation in animal models.12, 13 In a mouse skin transplant model, several protein biomarker candidates were detected by ProteinChip technology based on their molecular mass, which could be used to clearly differentiate between rejection and nonrejection groups, before a clinical manifestation.12 In a rat small bowel transplantation model, two migration inhibitory factor-related proteins and lysozyme that increased during allograft rejection were identified by a SELDI-TOF MS system.13 Thus, we believe that ProteinChip technology should be a useful tool for identifying specific markers related to PIR.

Previous studies have shown that combinations of several biomarkers are more sensitive and accurate than the use of a single marker in the diagnosis of an allogeneic response.11 However, most biomarkers are not well characterized and can only be detected by the ProteinChip system. As the ProteinChip system is not routinely available in clinical practice, we thought it would be necessary to identify a marker that could be monitored easily. In this study, SAA was identified as a candidate marker for PIR. Furthermore, this study showed the feasibility of quantitative analysis by the ProteinChip system, although the ProteinChip system has previously been considered to be a tool for semiquantitative analysis.

Serum biomarkers associated with leukemia14 and cancer15, 16, 17, 18, 19, 20, 21 have also been identified by the SELDI ProteinChip technique. In some of these studies, SAA has been reported to be a potential marker for particular cancer status. Multiple variants of SAA have been detected by the SELDI ProteinChip technique in renal cancer patients.20 The SELDI ProteinChip technique revealed that SAA may be a biomarker for identifying prostate cancer patients with bone lesions, with a sensitivity and specificity of 89.5%.21

SAA activates human mast cells, which leads to the degradation of SAA and the generation of an amyloidogenic SAA fragment.22 SAA is a major acute-phase reactant that increases by as much as 1000-fold during inflammation. SAA is potentially involved in the pathogenesis of several chronic inflammatory diseases: it is the precursor of amyloid A protein deposited in amyloid A amyloidosis, and has also been implicated in the pathogenesis of atherosclerosis and rheumatoid arthritis.23, 24 SAA may be closely related to poor patient outcomes, including left ventricular systolic dysfunction, cardiac rupture and mortality in acute myocardial infarction.25, 26

Some studies have suggested that the elevation of SAA may be associated with acute allograft rejection of the kidney,27, 28, 29, 30 liver31 and heart.32 By contrast, it has also been reported that SAA is inadequate for predicting acute rejection in cardiac allograft.33 With regard to renal allograft rejection, SAA was shown to be a sensitive marker that rose above 100 mg/l in all cases of rejection, whereas C-reactive protein (CRP) showed little or no response to rejection.29 We could not confirm whether or not the elevation of SAA was a phenomenon that occurs with all CBT around day 9, as the value of SAA in samples from non-febrile patients at this time point was not analyzed. However, it is unlikely that the elevation of SAA occurs with all allogeneic transplantation, as the phenomenon was not prominent in patients with acute GVHD. The possibility that the elevation of SAA was only a consequence of acute phase change that occurs with high-grade fever could not be completely ruled out, as the elevation of SAA was not confined to CBT; however, the elevation level was higher in PIR than in other conditions. Furthermore, patients who developed graft rejection had markedly higher levels of SAA. Although the reason for these observations is unclear, a previous report on SAA as an indication of allograft rejection has suggested that inflammation and cytokine production induced by an allo-reaction may be related to the elevation of SAA in PIR.

In the case of CBT, SAA that increases in relation to PIR, as a factor associated with a poor prognosis of CBT, may be related to allograft rejection. Our retrospective study showed that pre-engraftment CRP values may predict acute GVHD and nonrelapse mortality.34 Although CRP elevation was also observed during PIR, SAA elevation was more rapid and prominent. The SAA level was above the normal limit in all 13 samples at the day of fever onset, whereas 2 samples were within the normal limit for CRP. The mean SAA level was 121 times the upper normal limit at day 2 of fever onset, whereas the mean CRP level was 10 times the upper normal limit at the same time. SAA or anaphylatoxin C4a alone may lack specificity as a marker for PIR. However, the further analysis of samples obtained from CBT recipients by our method may provide fingerprints of markers useful for the diagnosis of PIR. Identification of peak markers suggests that the SELDI-TOF MS system in combination with other proteomic methods could serve as a potential diagnostic tool in discovering biomarkers for PIR after CBT.

References

  1. 1

    Kishi Y, Kami M, Miyakoshi S, Kanda Y, Murashige N, Teshima T et al. Early immune reaction after reduced-intensity cord-blood transplantation for adult patients. Transplantation 2005; 80: 34–40.

