HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Supplemental Data All Versions of this Article: M700194-MCP200v1 7/2/431    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Glossary Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Kim, J. Y. Articles by Lee, S.-w. Search for Related Content PubMed PubMed Citation Articles by Kim, J. Y. Articles by Lee, S.-w. Social Bookmarking                      What's this?

Molecular & Cellular Proteomics 7:431-441, 2008.
© 2008 by The American Society for Biochemistry and Molecular Biology, Inc.

---

Research

Platelet Factor-4 Is an Indicator of Blood Count Recovery in Acute Myeloid Leukemia Patients in Complete Remission^*,S

Jin Young Kim, Ho-Jun Song, Hoi-Jeong Lim^¶, Myung-Geun Shin^||, Jae Seong Kim^**, Hyeoung-Joon Kim, Baik Yoon Kim^** and Seung-won Lee^**,

From the Proteome Analysis Team, Korea Basic Science Institute, Daejeon 305-333, Korea, Departments of Dental Materials and ^¶ Biostatistics, Dental Science Research Institute, Brain Korea 21 Program, Chonnam National University School of Dentistry, Gwangju 501-757, Korea, Departments of ^|| Laboratory Medicine, ^** Anatomy, and Internal Medicine, Genome Research Center for Hematopoietic Diseases, Brain Korea 21 Program, Chonnam National University Medical School, Gwangju 501-746, Korea

	ABSTRACT

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
To investigate whether serum biomarkers can be used to indicate the responsiveness of acute myeloid leukemia to remission induction chemotherapy, we performed MALDI-TOF protein profile analysis of patient sera. The resulting spectra revealed a protein (or peptide) peak at m/z 7764 that varied in intensity; its intensity was much higher in samples from patients in complete remission than in those from patients with resistant disease or in samples taken prior to treatment (at the time of diagnosis). Using fractionation, trypsin digestion, MS/MS, and protein molecular weight analyses, we identified the m/z 7764 protein as platelet factor-4 (PF4). This identification was confirmed by a magnetic bead-based MALDI immunoassay. Statistical comparison of PF4 levels and platelet counts in patient sera revealed a significant positive correlation between the two variables. This study demonstrates that PF4 protein levels are a good indicator for the recovery of blood count in the complete remission of acute myeloid leukemia. The linear positive correlation curve indicates that blood count recovery of platelets to >100,000/mm³ is equivalent to a serum PF4 recovery level of >2.492 µg/ml.

The curability of AML is influenced by many pretreatment factors, including patient age, chromosome abnormality, previous hematological disorder, presenting leukocyte count, and leukemic cell characteristics. In addition to these variables, several treatment factors correlate with prognosis in AML including, most importantly, achievement of complete remission (CR) (1). Combination chemotherapy with N⁴-behenoyl-1-β-D-arabinofuranosylcytosine (BH-AC) and idarubicin is one of the most commonly used CR induction regimens. BH-AC is usually administered as a continuous intravenous infusion at 200–300 mg/m²/day for 7 days; idarubicin is also administered intravenously, usually at 12 mg/m²/day on days 1, 2, and 3 (the "7 and 3" regimen). All-trans-retinoic acid (ATRA) is also used only for remission induction of a subtype (M3) of AML. After induction chemotherapy, both bone marrow and blood are examined to determine whether the leukemia has been eliminated.

Major improvements in the treatment of AML have been achieved over the last 30 years. This improvement has been achieved mainly by an enormous intensification of chemotherapy (2). However, for many AML patients, even the most intense therapy does not prevent a fatal outcome. One of the greatest challenges in the treatment of AML is that of the design of risk-adapted therapies. To achieve this goal, it is essential to identify residual leukemic cells that can cause a relapse and hence necessitate further treatment for the patient. In hematological malignancies, monitoring of minimal residual disease and the defined indicators of CR has become one of the most important diagnostic tools for risk-adapted therapy. However, sensitive and specific markers for CR detection have yet to be identified.

The objective of this study was to investigate whether AML patient serum contains a biochemical marker that reflects the responsiveness of the disease to remission induction chemotherapy. Identification of a biomolecule whose levels are indicative of either CR or treatment-resistant disease (RD) after chemotherapy would provide an important clue to the biological mechanism of the human body's recovery from AML. Our results demonstrate that MALDI-TOF protein profile analysis of bone marrow sera of AML patients after CR induction chemotherapy can differentiate between CR and RD states. Moreover a high intensity peak of m/z 7764 is present in the MS spectra of CR patient sera but absent from the sera of RD patients and from sera previously taken at the time of the AML diagnosis.

	EXPERIMENTAL PROCEDURES

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Patients and Specimens—
The serum specimens used in this study were only from the Genome Research Center for Hematopoietic Diseases of Chonnam National University Hospital, a tertiary care center. Patients who were diagnosed as having AML and underwent chemotherapy for a 1-month period from July 2003 to March 2005 were eligible for collection of bone marrow serum to be archived in the Genome Research Center for Hematopoietic Diseases. Clinical information was obtained by chart review, and all diagnoses were confirmed histologically in the bone marrow biopsy section. At the time of bone marrow and blood collection, all cases provided the informed consent of allowing their postexamination specimen to be used for any further research-only purpose, and the Institutional Review Board on Clinical Investigation reviewed and approved this study. Serum samples were immediately placed on ice for transport to the laboratory where they were centrifuged, aliquoted, and immediately frozen at –80 °C until use.

Postchemotherapy Response Criteria—
A CR designation applies to appropriately treated patients who survived at least 7 days after completion of the final dose of the initial course of treatment and who achieved a morphologic leukemia-free state (5% blasts in an aspirate sample containing marrow spicules and 200 nucleated cells) and had an absolute neutrophil count of >1.000/µl and a platelet count of 100,000/µl. Blasts with Auer rods or persistence of extramedullary disease should not be present (supplemental Fig. 1I). An RD designation applies to appropriately treated patients who survived at least 7 days after completion of the final dose of the initial course of treatment but whose final posttreatment peripheral blood smear and/or bone marrow sample showed persistent AML (supplemental Fig. 1II) (3). In this retrospective study, the patients were divided into two groups, CR and RD, according to their response to idarubicin/BH-AC and ATRA (only for M3 AML) remission induction chemotherapy (Table I). The collection of postchemotherapy bone marrow serum was made at the same time after 1-month chemotherapy for all the AML patients. The evaluation of chemotherapy response (i.e. CR or RD) for AML patients was done at least 7 days later. Of the archived specimens, 26 were from patients in the CR state of AML, and five were from patients in the RD state of AML. Two samples were taken from each patient; the first sampling occurred at the time of diagnosis of AML (PreCR and PreRD samples), and the second occurred immediately after the 1-month remission induction chemotherapy (CR and RD samples).

