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BioMed Research International
Volume 2015, Article ID 872983, 17 pages
http://dx.doi.org/10.1155/2015/872983
Research Article

Peripheral Blood Mononuclear Cell Proteome Changes in Patients with Myelodysplastic Syndrome

Institute of Hematology and Blood Transfusion, U Nemocnice 1, 128 20 Prague 2, Czech Republic

Received 23 September 2014; Accepted 31 March 2015

Academic Editor: Shivani Soni

Copyright © 2015 Klara Pecankova et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Our aim was to search for proteome changes in peripheral blood mononuclear cells (PBMCs) of MDS patients with refractory cytopenia with multilineage dysplasia. PBMCs were isolated from a total of 12 blood samples using a Histopaque-1077 solution. The proteins were fractioned, separated by 2D SDS-PAGE (pI 4–7), and double-stained. The proteomes were compared and statistically processed with Progenesis SameSpots; then proteins were identified by nano-LC-MS/MS. Protein functional association and expression profiles were analyzed using the EnrichNet application and Progenesis SameSpots hierarchical clustering software, respectively. By comparing the cytosolic, membrane, and nuclear fractions of the two groups, 178 significantly (, ANOVA) differing spots were found, corresponding to 139 unique proteins. Data mining of the Reactome and KEGG databases using EnrichNet highlighted the possible involvement of the identified protein alterations in apoptosis, proteasome protein degradation, heat shock protein action, and signal transduction. Western blot analysis revealed underexpression of vinculin and advanced fragmentation of fermitin-3 in MDS patients. To the best of our knowledge, this is the first time that proteome changes have been identified in the mononuclear cells of MDS patients. Vinculin and fermitin-3, the proteins involved in cell adhesion and integrin signaling, have been shown to be dysregulated in MDS.

1. Introduction

MDS encompasses a diverse range of oncohematological diseases affecting hematopoietic stem cells and their hematopoietic microenvironment [1]. MDS is characterized by dysplastic ineffective hematopoiesis with the apoptosis of hematopoietic cells in the bone marrow and by subsequent cytopenias in the blood. It occurs in particularly elder people with incidence of 20–50 patients in 100,000 inhabitants [2]. There are several groups of MDS patients according to the WHO classification based on bone marrow and peripheral blood findings, cytogenetics, and other factors [3]. Prognostically MDS subgroups can be also stratified into low-risk and high-risk subgroups; high-risk subgroups are characterized by poor survival outcome and higher rate of progression toward acute myeloid leukemia. Refractory cytopenia with multilineage dysplasia (RCMD) is a subgroup of myelodysplastic syndrome (MDS). According to the revised WHO (World Health Organization) classification of MDS, RCMD is defined by the presence of cytopenias in peripheral blood and dysplastic changes present in 10% or more of the cells in two or more myeloid lineages in the bone marrow (with approximately 15% ringed sideroblasts) [3].

In recent years, fundamental knowledge in MDS pathophysiology based on DNA alterations has been and is still being complemented by other “omics” disciplines, in particular by proteomics, with the proteomes of plasma (of different MDS subgroups such as refractory anemia and refractory anemia with ringed sideroblasts (RA and RARS) [4], RCMD [5], refractory anemia with excess of blasts subtype 1 (RAEB-1) [6], and refractory anemia with excess of blasts subtype 2 (RAEB-2) [7]), serum [8, 9], platelets [10], and neutrophils [11] of MDS patients having been investigated. Despite research efforts the pathogenesis and exact mechanisms of MDS development still remain unclear, as there are many factors involved. For example, factors involved in the development of MDS (cytogenetic abnormalities [12], gene mutations [1315], epigenetic alterations [16], etc.) can contribute to the dysregulation of various processes in the immune system [17], a portion of which are by mononuclear blood cells (B-lymphocytes, T-lymphocytes, dendritic cells, and monocytes). Mononuclear cells represent a heterogeneous population; nevertheless, due to the rapid and simple methods of their isolation, they are believed to be a promising and interesting material to search for biomarkers [1820]. As very little is known about the role of mononuclear cells and their protein alterations in MDS the goal of this work, our aim, has been to describe the changes in the proteome of mononuclear blood cells of MDS patients and to discuss the involvement of these changes in MDS pathophysiology.

2. Methods

In this pilot study, a total of 12 samples (RCMD , control ) have been investigated. The diagnosis of RCMD was established according to the WHO classification criteria [21]. The median age of RCMD patients was 67; the patient group included 4 females (67%). The median age of sex-matched healthy control donors was 28. Patient characteristics are summarized in Table 1. All of the individuals tested agreed to participate in the study on the basis of an informed consent. All samples were obtained and analyzed in accordance with the Ethical Committee regulations of the Institute of Hematology and Blood Transfusion.

Table 1: Patient characteristics.

Blood samples were collected by venipuncture into EDTA-coated tubes. Peripheral blood mononuclear cells were isolated from 9 mL of whole blood using Histopaque-1077 (Sigma-Aldrich, Prague, Czech Republic) according to manufacturer instructions.

