Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer

JPROT-02712; No of Pages 9 Journal of Proteomics xxx (2016) xxx–xxx

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Journal of Proteomics journal homepage: www.elsevier.com/locate/jprot

Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer Raluca M Boteanu a, Viorel I Suica a, Elena Uyy a, Luminita Ivan a, Simona O Dima b, Irinel Popescu b, Maya Simionescu a, Felicia Antohe a,⁎ a b

Institute of Cellular Biology and Pathology “N. Simionescu” of the Romanian Academy, Bucharest, Romania Clinical Institute Fundeni, Bucharest, Romania

a r t i c l e

i n f o

Article history: Received 1 April 2016 Received in revised form 18 October 2016 Accepted 9 November 2016 Available online xxxx Keywords: Alarmins Proteomics Atherosclerosis Diabetes Cancer

a b s t r a c t There is a wide range of pathological conditions proved to be associated with inflammation. The inflammatory process offers protection against harmful stimuli such as induced cell injury and tissues damage by means of specialized mediators and cells. Alarmins, also known as endogenous danger signals or damage-associated molecular patterns (DAMPs) molecules, are critical players of immune response to tissue suffering. In many inflammatory and autoimmune conditions, alarmins are released into the extracellular milieu and bind to specific receptors to stimulate and promote activation of innate immune cells, cell differentiation, cell death or secretion of inflammatory mediators. This paper, based on biochemical and mass spectrometry proteomic data, highlights the role of heat shock proteins (HSPs), high-mobility group box 1 (HMGB1) protein and S100 proteins as main alarmins involved in the maintaining and amplifying inflammation in atherosclerosis, diabetes and cancer. Biological significance: This paper, based on biochemical and mass spectrometry proteomic data, highlights the role of the heat shock proteins (HSPs), high-mobility group box 1 (HMGB1) protein and S100 proteins as main alarmins involved in maintaining and amplifying atherosclerosis, diabetes and cancer inflammation. © 2016 Elsevier B.V. All rights reserved.

Contents 1. 2. 3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Proteomic technologies used for the research of alarmins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Clinical functions and medical importance of alarmins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Alarmins and the atherosclerotic plaque progression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Chronic hyperglycemia generates a systemic inflammatory status and proteomic alteration of membrane microdomains . 3.3. Alarmins and cancer associated inflammation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abbreviations: HSPs, heat shock proteins family; HMGB1, high-mobility group box 1; PRR, pattern recognition receptor; PAMP, pathogen-associated molecular pattern; CAD, coronary artery disease; SMC, smooth muscle cells; RAGE, receptor for advanced glycation end products; Cy, cyanine; DPP-IV, dipeptidyl peptidase IV; IMS, imaging mass spectrometry; RCC, renal cell carcinoma; qXL-MS, quantitative cross-linking mass spectrometry; SILAC, stable isotope labeling by amino acids in cell culture; SRM, selected reaction monitoring; FA, follicular adenoma; FTC, follicular thyroid carcinoma; PTC, papillary thyroid carcinoma; PRM-MS, parallel reaction monitoring mass spectrometry; IM-MS, ion mobility-mass spectrometry; MRM, multiple reaction monitoring; AQUA, absolute quantification; NP, nanoparticles; AuNP, gold nanoparticles; MudPIT, multidimensional protein identification technology; HILIC, hydrophilic interaction chromatography; HCC, hepatocellular carcinoma; ApoE, apolipoprotein E; DRM, detergent-resistant membrane; RaftProt, lipid raft proteome; UniProt, universal protein resource; KEGG, Kyoto Encyclopedia of Genes and Genomes; Akt, protein kinase B; PI3K, phosphatidylinositol-4,5-bisphosphate 3-kinase; Sp1, specificity protein 1; NF-kB, nuclear factor kappa-light-chain-enhancer of activated B cells; COX2, cyclooxygenase 2 protein; HIV, human immunodeficiency virus; PDAC, pancreatic ductal adenocarcinoma; BXPC3, human primary pancreatic adenocarcinoma cell line. ⁎ Corresponding author at: Institute of Cellular Biology and Pathology “N. Simionescu”, 8, B.P. Hasdeu Street, PO Box 35-14, 050568 Bucharest, Romania. E-mail address: [email protected] (F. Antohe).

http://dx.doi.org/10.1016/j.jprot.2016.11.006 1874-3919/© 2016 Elsevier B.V. All rights reserved.