Protein profiles were acquired with an Ultraflex MALDI-TOF mass spectrometer (Bruker Daltonics) in linear mode with external calibration to the protein calibration standard 1, which contained insulin (m/z 5734.51, M + H), ubiquitin I (m/z 8565.76, M + H), cytochrome c (m/z 12,360.97, M + H), myoglobin (m/z 16,952.30, M + H), cytochrome c (m/z 6180.99, M + 2H), and myoglobin (m/z 8476.65, M + 2H) (Bruker Daltonics). For each target, 30 laser shots at each of seven locations (a total of 210) were accumulated at 16% laser power with 15 matrix blaster shots at each location at 40% laser power. Spectra were collected using peak evaluation values of signal-to-noise ratio = 8, resolution >50, and no smoothing or base-line subtraction.

Spectral Analysis—
To detect and locate spectral peaks, preprocessing steps, including smoothing, base-line correction, peak detection, and peak alignment, were performed using an in-house program. The spectral mass range from 1000 to 20,000 Da was selected for analysis because this range contained the majority of the resolved protein/peptides. The molecular masses from 0 to 1000 Da were eliminated from analysis because the data in this range contain adducts and artifacts of the energy-absorbing molecule and may contain other chemical contaminants. For data smoothing, adjacent data points were averaged to reduce noise. The noise level was relatively high at low mass range, and it decreased as the mass value increased. Therefore, the number of data points comprising each average was selected based on criteria that do not affect the peak intensity; 10 points were used at the initial mass (1000 Da), and the number of points decreased linearly as mass increased; five points were used at the terminal mass (20,000 Da).

Chemical noise is one of the major obstacles in obtaining useful MALDI-MS and MS/MS spectra from small amounts of peptides. This noise is a result of the desorption and ionization of peptides, matrix, and impurities in the sample (4). Base-line correction is performed on a spectrum in isolation to eliminate any base-line signal that can be caused mostly by chemical noise. The optimum base-line curve was made by selecting the minimum level within a selected interval of the spectrum as the base line; as the range of mass values in the intervals increased, the following intervals for selecting a base line were increased serially by 1.2-fold. The initial interval began at m/z 120.

Peaks and valleys of the spectra were detected by applying a slope-based method at 50-data point intervals. Of the detected peaks, those with areas less than the selected threshold value were considered to be noise peaks and were eliminated. Peak areas were calculated by detecting the valleys on both sides of the peak followed by integrating the signal intensity according to a straight line connecting the valleys. Threshold values were applied proportionately with the mass range in one MS spectrum because the peak areas in the high mass range are much larger than those in the low mass range. Optimal threshold values were determined by testing a small set of spectra using different settings. The threshold value of peak area for the initial mass range was set at 1; it increased linearly to 20 at the final mass range. The number of peaks detected per spectrum using the above process was 110. The intensities of the selected peaks were obtained from the raw spectra to quantify the data.

All of the labeled peaks identified in this process were then aligned using an algorithm that grouped peaks with similar molecular weights across all the spectra into a peak cluster while allowing for slight variations in mass. Each cluster was then taken to represent a particular protein. The masses of peaks within each cluster differed by 5 Da, and the entire cluster was considered to represent the same peak. Missing peaks in each peak cluster were filled with the corresponding spectral value.

We used the intensity of the peaks to measure the amount of protein in the sera. Reproducibility can be defined in both spatial (i.e. alignment) and quantitative (i.e. intensity) terms. It is worth noting that the coefficient of variance (CV) for the peak position data using the Ultraflex MALDI-TOF mass spectrometer and similar methods was within 0.05% (Bruker Daltonics). The quantitative reproducibility of the MB-based MALDI spectra (i.e. the variation in peak intensity between measurements) was determined using bone marrow serum from a healthy donor. The reproducibility study was performed by a single person. Moreover the HIC-C₈ beads used were from one batch as were the tube strips, and the same MALDI platform was used to spot the eluted samples. Fifteen protein peaks with the highest amplitude in the range of 1000–20,000 Da, observed on the 96 spectra over the 3-day course of the analysis, were used to calculate the CV. The CV values for peak intensity in the crude data were between 14.33 and 44.12% and averaged 25.19% (data not shown).

Only the peak or peaks for which the spectral intensities indicated a relatively large difference between the two groups were selected by univariate and multivariate statistical analyses (see "Statistical Analysis") as a classifier or biomarker. The peaks for which the spectral intensities indicated a relatively small difference between the two groups were not chosen because the peak intensities of the two groups overlapped due to the similar abundance distribution or the relatively high CV.

Serum Protein Fractionation and Purification—
High abundance proteins such as albumin and IgG were removed from 1 ml of a bone marrow serum (30 µl x 34) using a multiple affinity removal system (MARS; Agilent Technologies, San Diego, CA) according to the manufacturer's protocol. The flow-through fraction was concentrated in a 5000 molecular weight cutoff concentrator and then fractionated by elution from a copper-MB preparation with an MB-IMAC copper kit (Bruker Daltonics). The concentrated copper-purified fractions of protein were then loaded onto a C₈ column of inner diameter 6 mm, length 150 mm, and particle size 5 µm (Shiseido, Tokyo, Japan). The component proteins/peptides were eluted at a flow rate of 0.75 ml/min with 20% acetonitrile for 2 min followed by a gradient of 20–60% acetonitrile over 60 min. Every C₈ fraction was analyzed on an AnchorChip target using an Ultraflex MALDI-TOF mass spectrometer (Bruker Daltonics), and those fractions confirmed by MALDI-TOF-MS to contain a significant majority of the 7.8-kDa peak were pooled. The pool was then split into two identical samples, which were dried by centrifugal evaporation.