Protein fractionation was performed using a ProteoExtract Subcellular Proteome Extraction Kit (Merck Millipore, Darmstadt, Germany) according to manufacturer instructions to enrich the proteins according to their subcellular localization; four different subproteomes were obtained (cytosolic, membrane and membrane organelle, nuclear, and cytoskeletal). Enriched proteins were precipitated with the addition of four volumes of acetone, incubated for 60 min at −20°C, and then centrifuged at 15,000 ×g for 10 min. Protein concentration in all samples was determined using a Micro-BCA Protein Assay Kit (Thermo Fischer Scientific, Waltham, MA, USA). Protein sample concentrations of each subproteome were adjusted to the same level.

Isoelectric focusing was performed (IPG strips pI 4–7, 7.7 cm) followed by SDS-PAGE (8 × 10 cm, 10% resolving gel, 3.75% stacking gel, and 30 mA/gel), as described in detail in previous publications [46, 22]. Briefly, 40 μg of cytosolic, 50 μg of membrane and membrane organelle, and 40 μg of nuclear proteins were used for an IPG strip. The proteins of the cytoskeletal subproteome were not analyzed due to insufficient protein yield.

The gels were double-stained according to the improved fast-staining protocol [23], combining imidazole-zinc reverse and Coomassie dye-based staining. Imidazole-zinc reverse staining was used to detect as many spots as possible, followed by Coomassie dye-based staining to enable maximal spot detection and quantification. After each staining step, the gels were digitized and processed with Progenesis SameSpots software (Nonlinear Dynamics, Newcastle upon Tyne, UK) that computed the fold and values of all spots using one-way ANOVA analysis. Protein spots that differed significantly () were submitted for protein identification by tandem mass spectrometry (HCT ultra ion-trap mass spectrometer with nanoelectrospray ionization; Bruker Daltonics, Bremen, Germany) coupled to a nano-LC system (UltiMate 3000; Dionex, Sunnyvale, CA, USA); this procedure has been described in detail previously [46, 22]. Mascot (Matrix Science, London, UK) was used for database searching (Swiss-Prot). Two unique peptides (with higher Mascot scores than the minimum for identification, ) were necessary to successfully identify a protein. Exceptions were given to proteins with a molecular weight of 15 kDa or less and to proteins with more than 3 additional unique peptides identified by error tolerant search.

To analyze the functional associations between identified proteins and cellular pathways, the protein list was processed with the on-line EnrichNet application [24] using KEGG [25, 26] and Reactome [27, 28] databases. The significance of overlap between protein sets was evaluated using a combination of one-side Fisher’s exact test () and network similarity scores (XD-scores). The threshold values were estimated via EnrichNet with a regression fit equivalent to a Fisher value of 0.05 and an upper boundary of 95% confidence for linear fitting.

Dendrogram analysis was performed using Progenesis SameSpots software to reveal closely related proteins. The dendrogram is a visual representation of spot correlation data (with correlation analysis performed on log-normalized spot expression levels). Spots were clustered according to their closest correlation.

Western blot analysis was performed for vinculin and fermitin-3 proteins. Equal protein amounts of all (patient or donor) samples of appropriate protein fractions were pooled and 1 μg or 0.75 μg of total protein amounts were used for 1D western blot analyses for vinculin or fermitin-3, respectively. Briefly, following SDS-PAGE (10% resolving gel) proteins were transferred to a PVDF membrane (10 V constant voltage for 60 min) using an Owl HEP-1 Semi Dry Electroblotting System (Thermo Scientific, Waltham, MA, USA). Membranes were then incubated with a blocking buffer (3% BSA in PBS) at 30°C for 60 min and incubated with primary antibodies, anti-vinculin antibody (V9131; Sigma-Aldrich, Praque, Czech Republic) (1 : 200 dilution) or anti-kindlin-3 antibody (SAB4200013; Sigma-Aldrich, Prague, Czech Republic) (1 : 340 dilution). Then the membranes were incubated with secondary antibodies, rabbit anti-mouse IgG antibody conjugated with peroxidase (for vinculin detection, 1 : 80,000 dilution) (A9044; Sigma-Aldrich, Prague, Czech Republic) or goat anti-rabbit IgG antibody conjugated with peroxidase (for kindlin-3 detection, 1 : 120,000 dilution) (A0545; Sigma-Aldrich, Prague, Czech Republic). Visualization was performed using a chemiluminescent substrate (SuperSignal West Pico; Thermo Scientific, Waltham, MA, USA) and CL-XPosure Film (Thermo Scientific, Waltham, MA, USA).

3. Results and Discussion

Comparing the PBMC subproteomes of RCMD patients () with healthy volunteer control group subproteomes (), we found 178 spots that differed significantly in their normalized volumes (). Figures 13 indicate the positions of significantly differing spots of the cytosolic, membrane and membrane organelle, and nuclear subproteomes, respectively. The spots are marked considering the gel staining.

Figure 1: Positions of cytosolic subproteome spots significantly differing in normalized volumes, only in gels stained by imidazole-zinc (red numbers), only in Coomassie stained gels (blue numbers), and in both stains (black numbers). Brightness and contrast of the gel image were adjusted for more clear illustration.
Figure 2: Positions of membrane and membrane organelle subproteome spots significantly differing in normalized volumes, only in gels stained by imidazole-zinc (red numbers), only in Coomassie stained gels (blue numbers), and in both stains (black numbers). Brightness and contrast of the gel image were adjusted for more clear illustration.
Figure 3: Positions of nuclear subproteome spots significantly differing in normalized volumes, only in gels stained by imidazole-zinc (red numbers), only in Coomassie stained gels (blue numbers), and in both stains (black numbers). Brightness and contrast of the gel image were adjusted for more clear illustration.

