Serum proteome profiling detects myelodysplastic syndromes and identifies CXC chemokine ligands 4 and 7 as markers for advanced disease

Abstract

Myelodysplastic syndromes (MDS) are among the most frequent hematologic malignancies. Patients have a short survival and often progress to acute myeloid leukemia. The diagnosis of MDS can be difficult; there is a paucity of molecular markers, and the pathophysiology is largely unknown. Therefore, we conducted a multicenter study investigating whether serum proteome profiling may serve as a noninvasive platform to discover novel molecular markers for MDS. We generated serum proteome profiles from 218 individuals by MS and identified a profile that distinguishes MDS from non-MDS cytopenias in a learning sample set. This profile was validated by testing its ability to predict MDS in a first independent validation set and a second, prospectively collected, independent validation set run 5 months apart. Accuracy was 80.5% in the first and 79.0% in the second validation set. Peptide mass fingerprinting and quadrupole TOF MS identified two differential proteins: CXC chemokine ligands 4 (CXCL4) and 7 (CXCL7), both of which had significantly decreased serum levels in MDS, as confirmed with independent antibody assays. Western blot analyses of platelet lysates for these two platelet-derived molecules revealed a lack of CXCL4 and CXCL7 in MDS. Subtype analyses revealed that these two proteins have decreased serum levels in advanced MDS, suggesting the possibility of a concerted disturbance of transcription or translation of these chemokines in advanced MDS.biomarker ͉ chemokine ͉ proteomics ͉ hematologic malignancy

Identification of disease- and therapy-associated proteome changes in the sera of patients with myelodysplastic syndromes and del(5q)

“…We are aware of the limitations of this technique and would suggest testing this model with more independent samples. Proteomic profiling of serum samples from patients with MDS using ProteinChip technology was previously carried out by Aivado et al 37 Although the overall aim to identify disease-associated serum proteome changes was the same, there were major differences between this and our study in samples and methodology. First, our study focused specifically on a group of patients with del(5q), whereas the previous study included patients with all MDS subtypes.…”

“…PF-4 is a chemokine released from the a-granules of activated platelet and it has been identified as potential toxicity-or disease-associated markers. [37][38][39] This protein showed a 29% decrease in peak intensity and an 11% decrease in concentration in diseased samples. Another interesting finding of our study was that PF-4 concentrations were not different between the responders and the non-responders before lenalidomide treatment, but were significantly different after treatment.…”

Going from genes to proteins in myelodysplastic syndromes

“…More closely related to the present work by Aivado et al (5), several studies investigating MDS reported downregulation of genes regulating megakaryocyte proliferation and platelet activity, i.e., PF4 (platelet factor 4, also called CXC chemokine ligand 4, CXCL4) and CD41b (platelet glycoprotein IIb) (12)(13)(14). Expression of genes involved in actin cytoskeleton maintenance and, intriguingly, megakaryocyte/platelet-associated genes were up-regulated in patients with del(5q), with PF4V1 being the most differentially expressed gene (14).…”

“…What is the value of the paper by Aivado et al (5), published in this issue of PNAS, for our understanding of MDS? By generating serum proteome profiles in a large group of MDS patients and controls, Aivado et al for the first time demonstrate that concentrations of the chemokines CXCL4 and CXCL7, but not other peptides, are selectively decreased in serum from MDS patients.…”

Proteomic Identification of Interleukin-2 Therapy Response in Metastatic Renal Cell Cancer

“…While SELDI appears to be more sensitive in the low-mass range, which holds valuable information for biomarker discovery, SELDI by itself cannot identify protein IDs. Nevertheless, we have previously developed and validated a robotic approach to determine protein profiles with high reproducibility by SELDI-TOF MS 11,12 . In the current study our objective was to detect a protein profile that distinguishes between IL-2 treatment responders and nonresponders among metastatic RCC patients using SELDI TOF-MS.…”