Nano-LC/ESI-MS/MS and MS Analysis for 7.8-kDa Protein Identification—
One sample from the duplicate pair was dissolved in digestion buffer containing 100 mM Tris (pH 8.0), 5 mM DTT, 5 mM CaCl₂, and 1 µg of trypsin and incubated at 37 °C for 12–16 h. The resulting peptides were lyophilized and dissolved in 0.1% formic acid for LC-MS/MS. MS/MS experiments for peptide identification were performed using a nano-LC-MS system consisting of an Ultimate HPLC system (Dionex) and a Q-TOF mass spectrometer (Waters) equipped with a nano-ESI source. An autosampler was used to load 10-µl aliquots of the peptide solutions onto a C₁₈ trap column of inner diameter 300 µm, length 5 mm, and particle size 5 µm (Dionex). The peptides were desalted and concentrated on the column at a flow rate of 20 µl/min. Then the trapped peptides were back-flushed and separated on a 100-mm homemade microcapillary column composed of C₁₈ (Aqua; particle size, 5 µm) packed into 75-µm silica tubing with an orifice inner diameter of 8 µm.

The mobile phases, A and B, were composed of 0 and 80% acetonitrile, respectively, each containing 0.1% formic acid. The gradient began with 5% B for 15 min; ramped to 20% B over 3 min, to 60% over 45 min, and to 95% over 2 min; and remained at 95% B for another 7 min. The column was equilibrated with 5% B for 10 min before the next run. The voltage applied to produce an electrospray was 2.5 kV, and the cone voltage was 30 eV. Argon was introduced as a collision gas at a pressure of 10 p.s.i. The three most abundant MS ions were selected by data-dependent peak selection, and the collision energy was stepped up to 30 eV.

For each sample, the MS/MS spectra were processed using MassLynx version 3.5 (Waters); they were smoothed one time using the Savitzky-Golay method set at ±3 channels and centered using the top half of each peak. Peak lists were generated using MassLynx version 3.5 and automatically combined into a single .pkl file.

To identify the peptides, MASCOT (version 2.0, Matrix Science, London, UK), operated on a local server, was used to search the human sequences within the International Protein Index (IPI) database (version 3.32). The human database contains 67,524 protein sequences. MASCOT was used with monoisotopic mass selected, a precursor mass error of 1.5 Da, and a fragment ion mass error of 0.8 Da. Trypsin was selected as the enzyme with one potential missed cleavage. ESI-Q-TOF was selected as the instrument type, and oxidized methionine was chosen as variable modification. Only proteins that were identified by one or more high scoring peptides were considered to be true matches. The high scoring peptides corresponded to peptides that were above the threshold in our MASCOT search (expected, <0.05; peptide score, >38). For peptides that matched with multiple members of a protein family, we selected the protein whose predicted molecular weight was closest to the actual molecular weight measured by MALDI-MS or ESI-MS.

The exact molecular weight of the second sample from the duplicate pair was determined to unambiguously identify the proteins. This second sample was dissolved in water containing 0.1% formic acid without additional preparation. ESI-Q-TOF-MS analysis was performed using this protein sample under the same LC-MS conditions, and the MS spectra were processed using the parameters described above without data-dependent MS/MS acquisition. The MS spectrum was deconvoluted using MassLynx version 3.5.

Magnetic Bead-based MALDI Immunoassay—
Protein G-immobilized MBs (MB-IAC Pro G kit, Bruker Daltonics) can bind the Fc regions of various antibodies. An aliquot (7.2 µg) of purified mouse monoclonal antibody specific for the human platelet factor-4 (PF4) protein (R&D Systems, Minneapolis, MN) in 30 µl of incubation buffer (Bruker Daltonics) was applied to the preactivated protein G beads in a thin walled PCR tube and incubated for 1 h at room temperature. The beads were washed twice with 100 µl of incubation buffer by placing the tube in an MB separator and moving it back and forth 20 times between adjacent wells. The beads were incubated for 2 h on a shaker with 5 µl of serum diluted with 10 µl of binding buffer (Bruker Daltonics), washed two times as above with 100 µl of binding buffer, and finally washed two times with 100 µl of wash solution (Bruker Daltonics).

The protein antigen was eluted by adding 10 µl of elution solution (Bruker Daltonics) to the tube. After thorough mixing, the eluted protein was transferred to a fresh tube. A 1-µl aliquot of the eluted protein was mixed with 10 µl of a matrix solution composed of 0.3 g/liter -cyano-4-hydroxycinnamic acid in 2:1 ethanol:acetone (Bruker Daltonics). One microliter of the diluted sample was spotted onto a 600-µm-diameter AnchorChip target. Protein profiles were acquired using an Ultraflex MALDI-TOF mass spectrometer (Bruker Daltonics) exactly as described above.

ELISA Determination of PF4 Levels—
To confirm that the m/z 7764.8 peak (i.e. PF4), which was discovered by MB-based MALDI protein profiling, is a determinant or biomarker capable of grouping the sera of AML patients, we directly measured the PF4 levels in the serum samples using conventional ELISA with anti-PF4 antibody. Serum levels of PF4 were determined using a sandwich immunoassay according to the manufacturer's recommendations (R&D Systems) with all steps carried out at room temperature. Briefly each well of a 96-well microtiter plate was coated with 100 µl of mouse monoclonal antibody specific for human PF4 (2.0 µg/ml in PBS) and incubated overnight. After three washes with 300 µl of wash buffer (0.05% Tween 20 in PBS, pH 7.4), the well was blocked with 300 µl of reagent diluent (1% BSA in PBS, pH 7.4) for 1 h. Each serum sample was diluted 1:20,000 with reagent diluent, 100 µl of diluted sample were added to each well, and the plate was incubated for 2 h. The wells were washed as described above with wash buffer and then incubated with 100 µl of a biotinylated polyclonal goat antibody specific for human PF4 (100 ng/ml in reagent diluent) for 2 h. The plates were washed again as described above, incubated with 100 µl of horseradish peroxidase-conjugated streptavidin (diluted 1:200 with reagent diluent) for 20 min, and washed three times.

For detection, 100 µl of substrate solution (1:1 H₂O₂:tetramethylbenzidine) were added to each well, and the plate was incubated for 20 min. The color reaction was stopped by addition of 50 µl of stop solution (2 N H₂SO₄) to each well, and the plates were read in a VERSA_max microplate reader (Molecular Devices, Sunnyvale, CA) at 450 nm. Data analysis was performed using SoftMax Pro version 5 software (Molecular Devices). All of the measurements were collected twice, and the detection values (i.e. the PF4 concentrations) are given as the mean.

Statistical Analysis—
All of the statistical computations were performed using statistical analysis system software release 8.2, and all p values reported are two-sided. The Mann-Whitney U test was used to compare the change of MALDI protein peak intensities or P in sera of AML patients (n = 31) who had achieved CR or RD after chemotherapy ( = 0.05). For a total of 110 P values per spectrum, P values were differences in serum protein peak intensities calculated from the intensities after chemotherapy (P_CR or P_RD) and at diagnosis (P_PreCR or P_PreRD) (i.e. P_CR = P_CR – P_PreCR and P_RD = P_RD – P_PreCR).