Proteins of the spots detected were submitted to protein identification by mass spectrometry, and 139 unique proteins were identified. The list of all spots, including ANOVA values, their multiplication (fold value), protein identification with the number of identified peptides (unique peptides above the identity threshold score), and protein accession number (Swiss-Prot), is summarized in Table 2.

Table 2: List of spots that differed significantly when RCMD patients were compared with a control group of healthy volunteers.

We compared these summarized results with our previous research that investigated the plasma proteomes of patients with different MDS subgroups [47]. It is known that PBMCs can secrete proteins into the plasma [29, 30]; therefore, we searched for changes in plasma proteomes that could be related to PBMCs. Nevertheless, none of the proteins identified in this study corresponded to any proteins identified in our previous proteomic studies of the plasma. This observation strongly indicates that the alterations observed in plasma proteins (possibly secreted by PBMCs) are caused by posttranslational modifications of such proteins instead of the changes in their level. For example, we have shown in our previous plasma proteome MDS studies [47] that inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) was extensively fragmented and the changes observed (for ITIH4) were related to these fragments; similar results were observed for complement proteins. However, it should be taken into account that PBMCs are not the only source of these plasma proteins.

In order to estimate the possible involvement of the identified proteins in the PBMC cellular and metabolic pathways and thus reveal the processes influenced by RCMD pathogenesis, we processed the protein dataset in EnrichNet. Enrichment analysis using KEGG and Reactome databases revealed implications of the identified proteins in several cellular pathways (Tables 3 and 4). XD-scores were considered to be more than 0.78 and 1.0 threshold values, as estimated by the application for the KEGG and Reactome databases, respectively.

Table 3: Functional association of the identified protein dataset with KEGG cellular pathways.
Table 4: Functional association of the identified protein dataset with Reactome cellular pathways.

Dendrogram analysis was performed using Progenesis SameSpots, which grouped spots by their expression profiles using an automatic correlation analysis and hierarchical clustering. We chose the top ten spot expression profile groups (with distance parameters less than 0.5) with almost identical expression profiles. Thus, each group contained spots with similar expression profiles, suggesting that these spots may be coregulated, colocalized, or by another way coaffected. The list of the expression profile groups (denoted as A, B, etc.), including the spot number, protein identification, and its accession number, is presented in Tables 57. Proteins in the F1 groups (cytosolic subproteome) were associated with the cytoskeleton, microtubule metabolism, cellular homeostasis maintained by heat shock proteins (HSPs), and proteasome. Proteins in the F2 groups (membrane and membrane organelle subproteome) were associated with the mitochondria and apoptosis. The protein identified in most cases in the F3 groups (nuclear subproteome) was Filamin-A, which is released from the apoptotic nucleus [31]. Other proteins in these groups were mainly actin and actin-binding proteins. Thus, the actual associations corresponded to the subproteomes as anticipated. Due to thematic similarity of the protein groups obtained via EnrichNet and dendrogram analysis, we discuss the results in parallel. Further in relation to MDS or other hematological malignancies, we summarize the most interesting protein groups that could be affected in connection with pathophysiological processes.

Table 5: List of the expression profile groups (A, B, and C) found in the cytosolic subproteome (F1).
Table 6: List of the expression profile groups (A, B, C, D, and E) found in the membrane and membrane organelle subproteome (F2).
Table 7: List of the expression profile groups (A, B) found in the nuclear subproteome (F3).

PBMCs are metabolically active cells (carbohydrate metabolism, cellular respiration) and as cells of the immune system are involved in antigen processing and presentation. Our KEGG results analysis (Table 3) highlighted the relationships of the identified proteins to infectious agents (E. coli). This observation is not surprising, as it is known that the immune system in MDS is dysregulated and MDS patients tend to be especially vulnerable to infections [17, 32]. Therefore, this observation is most likely related to the manifestation of secondary complications, rather than MDS itself.

T-complex protein 1 (TCP-1) subunits (four of eight identified, Table 2) with a degree of functional autonomy [33] are a part of the TRiC cytosolic chaperone (TCP-1 ring complex), which acts in tubulin biosynthesis (Table 4). This chaperone was originally thought to fold only cytoskeletal proteins but now is known to have a more general role in protein folding in eukaryotic cytosol [34]. TRiC also assists in the formation of BBSome, a part of the primary cilium, nonmotile microtubule-based sensory organelle transporting signals within the cell [35]. Primary cilium has not been under closer analysis until in the last decade, and many questions surrounding it are still unanswered. For example, it is not entirely known, whether the primary cilium is present in PBMCs [3639]. There is evidence that components which contribute to the assembly of the primary cilium are expressed by PBMCs [36]. Therefore, there is a possibility that TCP subunits are part of the machinery of primary cilium formation or function, as a chaperone not only of cytoskeletal proteins (see Table 5, Groups F1A, F1B). Changes in TCP subunits could cause changes or even errors in BBSome formation [40], thus an effect on signaling within the cell. In last decade, the function of primary cilium in several cancers has been described, but its role in hematological malignancies has not yet been unraveled. There is also the possibility that a change in TCP subunits could affect the proper folding of proteins involved in hematopoiesis and its regulation and therefore may contribute to MDS pathogenesis.