  2. 2

    Miyakoshi S, Yuji K, Kami M, Kusumi E, Kishi Y, Kobayashi K et al. Successful engraftment after reduced-intensity umbilical cord blood transplantation for adult patients with advanced hematological diseases. Clin Cancer Res 2004; 10: 3586–3592.

  3. 3

    Uchida N, Wake A, Takagi S, Yamamoto H, Kato D, Matsuhashi Y et al. Umbilical cord blood transplantation after reduced-intensity conditioning for elderly patients with hematologic diseases. Biol Blood Marrow Transplant 2008; 14: 583–590.

  4. 4

    Takahashi S, Iseki T, Ooi J, Tomonari A, Takasugi K, Shimohakamada Y et al. Single-institute comparative analysis of unrelated bone marrow transplantation and cord blood transplantation for adult patients with hematologic malignancies. Blood 2004; 104: 3813–3820.

  5. 5

    Narimatsu H, Terakura S, Matsuo K, Oba T, Uchida T, Iida H et al. Short-term methotrexate could reduce early immune reactions and improve outcomes in umbilical cord blood transplantation for adults. Bone Marrow Transplant 2007; 39: 31–39.

  6. 6

    Mori T, Aisa Y, Nakazato T, Yamazaki R, Shimizu T, Mihara A et al. Tacrolimus and methotrexate for the prophylaxis of graft-versus-host disease after unrelated donor cord blood transplantation for adult patients with hematologic malignancies. Transplant Proc 2007; 39: 1615–1619.

  7. 7

    Heike Y, Hosokawa M, Osumi S, Fujii D, Aogi K, Takigawa N et al. Identification of serum proteins related to adverse effects induced by docetaxel infusion from protein expression profiles of serum using SELDI ProteinChip system. Anticancer Res 2005; 25: 1197–1203.

  8. 8

    Srinivasan R, Daniels J, Fusaro V, Lundqvist A, Killian JK, Geho D et al. Accurate diagnosis of acute graft-versus-host disease using serum proteomic pattern analysis. Exp Hematol 2006; 34: 796–801.

  9. 9

    Weissinger EM, Mischak H, Ganser A, Hertenstein B . Value of proteomics applied to the follow-up in stem cell transplantation. Ann Hematol 2006; 85: 205–211.

  10. 10

    Kaiser T, Kamal H, Rank A, Kolb HJ, Holler E, Ganser A et al. Proteomics applied to the clinical follow-up of patients after allogeneic hematopoietic stem cell transplantation. Blood 2004; 104: 340–349.

  11. 11

    Weissinger EM, Schiffer E, Hertenstein B, Ferrara JL, Holler E, Stadler M et al. Proteomic patterns predict acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation. Blood 2007; 109: 5511–5519.

  12. 12

    El Essawy B, Otu HH, Choy B, Zheng XX, Libermann TA, Strom TB . Proteomic analysis of the allograft response. Transplantation 2006; 82: 267–274.

  13. 13

    Yamayoshi Y, Watanabe T, Tanabe M, Hoshino K, Matsumoto K, Morikawa Y et al. Novel application of ProteinChip technology exploring acute rejection markers of rat small bowel transplantation. Transplantation 2006; 82: 320–326.

  14. 14

    Albitar M, Potts SJ, Giles FJ, O'Brien S, Keating M, Thomas D et al. Proteomic-based prediction of clinical behavior in adult acute lymphoblastic leukemia. Cancer 2006; 106: 1587–1594.

  15. 15

    Koopmann J, Zhang Z, White N, Rosenzweig J, Fedarko N, Jagannath S et al. Serum diagnosis of pancreatic adenocarcinoma using surface-enhanced laser desorption and ionization mass spectrometry. Clin Cancer Res 2004; 10: 860–868.

  16. 16

    Wong YF, Cheung TH, Lo KW, Wang VW, Chan CS, Ng TB et al. Protein profiling of cervical cancer by protein-biochips: proteomic scoring to discriminate cervical cancer from normal cervix. Cancer Lett 2004; 211: 227–234.

  17. 17

    Yang SY, Xiao XY, Zhang WG, Zhang LJ, Zhang W, Zhou B et al. Application of serum SELDI proteomic patterns in diagnosis of lung cancer. BMC Cancer 2005; 5: 83.

  18. 18

    Ward DG, Suggett N, Cheng Y, Wei W, Johnson H, Billingham LJ et al. Identification of serum biomarkers for colon cancer by proteomic analysis. Br J Cancer 2006; 94: 1898–1905.

  19. 19

    Malik G, Ward MD, Gupta SK, Trosset MW, Grizzle WE, Adam BL et al. Serum levels of an isoform of apolipoprotein A-II as a potential marker for prostate cancer. Clin Cancer Res 2005; 11: 1073–1085.