The major statistical end point in the P analysis was the determination of factors associated with the diagnosis of achieving CR. Factors associated with this outcome were selected based on multivariate logistic regression modeling (5). For the multivariate analysis, a forward selection procedure with the predictor variables left continuous was used to obtain a final model ( = 0.10).

After determining PF4 levels in the individual CR, RD, PreCR, and PreRD samples using ELISA, we performed two-sample comparisons between the PreCR and CR samples and between the PreRD and RD samples. A nonparametric alternative to the paired t test, the Wilcoxon signed ranks test, was used to test the null hypotheses of no median differences between paired observations, PreRD and RD or PreCR and CR.

Linear regression analysis was used to investigate the relationship between platelet count (PLT) and PF4 levels. A graphical residual plot was used to examine the adequacy of both the linear regression model and the homoscedasticity (data not shown). Due to the nonconstancy of the error variance, logarithmic transformations of the two variables were used for a better fit.

	RESULTS

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
Magnetic Bead-based MALDI Analysis of Serum Proteins—
A panel of 62 bone marrow serum samples (Table I) was assayed with C₈ MBs. Of these samples, 26 (designated CR) were from AML patients who had achieved the CR state as a result of 1-month remission induction chemotherapy with idarubicin/BH-AC or ATRA. Another 26 serum samples (designated PreCR) were from the same patients but had been taken previously at the time of diagnosis (1 month prior to the chemotherapy); five serum samples (designated RD) were from AML patients who had not achieved the CR state after remission induction chemotherapy, exhibiting instead the RD state; and the remaining five samples (designated PreRD) were from the RD patients at diagnosis (supplemental Fig. 1).

We obtained MS spectra of these 62 samples using the AnchorChip MALDI technique for detection of serum proteins/peptides with -cyano-4-hydroxycinnamic acid as the matrix. We used an in-house algorithm to detect and align protein peaks. Up to 110 aligned peaks (or peak clusters) per spectrum were detected between M_r 1000 and 20,000.

Using a significance level of 5%, the Mann-Whitney U test selected 10 P values (i.e. the MALDI protein peak intensity difference: after-chemo intensity minus before-chemo intensity) variables (3882.6/p = 0.0056, 4208.8/p = 0.0168, 4458.9/p = 0.0467, 4646.7/p = 0.0099, 4708.1/p = 0.0386, 6631.9/p = 0.0362, 7764.8/p = 0.0014, 8814.9/p = 0.0440, 8921.0/p = 0.0499, and 9290.6/p = 0.0473) displaying the highly significant difference in its distribution in the CR group compared with the RD group. Then multivariate logistic regression analysis with the 10 selected variables revealed that the only significant predictor was 7764.8 (Table II). In the multivariate analysis, the odds ratio (OR) computed with the predictor variable being left continuous for the risk of being a CR responder was 11.688 (95% confidence interval, 0.773–176.775). In fact, the OR 11.688 was computed for an increase of 1 unit of the 7764.8 level. Because this may not be easily interpretable, we again computed the OR for a change from the 10th percentile (=–0.2) to the 60th percentile (= 5.1) of the predictor variable as a way to compare subjects in the middle of the 20th percentile of the distribution (considering the smaller RD group; n = 5) with those in the middle of the remaining 80th percentile of the distribution (considering the larger CR group; n = 26). Thus, the computed OR for this change was 456,151 (Table II). The odds of a subject being a CR was 456,151 times higher with a value of 5.1 than with a value of –0.2. (i.e. with an increase of 7764.8 from –0.2 to 5.1, the odds of a subject being a CR increased by 456,151 times).

View this table: [in this window] [in a new window]   TABLE II Multivariate logistic regression analysis of the continuous variable 7764.8 7764.8 levels are differences in serum protein peak intensities on the MS spectra calculated from the intensities after chemotherapy (7764.8CR or 7764.8RD) and at diagnosis (7764.8PreCR or 7764.8PreRD) (i.e. 7764.8CR = 7764.8CR – 7764.8PreCR and 7764.8RD = 7764.8RD – 7764.8PreRD). The Hosmer and Lemeshow goodness of fit is 2 = 0.5621, p = 0.9897. The estimated regression coefficient is β = 2.4586. OR for the risk of being a CR responder is computed for an increase of 1 unit of 7764.8 level. CI, confidence interval.

View larger version (56K): [in this window] [in a new window]   FIG. 1. Composite MALDI spectra of the four sample groups (A and B) and their individual gel views (C) of a peak at m/z 7764.8. PreCR and PreRD depict the states at diagnosis of patients who achieved a CR or who exhibited RD, respectively. A, composite (averaged) MALDI spectra of PreCR, PreRD, CR, and RD sera. MALDI-MS resolved 110 peaks between m/z 1000 and 10,000. B, composite (averaged) MALDI spectra of PreCR, PreRD, CR, and RD sera between m/z 7500 and 8500. Compared with the PreCR, PreRD, and RD samples, the CR samples overexpressed a protein at m/z 7764.8. C, contour plot of individual spectra between 7500 and 8500. The high intensity band at m/z 7764.8 was found only in CR samples.

Among the three proteins, the predicted molecular weight of PF4, except for the signal peptide from platelet factor-4 precursor, was very similar to the value found by MALDI-MS. PF4 was identified from the tryptic peptide ICLDLQAPLYK with a MASCOT search score of 55 and 16% sequence coverage. The MS and MS/MS spectra of the peptide are shown in Fig. 2.

View larger version (15K): [in this window] [in a new window]   FIG. 2. A, MS and MS/MS spectra of the tryptic peptide ICLDLQAPLYK from PF4. After MARS depletion, copper-bead preparation, and C8 reverse-phase chromatography, the partially purified protein was subjected to tryptic in-liquid digestion followed by nano-LC-ESI/MS/MS. B, ESI-MS (panel A) and deconvoluted MS (panel B) spectra of the non-digested PF4 protein.