Apoptosis, an important phenomenon in MDS, in a highly regulated manner removes the excess or potentially dangerous cells from the organism. The apoptotic process relies heavily on the cleavage of proteins/proteolysis. Any proteolytic pathway involved in cell death regulation must be precise; therefore, a highly regulated proteasome pathway is a good candidate for the regulation of protein composition during apoptosis [41]. Evidence of cross talk between the apoptotic pathways, HSPs, and proteasome system exists [42]; the relation of these processes is also suggested in our dendrogram analysis results (see Table 5, Group F1C). It is difficult to define a clear role or the involvement of the proteasome system in apoptosis, because in some systems proteasome activity induces apoptosis while in others it does not [42]. It is possible that increased proteasome activity causes the suppression of apoptosis, and this could be one of the reasons for the transformation from MDS to AML [43]. In relation to programmed cell death, researchers have identified changes in the regulatory subunits of the 19S cap complex [44, 45]. We observed changes in several proteasomal proteins and in the non-ATPase regulatory subunits of the 26S complex (Table 5, Group F1C), a part of which is the 19S cap complex [46]. We also observed changes in several HSPs, including HSP90α (identified in spot 51), whose overexpression has already been linked to apoptosis and MDS [47]. HSPs assist in proper protein folding, as molecular chaperones. They are fundamental for cell life and death decisions, and their abnormal expression is linked to oncogenesis [48]. When a protein is misfolded, HSPs are induced and associate with the misfolded protein, trying to refold it. When this process fails, the protein is ubiquitinated and determined to be processed by the proteasome. In case there are not enough HSPs or the proteasome function is impaired, proteins tend to aggregate with HSPs, ubiquitin, and proteasome to an insoluble compartment and trigger apoptosis [42, 49, 50]. HSPs can act in apoptosis at three levels: (i) in upstream mitochondria by regulating signaling molecules [51] (see Table 5, Group F1C); (ii) at the mitochondrial level by controlling mitochondrial membrane permeabilization and thus the release of cytochrome c [52] (see Table 6); and (iii) downstream of the mitochondria by affecting apoptosome formation [53] (see Table 5, Group F1C). Their role in apoptosis is also controversial; HSP function in apoptosis may be impacted by posttranslational modifications and the interaction with cochaperones (e.g., the DnaJ-family proteins identified in spot 124) [54]. The overexpression of HSPs has been shown to block apoptosis; and on the other hand, the depletion of HSPs increases sensitivity to apoptotic stimuli [55]. We observed both a decrease and an increase in normalized volumes in the spots containing HSPs (Table 2). However, from 2D SDS-PAGE data it is not possible to claim whether a change is caused by protein expression alteration or by protein posttranslational modification. Therefore, there is the possibility that the HSPs identified are posttranslationally modified, differently expressed, or a combination of both. Changes in proteasomal proteins and HSPs could be involved in cells’ decisions regarding the triggering of apoptosis. Because of the inconsistency in the roles of both the proteasome and HSPs in apoptosis, we can only speculate whether the changes are the cause of the apoptosis in MDS.

In order to provide further insight into the possible PMBCs alterations in MDS patients additional to those suggested by the 2D electrophoresis data, western blot analysis was performed for the two of identified proteins: fermitin-3 and vinculin. Both the proteins were uniquely identified in the corresponding spots (without coidentified proteins) and they are both involved in particular in cell adhesion and integrin signaling [56, 57]. While vinculin was identified in five different spots with both increasing and decreasing spot normalized volumes (which strongly indicates the presence of posttranslational modifications and the alterations of individual proteoforms), fermitin-3 was observed in one spot only. The results of western blot analysis are shown in Figure 4.

Figure 4: Western blot analysis of vinculin and fermitin-3 proteins; 1, molecular weight marker (kDa); 2 and 4, pooled control samples; 3 and 5, pooled MDS patient samples.

It is apparent that vinculin is underexpressed in PBMCs of MDS patients when compared to the healthy donor group. Therefore, while the prevalent vinculin form is decreased in MDS there is also a minority of posttranslationally modified forms altered as estimated from 2D electrophoresis and LC-MS/MS data. Vinculin is an actin-binding protein that is involved especially in cell adhesion dynamics and cell migration [56, 58]. Downregulation of vinculin expression could be possibly related to the immune system dysregulation in MDS as vinculin underexpression was described in the study by Kim et al. [56] investigating proteome changes in PBMCs of patients with atopic dermatitis, a chronic inflammatory skin disease. The presence of vinculin posttranslational modifications (as indicated in this work) was also observed in the proteomic study of PBMCs collected from amyotrophic lateral sclerosis (ALS) patients; significantly higher level of vinculin nitration was observed for sporadic ALS patients compared to healthy donors [59].

