12th Congress of the European Hematology ... - Haematologica

Genomics and proteomics
0158
PLASMA PROTEOMIC PROFILES MAY PREDICT EARLY ACUTE GRAFT-VS.-HOST DISEASE
FOLLOWING REDUCED INTENSITY CONDITIONING ALLOGENEIC HLA-IDENTICAL SIBLING
TRANSPLANTATION
M. Mohty, 1 M. Mohty, 2 A. Goncalves, 2 E. Esterni, 2 Y. Toiron, 2
B. Gaugler, 2 C. Faucher, 2 J. El-Cheikh, 2 S. Furst, 2 J.A. Gastaut, 2 P. Viens, 2
D. Olive, 2 C. Chabannon, 2 J.P. Borg, 2 D. Blaise2 1 2 Imperial College, LONDON, United Kingdom, Institut Paoli-Calmettes,
MARSEILLES, France
Background. Modern approaches to predict the occurrence/severity of
aGVHD are needed. Aims. This study aimed to identify a plasma protein
signature correlating with occurrence of early aGVHD. Methods. We performed
Surface-Enhanced Laser Desorption/Ionization time (SELDI) of
flight mass spectrometry profiling of plasma from 88 pts who received
RIC allo-SCT from HLA-identical siblings. Results. Median age of pts
was 51 (range, 18-70) y. 41 pts (47%) had a myeloid malignancy, whereas
30 (34%) had a lymphoid malignancy. 17 pts (19%) were treated for
metastatic non-hematological malignancies. The RIC regimen included
fludarabine, busulfan and ATG in 53 pts (60%) and low dose irradiation
in 35 pts (40%). With a median FU of 400 (range, 127-829) d, 20 pts
(23%) had early (prior to day 35 after allo-SCT) grade 2-4 acute GVHD
(12 grade 2 and 8 grade 3-4). Denatured plasma samples (collected at a
median of 28 d.) were incubated with H50 and CM10 ProteinChip arrays
and subjected to SELDI analysis. Pts population was divided into a training
(n=59) and a validation set (n=29). In the training set, 36 protein
peaks were differentially expressed according to early aGVHD occurrence.
By combining partial least squares and logistic regression methods,
we built a multiprotein model that correctly predicted outcome in
96% of pts (14/14 patients with early aGVHD; specificity, 96%). The
observed correct prediction rate in the validation set was 69% with a
sensitivity of 67%, and a specificity of 70%. While negative predictive
value of the model was only 36%, predictive positive value was estimated
to 89% in the validation set. The performances of the model remained
very similar after iterative (500 times) random resampling (correct prediction
rate: 74%, median sensitivity: 48%, median specificity: validation
set: 83%). Univariate and multivariate analyses of known risk factors
(demographic features, diagnoses and transplant procedures) for
early grade 2-4 aGVHD did not show any statistically significant difference
between the group of 20 patients who had early grade 2-4 aGVHD
as compared to the remaining patients, and suggested that the multiprotein
index is likely to be the only independent prognostic parameter.
Major components of this multiprotein index are currently being characterized
and will be presented. Conclusions. Obviously, larger prospective
studies are still needed, but our results already suggest that proteomic
analysis of plasma will prove increasingly important in the early
and clinical diagnosis of aGVHD.
0159
PROTEOME PROFILING IDENTIFIES APOLIPOPROTEIN A1 AS A SERUM MARKER
CORRELATED TO JAK2 V617F BURDEN IN POLYCYTHEMIA VERA AT DIAGNOSIS
P. Mossuz, 1 A. Bouamrani, 2 S. Brugière, 3 M. Arlotto, 2 S. Hermouet, 4
E. Lippert, 5 F. Laporte, 1 F. Girodon, 6 I. Dobo, 7 V. Praloran,5 J. Garin, 3
J.Y. Cahn, 1 F. Berger1 1 CHU Grenoble, GRENOBLE; 2 INSERM U318, GRENOBLE; 3 CEA, UNIT-
M 201, GRENOBLE; 4 CHU Nantes, NANTES; 5 CHU Bordeaux, BOR-
DEAUX; 6 CHU Dijon, DIJON; 7 CHU Angers, ANGERS, France
Background. Polycythemia Vera (PV) is a myeloproliferative disorder
(MPD) originating from a multipotent haematopoietic progenitor cell.
The great majority of PV are characterized by a recurrent acquired gainof-function
mutation of the JAK2 protein (JAK2-V617F). Modifications of
JAK2-V617F burden are associated with changes of PV phenotype and
probably impact on the risk of complications. However, we don’t know
whether if the proportion of JAK2-V617F allele modifies certain serum
proteins. Aims. The purpose of our study was to generate serum proteome
profiles of PV patients to discover and identify novel serum protein
correlated with the levels of granulocyte JAK2-V617F. Methods. PV
serums were collected in a multicenter study and were randomly affected
in two independent learning and validation sets. Proteome profiles
were generated by SELDI-TOF mass spectrometry. JAK2 V617F status
was determined by quantitative-PCR analysis of purified granulocytes.
12 th Congress of the European Hematology Association
Results. Unsupervised clustering analysis of the learning set showed that
PV patients could be separated in two major subgroups tending to be different
with respect to the mean percentage of mutated JAK2 (p=0.09), the
number of PRV-1 transcripts (p=0.08) and Ht (p=0.09). Comparative analysis
of proteome profiles found significant difference (p grade
II) and samples (n=50) of 23 patients without aGvHD. The application
of the aGvHD specific pattern and calculated model allowed correct classification
of blinded and prospectively collected urine samples with high
accuracy: The model enabled the diagnosis of aGvHD > grade II with a
sensitivity of more than 83% [95% CI 73.1 to 87.9]). High resolution proteome
analysis with diagnostic peptide patterns may help to identify
patients at risk of severe aGvHD development prior to clinical features
(mean: 7 days, range: 1 to 13 days prior to clinical symptoms) in an unbiased
laboratory based screening assay. Other patterns (bacterial infection/septicaemia,
CMV and EBV reactivation and infection) will be
shown. Application of proteomic based patterns may lead to the establishment
of a diagnostic tool suitable for pre-emptive therapy of aGvHD
based on proteomic patterns.
haematologica/the hematology journal | 2007; 92(s1) | 57