Although PF4 was matched by the tryptic peptide (ICLDLQAPLYK) with a high search score, the identification was based on a single peptide assignment. To unambiguously identify the protein, we performed LC-ESI/Q-TOF-MS analysis to determine its exact molecular weight. The average molecular mass of the protein was 7764.98 ± 0.13 Da (Fig. 2B), which is about 4 Da lower than the theoretical value (7769.21 Da, estimated from the sequence of PF4). When we consider the two disulfide bonds (at Cys-10 and Cys-36 for one and at Cys-12 and Cys-52 for the other) (ca.expasy.org/uniprot/P02776) in human PF4, its average molecular mass becomes 7765.18 Da. This is consistent with the molecular weight determined for the intact protein by ESI-MS and MALDI-MS (the m/z 7764.8 ion; supplemental Table II). These results confirm the identity of human PF4.

In this molecular weight data analysis of intact protein, we additionally found a few peaks with small intensities at m/z 7836.63, 7923.00, and 8141.13 (Fig. 2B, panel B). Struyf et al. (7) reported several N-terminally processed isoforms of a platelet factor 4 variant (PF4V, UniProt accession number P10720) and PF4 in thrombin-stimulated human platelets. Based on the report by Struyf et al. (7) and our molecular weight data on intact proteins, the small peaks are thought to be N-terminally processed isoforms of PF4 (supplemental Table III). Interestingly their appearance pattern between tested sample groups is almost identical to that of PF4 (Fig. 1B). All the N-terminally modified peaks including PF4 show the relatively increased signal only in the CR group. However, except for PF4, the intensity change between groups was not very evident. This finding regarding the PF4 isoforms more strongly supports the argument that the 7.8-kDa protein is PF4.

Confirmation of the Identification of the m/z 7764.8 Protein as PF4 by MB-based MALDI Immunoassay—
To confirm that the 7764.8-Da protein was PF4, we used an MB-based MALDI immunoassay with a specific anti-PF4 antibody to analyze four samples; two of the samples were CR sera containing the 7764.8-Da peak, one sample was a RD serum that yielded no 7764.8-Da peak upon C₈ chromatography/MB, and the fourth sample was a control containing only 1% BSA blocking agent (Fig. 3). Both 7764.8-Da peak-containing CR samples yielded a specific peak of mass 7.8 kDa upon anti-PF4 antibody coated MB (positive control). This peak was detected neither in the RD sample nor in the BSA control sample (negative control).

View larger version (15K): [in this window] [in a new window]   FIG. 3. Representative examples of MB-based MALDI immunoassay spectra showing PF4 protein in two complete remission samples (CR1 and CR2). These samples had yielded a 7764.8-Da peak upon AnchorChip MALDI analysis with C8 beads. A peak corresponding to PF4 was not present in the serum (RD) of a patient whose disease was resistant to the remission induction chemotherapy or when the anti-PF4 antibody was incubated with only 1% BSA (No serum). Intens., intensity; a.u., arbitrary units.

View larger version (35K): [in this window] [in a new window]   FIG. 4. Box plots of the PF4 protein serum level (µg/ml) in sera from patients in various disease states. PreCR and PreRD are samples taken prior to treatment (at the time of AML diagnosis) from patients who had achieved CR or who had RD, respectively.

Correlation between PF4 Levels and Platelet Counts in AML Patient Sera—
We next sought to determine whether PF4 levels had any statistical relationship with platelet counts (Table III). To achieve this goal, we compared PF4 levels and platelet counts in the CR and RD samples (Fig. 5), which exhibit a relatively wide range of serum levels, as compared with the PreCR and PreRD samples. Logarithmic transformation of each variable yielded the following linear regression model.

(Eq. 1)

This model is indicative of a positive linear correlation between lnPF4 and lnPLT (p = 0.000). Furthermore the value of R², the coefficient of determination, was 0.861, indicating that 86% of the observed variability in the response (lnPF4) was modeled by lnPLT.

View larger version (9K): [in this window] [in a new window]   FIG. 5. Statistical relationship between the logarithms of platelet count (ln_PLT; 103/mm3) and PF4 serum level (ln_PF4; µg/ml). We compared platelet counts and PF4 levels in the CR and RD samples, which exhibit a relatively wide range of serum levels compared with the PreCR and PreRD samples. The coefficient of determination was R2 = 0.861. For a platelet count of 100 x 103/mm3, the amount of PF4 derived from the curve of the positive linear correlation was 2.492 µg/ml.

(Eq. 2)

	DISCUSSION

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 
AML describes a heterogeneous group of clonal hematopoietic progenitor cell disorders with a spectrum of morphologic, immunophenotypic, cytogenetic, and molecular characteristics (3). Although diagnosis may be possible based solely on a peripheral blood examination, a bone marrow aspiration is strongly recommended. Bone marrow trephine biopsy is not routinely indicated, although it may be necessary if the aspirate is dilute, hypocellular, or inaspirable. The French-American-British (FAB) classification for diagnosis in AML was based initially on morphology, cellularity, blast percentage, and cytochemistry (8). A subsequent update and modification of the FAB diagnostic criteria by the World Health Organization (WHO) (9) instituted a major change in the diagnostic threshold for the AML blast percentage in the peripheral blood or bone marrow aspirate. The WHO recommendations decreased this threshold to 20% from the 30% level recommended by the FAB. Thereafter new recommendations of the International Working Group for diagnosis and standardization criteria in AML were published in 1990 and recently revised (3). This group of investigators used the cytochemical and phenotypic criteria of the WHO (9, 10) and emphasized the prognostic relevance of bone marrow cytogenetics (11–13) and molecular genetics (14, 15). They also recommended new criteria for variable responses to the currently available therapy in AML.

According to the International Working Group criteria, a morphologic CR designation requires that the patient survive for at least 7 days after the final dose of the initial course of treatment and achieve a morphologic leukemia-free state (5% blasts in an aspirate sample containing marrow spicules and 200 nucleated cells) and have an absolute neutrophil count of >1.000/µl and a platelet count of 100,000/µl. The criteria for treatment failure due to RD includes appropriately treated patients who survive for at least 7 days after the final dose of the initial course of treatment and whose last posttreatment peripheral blood smear and/or bone marrow sample showed persistent AML. It includes those patients for whom treatment has failed to achieve CR in a phase III trial or failed to achieve at least a partial remission (5–25% blasts, neutrophils >1.000/µl, and platelets 100,000/µl) in a phase I or II trial. In the present study, CR samples included cases from patients who fulfilled the major requirements of minimal blast count (i.e. <5% blasts in an aspirate sample) and blood count recovery (i.e. neutrophils of 1.000/µl and platelets of 100,000/µl). However, the RD samples included cases from patients who had succeeded in achieving neither minimal blast count nor blood count recovery (i.e. 5% blasts in an aspirate sample, neutrophils of <1.000/µl, and platelets of <100,000/µl).