Western blot analysis of fermitin-3 showed the presence of several protein forms; in addition to the uncleaved protein, various fragments of fermitin-3 were observed. The uncleaved fermitin-3 band was observed with a lower intensity in MDS patients compared to the healthy controls; this observation may suggest fermitin-3 underexpression in MDS patients. However, the total intensity of the unaltered fermitin-3 together with its fragments estimated with ImageJ software [60] showed that there is no difference between MDS patients and the healthy controls. Therefore, while fermitin-3 expression did not seem to differ between the studied groups, it was shown that there was advanced fermitin-3 fragmentation in MDS patients. Fermitin-3 is a member of the family of focal adhesion proteins exclusively expressed in hematopoietic cells [61]. Its role in adhesion is essential for the function of blood cells including leukocytes [57, 62, 63]. Thus, higher rate of fermitin-3 fragmentation observed in this work could substantially influence PMBCs function in MDS. Moreover, fermitin-3 and vinculin are known to be colocalized to hematopoietic cell adhesion structure called podosome [64]. Therefore, since vinculin and fermitin-3 are both involved in cell adhesion and integrin signaling (and thus could play an important role in clinical applications) their changes observed in this work could initiate future research efforts.

4. Conclusion

In conclusion, we have compared the peripheral blood mononuclear cell proteome of myelodysplastic syndrome patients with refractory cytopenia with multilineage dysplasia against the proteome of healthy donors using two-dimensional electrophoresis combined with mass spectrometry. Through data mining of the Reactome and KEGG databases using EnrichNet, we highlighted the possible involvement of the identified protein alterations in apoptosis, protein degradation by proteasome, heat shock protein action, and signal transduction. Western blot analysis showed substantial changes in vinculin and fermitin-3, proteins involved in cell adhesion and integrin signaling. Vinculin was found to be underexpressed in MDS patients; advanced fragmentation of fermitin-3 was shown to take place in PBMCs of MDS patients.

To the best of our knowledge, our pilot study represents the first report on the proteome changes of peripheral blood mononuclear cells in myelodysplastic syndrome.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

This study was supported by the Czech Science Foundation P205/12/G118 and by the state project (Ministry of Health, Czech Republic) for the conceptual development of the research organization (Institute of Hematology and Blood Transfusion).