  20. 20

    Tolson J, Bogumil R, Brunst E, Beck H, Elsner R, Humeny A et al. Serum protein profiling by SELDI mass spectrometry: detection of multiple variants of serum amyloid alpha in renal cancer patients. Lab Invest 2004; 84: 845–856.

  21. 21

    Le L, Chi K, Tyldesley S, Flibotte S, Diamond DL, Kuzyk MA et al. Identification of serum amyloid A as a biomarker to distinguish prostate cancer patients with bone lesions. Clin Chem 2005; 51: 695–707.

  22. 22

    Niemi K, Baumann MH, Kovanen PT, Eklund KK . Serum amyloid A (SAA) activates human mast cells which leads into degradation of SAA and generation of an amyloidogenic SAA fragment. Biochim Biophys Acta 2006; 1762: 424–430.

  23. 23

    Uhlar CM, Whitehead AS . Serum amyloid A, the major vertebrate acute-phase reactant. Eur J Biochem 1999; 265: 501–523.

  24. 24

    Salazar A, Pinto X, Mana J . Serum amyloid A and high-density lipoprotein cholesterol: serum markers of inflammation in sarcoidosis and other systemic disorders. Eur J Clin Invest 2001; 31: 1070–1077.

  25. 25

    Katayama T, Nakashima H, Takagi C, Honda Y, Suzuki S, Iwasaki Y et al. Serum amyloid a protein as a predictor of cardiac rupture in acute myocardial infarction patients following primary coronary angioplasty. Circ J 2006; 70: 530–535.

  26. 26

    Katayama T, Nakashima H, Honda Y, Suzuki S, Yamamoto T, Iwasaki Y et al. The relationship between acute phase serum amyloid A (SAA) protein concentrations and left ventricular systolic function in acute myocardial infarction patients treated with primary coronary angioplasty. Int Heart J 2007; 48: 45–55.

  27. 27

    Muller TF, Trosch F, Ebel H, Grussner RW, Feiber H, Goke B et al. Pancreas-specific protein (PASP), serum amyloid A (SAA), and neopterin (NEOP) in the diagnosis of rejection after simultaneous pancreas and kidney transplantation. Transpl Int 1997; 10: 185–191.

  28. 28

    Maury CP, Teppo AM, Ahonen J, von Willebrand E . Measurement of serum amyloid A protein concentrations as test of renal allograft rejection in patients with initially non-functioning grafts. Br Med J (Clin Res Ed) 1984; 288: 360–361.

  29. 29

    Hartmann A, Eide TC, Fauchald P, Bentdal O, Herbert J, Gallimore JR et al. Serum amyloid A protein is a clinically useful indicator of acute renal allograft rejection. Nephrol Dial Transplant 1997; 12: 161–166.

  30. 30

    Fukuda Y, Hoshino S, Tanaka I, Yoneya T, Takeshita T, Sumimoto R et al. Examination of serum amyloid A protein in kidney transplant patients. Transplant Proc 2000; 32: 1796–1798.

  31. 31

    Feussner G, Stech C, Dobmeyer J, Schaefer H, Otto G, Ziegler R . Serum amyloid A protein (SAA): a marker for liver allograft rejection in humans. Clin Investig 1994; 72: 1007–1011.

  32. 32

    Muller TF, Vogl M, Neumann MC, Lange H, Grimm M, Muller MM . Noninvasive monitoring using serum amyloid A and serum neopterin in cardiac transplantation. Clin Chim Acta 1998; 276: 63–74.

  33. 33

    Vermes E, Kirsch M, Farrokhi T, Loisance D, Fanen P, Zimmermann R . Serum amyloid A protein: not a relevant marker for recognition of cardiac allograft rejection. Transplantation 2004; 78: 950–951.

  34. 34

    Fuji S, Kim SW, Fukuda T, Mori S, Yamasaki S, Morita-Hoshi Y et al. Preengraftment serum C-reactive protein (CRP) value may predict acute graft-versus-host disease and nonrelapse mortality after allogeneic hematopoietic stem cell transplantation. Biol Blood Marrow Transplant 2008; 14: 510–517.

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Acknowledgements

This work was supported in part by grants from the Ministry of Health, Labor and Welfare, Japan.

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Correspondence to Y Heike.

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The authors declare no conflict of interest.

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Morita-Hoshi, Y., Mori, S., Soeda, A. et al. Identification of molecular markers for pre-engraftment immune reactions after cord blood transplantation by SELDI-TOF MS. Bone Marrow Transplant 45, 1594–1601 (2010). https://doi.org/10.1038/bmt.2010.18

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Keywords

  • serum amyloid A
  • pre-engraftment immune reactions
  • cord blood transplantation
  • SELDI-TOF MS

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