Thus, to analyze the MALDI-TOF protein profiles from the CR and RD groups of serum samples we performed a multiple logistic regression analysis. We found that for the 7764.8-Da protein, the odds of a subject being a CR responder are 456,151 times higher for a change of 5.1 than for a change of –0.2. Moreover we found that only one variable (i.e. the 7764.8-Da protein) was significantly different between the two groups. Given that the patients have been subjected to chemotherapy in between the sampling times, one would expect many real changes or biomarker candidates. As mentioned under "Spectral Analysis," although the spatial (i.e. alignment) reproducibility of MALDI-TOF protein peaks was excellent (CV values within 0.05%), the quantitative (i.e. intensity) reproducibility of the MALDI-TOF protein peaks was not very good (CV values between 14.33 and 44.12%). In actuality, almost all commercially available MALDI-TOF instruments to date are known to have a similar reproducibility. On the other hand, serum proteins being expressed differentially between groups may be biomarker candidates only if the protein profiling platform can detect the minimal change of protein amount. However, the peaks for which the spectral intensities between the two groups overlapped due to the high CVs, even though their real values are separated statistically, will not be chosen as being significant. Consequently considering the relatively high CV of MALDI protein peak intensities, any protein peaks for which the difference in peak intensity exists but was not so large between the two groups were not selected by the present logistic analysis. In addition, in this study, we enrolled 26 CR but only five RD cases for 21 months (from July 2003 to March 2005) due to the very low incidence of AML. We think that it is necessary to perform another validation step in a new cohort of patients especially with a large sample size of RD patients.

The 7764.8-Da protein was purified by several steps of HPLC/bead separation and identified using nano-LC-MS/MS and MB-based MALDI immunoassay. This protein proved to be a monomer of tetrameric PF4. To investigate the origin of the difference in the calculated values of PF_CR and PF_RD, we determined the PF4 levels in the individual CR, RD, PreCR, and PreRD samples using ELISA. The results of two-sample comparisons between the PreCR and CR samples and between the PreRD and RD samples showed that PF4 was present only at a minimum level in both the PreRD and RD samples, whereas the high PF_CR value originated primarily from the relatively high PF4 level in the CR sample as compared with the same minimum PF4 level found in the PreCR sample.

PF4, also known as CXCL4 (chemokine (CXC motif) ligand 4), was originally described as a platelet-derived heparin-neutralizing factor (16). PF4 is synthesized entirely in megakaryocytes and, to a lesser extent, in mature platelets, and is stored in platelet -granules. It accounts for 25% of the protein in the platelet granule. When platelets are activated, PF4 is released along with other protein components of the platelet -granules. PF4 levels in plasma are 2–10 ng/ml, whereas they are 5–10 µg/ml in serum prepared by provoking thrombin-mediated platelet aggregation and coagulation (16). The human PF4 monomer is a 7800-Da protein of 70 amino acids (17). NMR studies have shown that PF4 in solution exists in a concentration-dependent equilibrium of monomers, dimers, and tetramers (18).

Unlike other CXC chemokines, such as IL-8, which typically mediate chemotaxis of neutrophils, PF4 is devoid of chemotactic activity for neutrophils (19). It has recently been proposed that some vascular beds in humans express an alternatively spliced form of CXCR3, termed CXCR3B, that binds PF4 (20). PF4 binds with high affinity to heparin and other anionic glycosaminoglycans (21, 22), and the PF4 tetramer has an equatorial band of cationic charges that attracts heparin molecules (23). Upon its release from activated platelets, PF4 binds to proteoglycans on the surfaces of endothelial cells (24), platelet membranes (25), and hepatocytes (26). It has been implicated in diverse biological processes; its suggested roles include those of a procoagulant of platelet function and plasmatic coagulation (16), an inhibitor of hematopoiesis (27, 28) and angiogenesis (29, 30), a promoter of neutrophil adhesion and degranulation (31), an enhancer of oxidized low density lipoprotein binding to the low density lipoprotein receptor (32), and a stimulator of anticoagulant-activated protein C generation (33). These effects have been observed only at high PF4 concentrations (5–25 µg/ml), which can be achieved at the site of intense platelet activation (6).

Statistical comparison of the PF4 levels and platelet counts in sera from the 31 AML patients (CR and RD) revealed a significant positive correlation between the PF4 level and the platelet count. The PF4 level corresponding to a platelet count of 100,000/mm³, as derived from the positive linear correlation curve, was 2.492 µg/ml. Therefore, one of the three requirements for the designation of complete remission, a blood platelet count recovery of >100,000/mm³, might be equivalent to a serum PF4 level recovery of >2.492 µg/ml. The morphology of platelets and other blood cells frequently changes after chemotherapy, and thus even a blood cell counter would not reflect the correct measurement of blood cell counts. In this situation, the serum PF4 assay might be a good alternative for assessing blood cell recovery. In addition, the serum PF4 level can be determined simply by a conventional ELISA method. Considering that a good alternative for assessing platelet count does not exist, serum PF4 measurement seems to provide a cost-effective means of yielding information on the status of hematopoietic recovery in an AML patient after chemotherapy.

In conclusion, we have demonstrated, using an MB-based MALDI profiling technology, that serum PF4 levels in AML patients return to or are elevated above the normal level in patients achieving CR, whereas in RD patients, levels were unchanged or decreased below the normal level. In fact, PF4 was shown to be a good indicator for the recovery of blood count in the complete remission of AML.

	ACKNOWLEDGMENTS

 
We thank In-Seong Wo and Sun-Ho Lee for help in preparing the manuscript, Bo Yoon Jeong for help in statistical analysis, Dr. Il-Kwon Lee for help in specimen collection, Dr. Jae-Hak Moon for advice on HPLC purification, and Dr. Jong Shin Yoo at Korea Basic Science Institute for technical support in MS analysis.

	FOOTNOTES

 
Received, May 1, 2007, and in revised form, October 1, 2007.

Published, MCP Papers in Press, November 12, 2007, DOI 10.1074/mcp.M700194-MCP200

¹ The abbreviations used are: AML, acute myeloid leukemia; CR, complete remission; RD, resistant disease; PF, platelet factor; BH-AC, N⁴-behenoyl-1-β-D-arabinofuranosylcytosine; ATRA, all-trans-retinoic acid; MB, magnetic bead; CV, coefficient of variance; PLT, platelet count; OR, odds ratio; MARS, multiple affinity removal system; IQR, interquartile range; FAB, French-American-British; WHO, World Health Organization; MB-HIC, magnetic beads-based hydrophobic interaction chromatography.