References

  1. J. Schecter, N. Galili, and A. Raza, “MDS: refining existing therapy through improved biologic insights,” Blood Reviews, vol. 26, no. 2, pp. 73–80, 2012. View at Publisher · View at Google Scholar · View at Scopus
  2. R. Neuwirtová, “Myelodysplastický syndrom: onkohematologické onemocnění vyššího věku,” Česká Geriatrická Revue, vol. 3, no. 2, pp. 21–28, 2005. View at Google Scholar
  3. J. W. Vardiman, J. Thiele, D. A. Arber et al., “The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes,” Blood, vol. 114, no. 5, pp. 937–951, 2009. View at Publisher · View at Google Scholar · View at Scopus
  4. P. Májek, Z. Riedelová-Reicheltová, J. Suttnar, K. Pečánková, J. Čermák, and J. E. Dyr, “Plasma proteome changes associated with refractory anemia and refractory anemia with ringed sideroblasts in patients with myelodysplastic syndrome,” Proteome Science, vol. 11, no. 1, article 14, 2013. View at Publisher · View at Google Scholar · View at Scopus
  5. P. Májek, Z. Reicheltová, J. Suttnar, J. Čermák, and J. E. Dyr, “Plasma proteome changes associated with refractory cytopenia with multilineage dysplasia,” Proteome Science, vol. 9, article 64, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. P. Májek, Z. Reicheltová, J. Suttnar, J. Čermák, and J. E. Dyr, “Plasma protein alterations in the refractory anemia with excess blasts subtype 1 subgroup of myelodysplastic syndrome,” Proteome Science, vol. 10, no. 1, article 31, 2012. View at Publisher · View at Google Scholar · View at Scopus
  7. P. Májek, Z. Riedelová-Reicheltová, J. Suttnar, K. Pecankova, J. Čermák, and J. E. Dyr, “Proteome changes in the plasma of myelodysplastic syndrome patients with refractory anemia with excess blasts subtype 2,” Disease Markers, vol. 2014, Article ID 178709, 8 pages, 2014. View at Publisher · View at Google Scholar
  8. M. Aivado, D. Spentzos, U. Germing et al., “Serum proteome profiling detects myelodysplastic syndromes and identifies CXC chemokine ligands 4 and 7 as markers for advanced disease,” Proceedings of the National Academy of Sciences of the United States of America, vol. 104, no. 4, pp. 1307–1312, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Chen, D. T. Bowen, A. A. N. Giagounidis, B. Schlegelberger, S. Haase, and E. G. Wright, “Identification of disease- and therapy-associated proteome changes in the sera of patients with myelodysplastic syndromes and del(5q),” Leukemia, vol. 24, no. 11, pp. 1875–1884, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. J. Fröbel, R.-P. Cadeddu, S. Hartwig et al., “Platelet proteome analysis reveals integrin-dependent aggregation defects in patients with myelodysplastic syndromes,” Molecular & Cellular Proteomics, vol. 12, no. 5, pp. 1272–1280, 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. H. Kazama, M. Teramura, S. Kurihara, K. Yoshinaga, T. Kato, and T. Motoji, “Peroxiredoxin 2 expression is increased in neutrophils of patients with refractory cytopenia with multilineage dysplasia,” British Journal of Haematology, vol. 166, no. 5, pp. 720–728, 2014. View at Google Scholar
  12. P. L. Greenberg, Ed., Myelodysplastic Syndromes: Clinical and Biological Advances, Cambridge University Press, Cambridge, UK, 2006.
  13. M. J. Walter, D. Shen, J. Shao et al., “Clonal diversity of recurrently mutated genes in myelodysplastic syndromes,” Leukemia, vol. 27, no. 6, pp. 1275–1282, 2013. View at Publisher · View at Google Scholar · View at Scopus
  14. A. Bains, R. Luthra, L. J. Medeiros, and Z. Zuo, “FLT3 and NPM1 mutations in myelodysplastic syndromes: frequency and potential value for predicting progression to acute myeloid leukemia,” The American Journal of Clinical Pathology, vol. 135, no. 1, pp. 62–69, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. C.-Y. Chen, L.-I. Lin, J.-L. Tang et al., “RUNX1 gene mutation in primary myelodysplastic syndrome—the mutation can be detected early at diagnosis or acquired during disease progression and is associated with poor outcome,” British Journal of Haematology, vol. 139, no. 3, pp. 405–414, 2007. View at Publisher · View at Google Scholar · View at Scopus
  16. J.-P. Issa, “Epigenetic changes in the myelodysplastic syndrome,” Hematology/Oncology Clinics of North America, vol. 24, no. 2, pp. 317–330, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. C. Sugimori, A. F. List, and P. K. Epling-Burnette, “Immune dysregulation in myelodysplastic syndrome,” Hematology Reports, vol. 2, no. 1, article e1, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. D. Vergara, F. Chiriacò, R. Acierno, and M. Maffia, “Proteomic map of peripheral blood mononuclear cells,” Proteomics, vol. 8, no. 10, pp. 2045–2051, 2008. View at Publisher · View at Google Scholar · View at Scopus
  19. G. Maccarrone, C. Rewerts, M. Lebar, C. W. Turck, and D. Martins-de-Souza, “Proteome profiling of peripheral mononuclear cells from human blood,” Proteomics, vol. 13, no. 5, pp. 893–897, 2013. View at Publisher · View at Google Scholar · View at Scopus
  20. E. Maes, B. Landuyt, I. Mertens, and L. Schoofs, “Interindividual variation in the proteome of human peripheral blood mononuclear cells,” PLoS ONE, vol. 8, no. 4, Article ID e61933, 2013. View at Publisher · View at Google Scholar · View at Scopus
  21. J. W. Vardiman, N. L. Harris, and R. D. Brunning, “The World Health Organization (WHO) classification of the myeloid neoplasms,” Blood, vol. 100, no. 7, pp. 2292–2302, 2002. View at Publisher · View at Google Scholar · View at Scopus
  22. P. Májek, Z. Reicheltová, J. Štikarová, J. Suttnar, A. Sobotková, and J. E. Dyr, “Proteome changes in platelets activated by arachidonic acid, collagen, and thrombin,” Proteome Science, vol. 8, article 56, 2010. View at Publisher · View at Google Scholar · View at Scopus
  23. P. Májek, Z. Riedelová-Reicheltová, K. Pecánková, and J. E. Dyr, “Improved coomassie blue dye-based fast staining protocol for proteins separated by SDS-PAGE,” PLoS ONE, vol. 8, no. 11, Article ID e81696, 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. E. Glaab, A. Baudot, N. Krasnogor, R. Schneider, and A. Valencia, “EnrichNet: network-based gene set enrichment analysis,” Bioinformatics, vol. 28, no. 18, pp. i451–i457, 2012. View at Publisher · View at Google Scholar · View at Scopus
  25. M. Kanehisa, S. Goto, Y. Sato, M. Kawashima, M. Furumichi, and M. Tanabe, “Data, information, knowledge and principle: back to metabolism in KEGG,” Nucleic Acids Research, vol. 42, no. 1, pp. D199–D205, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. M. Kanehisa and S. Goto, “KEGG: kyoto encyclopedia of genes and genomes,” Nucleic Acids Research, vol. 28, no. 1, pp. 27–30, 2000. View at Publisher · View at Google Scholar · View at Scopus
  27. D. Croft, A. F. Mundo, R. Haw et al., “The reactome pathway knowledgebase,” Nucleic Acids Research, vol. 42, no. 1, pp. D472–D477, 2014. View at Publisher · View at Google Scholar · View at Scopus
  28. M. M. Milacic, R. Haw, K. Rothfels et al., “Annotating cancer variants and anti-cancer therapeutics in reactome,” Cancers, vol. 4, no. 4, pp. 1180–1211, 2012. View at Publisher · View at Google Scholar · View at Scopus
  29. K. E. Sullivan, J. Cutilli, L. M. Piliero et al., “Measurement of cytokine secretion, intracellular protein expression, and mRNA in resting and stimulated peripheral blood mononuclear cells,” Clinical and Diagnostic Laboratory Immunology, vol. 7, no. 6, pp. 920–924, 2000. View at Publisher · View at Google Scholar · View at Scopus
  30. D. G. Haider, N. Leuchten, G. Schaller et al., “C-reactive protein is expressed and secreted by peripheral blood mononuclear cells,” Clinical and Experimental Immunology, vol. 146, no. 3, pp. 533–539, 2006. View at Publisher · View at Google Scholar · View at Scopus
  31. K. A. Browne, R. W. Johnstone, D. A. Jans, and J. A. Trapani, “Filamin (280-kDa actin-binding protein) is a caspase substrate and is also cleaved directly by the cytotoxic T lymphocyte protease granzyme B during apoptosis,” The Journal of Biological Chemistry, vol. 275, no. 50, pp. 39262–39266, 2000. View at Publisher · View at Google Scholar · View at Scopus
  32. J. Bennett, Understanding Myelodysplastic Syndromes: A Patient Handbook, The Myelodysplastic Syndromes Foundation, Crosswicks, NJ, USA, 6th edition, 2008.
  33. C. Coghlin, B. Carpenter, S. R. Dundas, L. C. Lawrie, C. Telfer, and G. I. Murray, “Characterization and over-expression of chaperonin t-complex proteins in colorectal cancer,” The Journal of Pathology, vol. 210, no. 3, pp. 351–357, 2006. View at Publisher · View at Google Scholar · View at Scopus
  34. M. B. Yaffe, G. W. Farr, D. Miklos, A. L. Horwich, M. L. Sternlicht, and H. Sternlicht, “TCP1 complex is a molecular chaperone in tubulin biogenesis,” Nature, vol. 358, no. 6383, pp. 245–248, 1992. View at Publisher · View at Google Scholar · View at Scopus
  35. S. C. Goetz and K. V. Anderson, “The primary cilium: a signalling centre during vertebrate development,” Nature Reviews Genetics, vol. 11, no. 5, pp. 331–344, 2010. View at Publisher · View at Google Scholar · View at Scopus
  36. F. Finetti, S. R. Paccani, M. G. Riparbelli et al., “Intraflagellar transport is required for polarized recycling of the TCR/ CD3 complex to the immune synapse,” Nature Cell Biology, vol. 11, no. 11, pp. 1332–1339, 2009. View at Publisher · View at Google Scholar · View at Scopus
  37. I. B. Alieva and I. A. Vorobjev, “Vertebrate primary cilia: a sensory part of centrosomal complex in tissue cells, but a ‘sleeping beauty’ in cultured cells?” Cell Biology International, vol. 28, no. 2, pp. 139–150, 2004. View at Publisher · View at Google Scholar · View at Scopus
  38. O. V. Plotnikova, E. A. Golemis, and E. N. Pugacheva, “Cell cycle-dependent ciliogenesis and cancer,” Cancer Research, vol. 68, no. 7, pp. 2058–2061, 2008. View at Publisher · View at Google Scholar · View at Scopus
  39. E. S. Seeley and M. V. Nachury, “The perennial organelle: assembly and disassembly of the primary cilium,” Journal of Cell Science, vol. 123, no. 4, pp. 511–518, 2010. View at Publisher · View at Google Scholar · View at Scopus
  40. S. Seo, L. M. Baye, N. P. Schulz et al., “BBS6, BBS10, and BBS12 form a complex with CCT/TRiC family chaperonins and mediate BBSome assembly,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 4, pp. 1488–1493, 2010. View at Publisher · View at Google Scholar · View at Scopus
  41. L. M. Grimm and B. A. Osborne, “The role of the proteasome in apoptosis,” in Proteasomes: The World of Regulatory Proteolysis, W. Hilt and D. M. Wolf, Eds., pp. 315–331, Landes Bioscience, Georgetown, Tex, USA, 2000. View at Google Scholar
  42. C. Wójcik, “Regulation of apoptosis by the ubiquitin and proteasome pathway,” Journal of Cellular and Molecular Medicine, vol. 6, no. 1, pp. 25–48, 2002. View at Publisher · View at Google Scholar · View at Scopus