^* This work was supported by Grants 01-PJ10-PG6-01GN16-0005 and A030003 from the Korean Health 21 Research and Development Project, Ministry of Health and Welfare, Republic of Korea.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

^S The on-line version of this article (available at http://www.mcponline.org) contains supplemental material.

To whom correspondence should be addressed: Dept. of Anatomy, Chonnam National University Medical School, 5 Hakdong, Donggu, Gwangju 501-746, Korea. E-mail: seunglee{at}chonnam.ac.kr

	REFERENCES

TOP ABSTRACT EXPERIMENTAL PROCEDURES RESULTS DISCUSSION REFERENCES

 

1. Kasper, D. L., Braunwald, E., Fauci, A. S., Hauser, S. L., Longo, D. L., and Jameson, J. L. (2004 ) Harrison's Principles of Internal Medicine , pp. 631 –641, McGraw-Hill, Columbus, OH

2. Ravindranath, Y. (2003 ) Recent advances in pediatric acute lymphoblastic and myeloid leukemia. Curr. Opin. Oncol. 15, 23 –35[CrossRef][Medline]

3. Cheson, B. D., Bennett, J. M., Kopecky, K. J., Buchner, T., Willman, C. L., Estey, E. H., Schiffer, C. A., Doehner, H., Tallman, M. S., Lister, T. A., Lo-Coco, F., Willemze, R., Biondi, A., Hiddemann, W., Larson, R. A., Lowenberg, B., Sanz, M. A., Head, D. R., Ohno, R., and Bloomfield, C. D.; International Working Group for Diagnosis, Standardization of Response Criteria, Treatment Outcomes, and Reporting Standards for Therapeutic Trials in Acute Myeloid Leukemia (2003 ) Revised recommendations of the International Working Group for Diagnosis, Standardization of Response Criteria, Treatment Outcomes, and Reporting Standards for Therapeutic Trials in Acute Myeloid Leukemia. J. Clin. Oncol. 21, 4642 –4649[Abstract/Free Full Text]

4. Krutchinsky, A. N., and Chait, B. T. (2002 ) On the nature of the chemical noise in MALDI mass spectra. J. Am. Soc. Mass Spectrom. 13, 129 –134[CrossRef][Medline]

5. Hilario, M., Kalousis, A., Pellegrini, C., and Muller, M. (2006 ) Processing and classification of protein mass spectra. Mass Spectrom. Rev. 25, 409 –449[CrossRef][Medline]

6. Kaplan, K. L., Broekman, M. J., Chernoff, A., Lesznik, G. R., and Drillings, M. (1979 ) Platelet alpha-granule proteins: studies on release and subcellular localization. Blood 53, 604 –618[Free Full Text]

7. Struyf, S., Burdick, M. D., Proost, P., Damme, J. V., and Strieter, R. M. (2004 ) Platelet release CXCL4L1, a nonallelic variant of the chemokine platelet factor-4/CXCL4 and potent inhibitor of angiogenesis. Circ. Res. 95, 855 –857[Abstract/Free Full Text]

8. Bennett, J. M., Catovsky, D., Daniel, M. T., Flandrin, G., Galton, D. A., Gralnick, H. R., and Sultan, C. (1976 ) Proposals for the classification of the acute leukaemias: French-American-British (FAB) Co-Operative Group. Br. J. Haematol. 33, 451 –458[Medline]

9. Vardiman, J., Harris, N. L., and Brunning, R. D. (2002 ) The World Health Organization (WHO) classification of the myeloid neoplasms. Blood 100, 2292 –2302[Abstract/Free Full Text]

10. Harris, N. L., Jaffe, E. S., Diebold, J., Flandrin, G., Muller-Hermelink, H. K., Vardiman, J., Lister, T. A., and Bloomfield, C. D. (1999 ) World Health Organization classification of neoplastic diseases of the hematopoietic and lymphoid tissues: report of the Clinical Advisory Committee meeting-Airlie House, Virginia. J. Clin. Oncol. 17, 3835 –3849[Abstract/Free Full Text]

11. Whitman, S. P., Archer, K. J., Feng, L., Baldus, C., Becknell, L. B., Carlson, B. D., Carroll, A. J., Mrozek, K., Vardiman, J. W., George, S. L., Kolitz, J. E., Larson, R. A., Bloomfield, C. D., and Caligiuri, M. A. (2001 ) Absence of the wild-type allele predicts poor prognosis in adult de novo acute myeloid leukemia with normal cytogenetics and the internal tandem duplication of FLT3: a cancer and leukemia group B study. Cancer Res. 61, 7233 –7239[Abstract/Free Full Text]

12. Thiede, C., Steudel, C., Mohr, B., Schaich, M., Schakel, U., Platzbecker, U., Wermke, M., Bornhauser, M., Ritter, M., Neubauer, A., Ehninger, G., and Illmer, T. (2002 ) Analysis of FLT3-activating mutations in 979 patients with acute myelogenous leukemia: association with FAB subtypes and identification of subgroups with poor prognosis. Blood 99, 4326 –4335[Abstract/Free Full Text]

13. Frohling, S., Schlenk, R. F., Breitruck, J., Benner, A., Kreitmeier, S., Tobis, K., Dohner, H., and Dohner, K. (2002 ) Prognostic significance of activating FLT3 mutations in younger adults (16 to 60 years) with acute myeloid leukemia and normal cytogenetics: a study of the AML Study Group Ulm. Blood 100, 4372 –4380[Abstract/Free Full Text]

14. Dohner, K., Tobis, K., Ulrich, R., Frohling, S., Benner, A., Schlenk, R. F., and Dohner, H. (2002 ) Prognostic significance of partial tandem duplications of the MLL gene in adult patients 16 to 60 years old with acute myeloid leukemia and normal cytogenetics: a study of the Acute Myeloid Leukemia Study Group Ulm. J. Clin. Oncol. 20, 3254 –3261[Abstract/Free Full Text]

15. Caligiuri, M. A., Strout, M. P., Lawrence, D., Arthur, D. C., Baer, M. R., Yu, F., Knuutila, S., Mrozek, K., Oberkircher, A. R., Marcucci, G., de la Chapelle, A., Elonen, E., Block, A. W., Rao, P. N., Herzig, G. P., Powell, B. L., Ruutu, T., Schiffer, C. A., and Bloomfield, C. D. (1998 ) Rearrangement of ALL1 (MLL) in acute myeloid leukemia with normal cytogenetics. Cancer Res. 58, 55 –59[Abstract/Free Full Text]

16. Zucker, M. B., and Katz, I. R. (1991 ) Platelet factor 4: production, structure, and physiologic and immunologic action. Proc. Soc. Exp. Biol. Med. 198, 693 –702[CrossRef][Medline]

17. Deuel, T. F., Keim, P. S., Farmer, M., and Heinrikson, R. L. (1977 ) Amino acid sequence of human platelet factor 4. Proc. Soc. Exp. Biol. Med. 74, 2256 –2258

18. Mayo, K., and Chen, M. J. (1989 ) Human platelet factor 4 monomer-dimer-tetramer equilibria investigated by 1H NMR spectroscopy. Biochemistry 28, 9469 –9478[CrossRef][Medline]

19. Clark-Lewis, I., Dewald, B., Geiser, T., Moser, B., and Baggiolini, M. (1993 ) Platelet factor 4 binds to interleukin 8 receptors and activates neutrophils when its N terminus is modified with Glu-Leu-Arg. Proc. Natl. Acad. Sci. U. S. A. 90, 3574 –3577[Abstract/Free Full Text]

20. Lasagni, L., Francalanci, M., Annunziato, F., Lazzeri, E., Giannini, S., Cosmi, L., Sagrinati, C., Mazzinghi, B., Orlando, C., Maggi, E., Marra, F., Romagnani, S., Serio, M., and Romagnani, P. (2003 ) An alternatively spliced variant of CXCR3 mediates the inhibition of endothelial cell growth induced by IP-10, Mig, and I-TAC, and acts as functional receptor for platelet factor 4. J. Exp. Med. 197, 1537 –1549[Abstract/Free Full Text]

21. Stringer, S. E., and Gallagher, J. T. (1997 ) Specific binding of the chemokine platelet factor 4 to heparan sulfate. J. Biol. Chem. 272, 20508 –20514[Abstract/Free Full Text]

22. Stuckey, J. A., St. Charles, R., and Edwards, B. F. (1992 ) A model of the platelet factor 4 complex with heparin. Proteins 14, 277 –287[CrossRef][Medline]

23. Zhang, X., Chen, L., Bancroft, D. P., Lai, C. K., and Maione, T. E. (1994 ) Crystal structure of recombinant human platelet factor 4. Biochemistry 33, 8361 –8366[CrossRef][Medline]

24. Rybak, M. E., Gimbrone, M. A., Davies, P. F., and Handin, R. I. (1989 ) Interaction of platelet factor four with cultured vascular endothelial cells. Blood 73, 1534 –1539[Abstract/Free Full Text]

25. Capitanio, A. M., Niewiarowski, S., Rucinski, B., Tuszynski, G. P., Cierniewski, C. S., Hershock, D., and Kornecki, E. (1985 ) Interaction of platelet factor 4 with human platelets. Biochim. Biophys. Acta 839, 161 –173[Medline]

26. Rucinski, B., Stewart, G. J., De Feo, P. A., Boden, G., and Niewiarowski, S. (1987 ) Uptake and processing of human platelet factor 4 by hepatocytes. Proc. Soc. Exp. Biol. Med. 186, 361 –367[CrossRef][Medline]

27. Han, Z. C., Zhang, X. J., Xi, X. D., Lu, M., Jiang, S., Jiang, L. Z., Wang, X. M., Gu, G. L., and Caen, J. P. (1995 ) Platelet factor 4 acts as both inhibitor and protector of hematopoietic precursor cells: possible mechanism of action. Shi Yan Sheng Wu Xue Bao 28, 415 –426[Medline]

28. Gewirtz, A. M., Zhang, J., Ratajczak, J., Ratajczak, M., Park, K. S., Li, C., Yan, Z., and Poncz, M. (1995 ) Chemokine regulation of human megakaryocytopoiesis. Blood 86, 2559 –2567[Abstract/Free Full Text]

29. Gengrinovitch, S., Greenberg, S. M., Cohen, T., Gitay-Goren, H., Rockwell, P., Maione, T. E., Levi, B. Z., and Neufeld, G. (1995 ) Platelet factor-4 inhibits the mitogenic activity of VEGF121 and VEGF165 using several concurrent mechanisms. J. Biol. Chem. 270, 15059 –15065[Abstract/Free Full Text]

30. Sharpe, R. J., Byers, H. R., Scott, C. F., Bauer, S. I., and Maione, T. E. (1990 ) Growth inhibition of murine melanoma and human colon carcinoma by recombinant human platelet factor 4. J. Natl. Cancer Inst. 82, 848 –853[Abstract/Free Full Text]

31. Kasper, B., Brandt, E., Bulfone-Paus, S., and Peterson, F. (2004 ) Platelet factor 4 (PF-4)-induced neutrophil adhesion is controlled by src-kinases, whereas PF-4-mediated exocytosis requires the additional activation of p38 MAP kinase and phosphatidylinositol 3-kinase. Blood 103, 1602 –1610[Abstract/Free Full Text]

32. Nassar, T., Sachais, B. S., Akkawi, S., Kowalska, M. A., Bdeir, K., Leitersdorf, E., Hess, E., Ziporen, L., Aviram, M., Cines, D., Poncz, M., and Higazi, A. A. (2003 ) Platelet factor 4 enhances the binding of oxidized low-density lipoprotein to vascular wall cells. J. Exp. Med. 278, 6187 –6193

33. Slungaard, A., and Key, N. S. (1994 ) Platelet factor 4 stimulates thrombomodulin protein C-activating cofactor activity. A structure-function analysis. J. Exp. Med. 269, 25549 –25556

CiteULike

Complore

Connotea

Del.icio.us

Digg

Reddit

Technorati

This article has been cited by other articles:

				Z. Huang, Y. Shi, B. Cai, L. Wang, Y. Wu, B. Ying, L. Qin, C. Hu, and Y. Li MALDI-TOF MS combined with magnetic beads for detecting serum protein biomarkers and establishment of boosting decision tree model for diagnosis of systemic lupus erythematosus Rheumatology, June 1, 2009; 48(6): 626 - 631. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Supplemental Data All Versions of this Article: M700194-MCP200v1 7/2/431    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Glossary Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Kim, J. Y. Articles by Lee, S.-w. Search for Related Content PubMed PubMed Citation Articles by Kim, J. Y. Articles by Lee, S.-w. Social Bookmarking                      What's this?