  43. T. Braun, G. Carvalho, A. Coquelle et al., “NF-κB constitutes a potential therapeutic target in high-risk myelodysplastic syndrome,” Blood, vol. 107, no. 3, pp. 1156–1165, 2006. View at Publisher · View at Google Scholar · View at Scopus
  44. S. P. Dawson, J. E. Arnold, N. J. Mayer et al., “Developmental changes of the 26 S proteasome in abdominal intersegmental muscles of Manduca sexta during programmed cell death,” The Journal of Biological Chemistry, vol. 270, no. 4, pp. 1850–1858, 1995. View at Publisher · View at Google Scholar · View at Scopus
  45. K. Takayanagi, S. Dawson, S. E. Reynolds, and R. J. Mayer, “Specific developmental changes in the regulatory subunits of the 26 S proteasome in intersegmental muscles preceding eclosion in Manduca sexta,” Biochemical and Biophysical Research Communications, vol. 228, no. 2, pp. 517–523, 1996. View at Publisher · View at Google Scholar · View at Scopus
  46. G. N. DeMartino and T. G. Gillette, “Proteasomes: machines for all reasons,” Cell, vol. 129, no. 4, pp. 659–662, 2007. View at Publisher · View at Google Scholar · View at Scopus
  47. P. Flandrin-Gresta, F. Solly, C. M. Aanei et al., “Heat shock protein 90 is overexpressed in high-risk myelodysplastic syndromes and associated with higher expression and activation of focal adhesion kinase,” Oncotarget, vol. 3, no. 10, pp. 1158–1168, 2012. View at Google Scholar · View at Scopus
  48. E. M. Creagh, D. Sheehan, and T. G. Cotter, “Heat shock proteins—modulators of apoptosis in tumour cells,” Leukemia, vol. 14, no. 7, pp. 1161–1173, 2000. View at Publisher · View at Google Scholar · View at Scopus
  49. M. Y. Sherman and A. L. Goldberg, “Cellular defenses against unfolded proteins: a cell biologist thinks about neurodegenerative diseases,” Neuron, vol. 29, no. 1, pp. 15–32, 2001. View at Publisher · View at Google Scholar · View at Scopus
  50. R. R. Kopito, “Aggresomes, inclusion bodies and protein aggregation,” Trends in Cell Biology, vol. 10, no. 12, pp. 524–530, 2000. View at Publisher · View at Google Scholar · View at Scopus
  51. D. Lanneau, M. Brunet, E. Frisan, E. Solary, M. Fontenay, and C. Garrido, “Heat shock proteins: essential proteins for apoptosis regulation,” Journal of Cellular and Molecular Medicine, vol. 12, no. 3, pp. 743–761, 2008. View at Publisher · View at Google Scholar · View at Scopus
  52. A. R. Stankiewicz, G. Lachapelle, C. P. Foo, S. M. Radicioni, and D. D. Mosser, “Hsp70 inhibits heat-induced apoptosis upstream of mitochondria by preventing Bax translocation,” The Journal of Biological Chemistry, vol. 280, no. 46, pp. 38729–38739, 2005. View at Publisher · View at Google Scholar · View at Scopus
  53. H. M. Beere, B. B. Wolf, K. Cain et al., “Heat-shock protein 70 inhibits apoptosis by preventing recruitment of procaspase-9 to the Apaf-1 apoptosome,” Nature Cell Biology, vol. 2, no. 8, pp. 469–475, 2000. View at Publisher · View at Google Scholar · View at Scopus
  54. S. Takayama, J. C. Reed, and S. Homma, “Heat-shock proteins as regulators of apoptosis,” Oncogene, vol. 22, no. 56, pp. 9041–9047, 2003. View at Publisher · View at Google Scholar · View at Scopus
  55. M. Kamada, A. So, M. Muramaki, P. Rocchi, E. Beraldi, and M. Gleave, “Hsp27 knockdown using nucleotide-based therapies inhibit tumor growth and enhance chemotherapy in human bladder cancer cells,” Molecular Cancer Therapeutics, vol. 6, no. 1, pp. 299–308, 2007. View at Publisher · View at Google Scholar · View at Scopus
  56. W. K. Kim, H. J. Cho, S. I. Ryu et al., “Comparative proteomic analysis of peripheral blood mononuclear cells from atopic dermatitis patients and healthy donors,” Biochemistry and Molecular Biology Reports, vol. 41, no. 8, pp. 597–607, 2008. View at Google Scholar
  57. Z. H. Xue, C. Feng, W. L. Liu, and S. M. Tan, “A role of kindlin-3 in integrin αMβ2 outside-in signaling and the Syk-Vav1-Rac1/Cdc42 signaling axis,” PLoS ONE, vol. 8, Article ID e56911, 2013. View at Google Scholar
  58. D. R. Critchley, “Cytoskeletal proteins talin and vinculin in integrin-mediated adhesion,” Biochemical Society Transactions, vol. 32, part 5, pp. 831–836, 2004. View at Google Scholar
  59. G. Nardo, S. Pozzi, S. Mantovani et al., “Nitroproteomics of peripheral blood mononuclear cells from patients and a rat model of ALS,” Antioxidants and Redox Signaling, vol. 11, no. 7, pp. 1559–1567, 2009. View at Google Scholar
  60. C. A. Schneider, W. S. Rasband, and K. W. Eliceiri, “NIH Image to ImageJ: 25 years of image analysis,” Nature Methods, vol. 9, no. 7, pp. 671–675, 2012. View at Google Scholar
  61. S. Ussar, H. V. Wang, S. Linder, R. Fässler, and M. Moser, “The Kindlins: subcellular localization and expression during murine development,” Experimental Cell Research, vol. 312, pp. 3142–3151, 2006. View at Google Scholar
  62. M. Moser, M. Bauer, S. Schmid et al., “Kindlin-3 is required for β2 integrin-mediated leukocyte adhesion to endothelial cells,” Nature Medicine, vol. 15, pp. 300–305, 2009. View at Google Scholar
  63. V. L. Morrison, M. MacPherson, T. Savinko, H. S. Lek, A. Prscott, and S. C. Fagerholm, “The β2 integrin-kindlin-3 interaction is essential for T-cell homing but dispensable for T-cell activation in vivo,” Blood, vol. 122, no. 8, pp. 1428–1436, 2013. View at Google Scholar
  64. S. Linder and P. Kopp, “Podosomes at a glance,” Journal of Cell Science, vol. 118, no. 10, pp. 2079–2082, 2005. View at Google Scholar