Please cite this article as: R.M. Boteanu, et al., Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer, J Prot (2016), http://dx.doi.org/10.1016/j.jprot.2016.11.006

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1. Introduction

2. Proteomic technologies used for the research of alarmins

The living cells are equipped with efficient mechanisms that maintain the functional homeostasis while being in permanent communication with the extracellular environment. There are regulatory proteins forming complex macromolecular structures embedded in biomembranes that assure the compartmentalization of the cells and tissues. These semipermeable barriers maintain a favourable microenvironment so that specific biochemical reactions take place in different temporal and spatial locations. Under various stress factors, the induced structural and/or functional modifications are followed by dysfunctions of the cells, tissues, organs and finally of the entire body that may lead to severe pathological conditions and sometimes toward a fatal outcome. These events are accompanied by an inflammatory response which reduces further damage, remove cellular debris and promote healing. Sterile inflammation following cellular stress or injury is initiated when pattern recognition receptors (PRRs) or damage-associated molecular patterns (DAMPs) specific receptors of resident immune cells recognize endogenous molecules (alarmins, DAMPs) released from necrotic, stressed or immunogenic apoptotic cells, as danger signals [1]. So far, there have been no clear differences recognized between alarmins and DAMPs. However, the definition of DAMP molecules is sometimes used to designate both endogenous alarmins and exogenous molecules called pathogen-associated molecular patterns (PAMPs), which are also recognized by PRRs [2]. Since alarmins are potent mediators of inflammation, understanding and modulating their activity may offer a new approach in controlling the inflammatory processes of numerous disorders. The modern medicine, recently called precision medicine, aims to rapidly translate basic research results toward clinical applications for an early diagnosis and personalized therapy of each patient. This strategy is closely supported by the unprecedented technological development of the biomedical research. Thus, classical biochemical, immunological and microscopy imaging methods have been extended by high performance structural and functional mass spectrometry (MS) based proteomics methodologies. Through a relevant clinical and surgical laboratory sampling it is possible to generate essential correlations in control versus pathological conditions and in the most favourable situations to identify valuable molecular markers for both diagnosis and personalized treatment. Alongside genes, proteins are key entities that generate a high variability and diversity of living organisms and are also the effectors of all biological functions. The major advantages offered by mass spectrometry-based proteomic research include its extreme sensitivity, mass accuracy and resolution (b1 fmol, b 1 ppm and N1,000,000, respectively) accompanied by the possibility to analyze protein mixtures of a high complexity in minute amounts of sample. Therefore, we took advantage of these powerful properties to evaluate the expression of alarmins released under various stress factors (including hyperlipidemic diet, hyperglycemia, or other unknown insults that generate cancer) in different experimental biological systems (cells in culture, small animal models and human tissue samples). Alarmins are multifunctional and unrelated structural endogenous molecules but competent to activate immune cells following the interaction with their specific receptors during host defence and tissue repair [3]. In homeostatic conditions, alarmins are located in many cellular compartments such as the nucleus (e.g. nucleolin, HMGB1, galectin-3), cytoplasm (e.g. HSPs, annexins, HMGB1, S100P, galectin-3), mitochondrion (e.g. galectin-3), cell matrix (e.g. hyaluronan, fibronectin, galectin-3) or can be stored in granules (e.g. α-defensins, cathelicidin, S100A12). Based on their features: a rapid release during necrosis, sequestration in apoptosis, secretion by stimulated immune cells and capability to restore homeostasis, these molecules were grouped into the alarmins family [4]. The aim of this paper was to give a brief overview of the complex implications of selected DAMPs in some chronic diseases including both published and recent new data of our group.

Proteomic approaches used to study proteins in different diseases have been extended over the years from classical techniques to complicated technologies, thanks to the developments of new instrumentation and bioinformatics tools which have made possible the transition from the analysis of a single molecule at a time to a complete analysis of the proteome. In this chapter, we present a brief overview of currently available proteomic technologies that provide relevant information about alarmins in chronic noncommunicable diseases. Two dimensional polyacrylamide gel electrophoresis (2DE) coupled to matrix assisted laser desorption ionization tandem time of flight (MALDI-TOF/TOF) mass spectrometry is a powerful classical proteomic methodology for the study of macromolecules. A relatively high tolerance of MALDI to contaminants still makes it a valuable technique that most often complements other approaches with different ionization principles. The combination of these technologies was applied in a study from 2013, which was focused on the isoproterenol induced cardiac hypertrophy rat model. The results revealed 16 differentially abundant proteins out of a total of 37 identified ones, the heat shock proteins (Hsp60, Hsp70 and HspD1) category being increased in the cardiac hypertrophy rat model in comparison to controls [5]. The same methodology was used for the analysis of monocytes isolated from peripheral blood mononuclear cells of coronary artery disease (CAD) patients. Therefore, several attractive biomarker candidates in the pathogenesis of atherosclerosis, such as Hsp70 and S100A8 alarmins, were identified [6]. A study from 2007, employing the separation of proteins using 2DE followed by liquid chromatography electrospray tandem mass spectrometry (LC-ESI MS/MS) analysis, showed that S100A4 is a marker of porcine rhomboid smooth muscle cells (SMC) in both in vitro and in vivo intimal SMCs, in pigs and humans [7]. The authors speculated that the analysis of its mechanisms of interaction with receptor for advanced glycation end products (RAGE) should be useful to better understand the evolution of atherosclerosis and restenosis processes. 2DE followed by MALDI-TOF MS was also employed for studying pentoxifyline, a non-specific phosphodiesterase inhibitor, utilised for the treatment of vascular diseases [8]. The analysis was performed on proteins extracted from peripheral blood mononuclear cells isolated from CAD patients and revealed that the administration of pentoxifyline decreased the protein level of S100A9, suggesting a drop in the induction of neutrophil/monocyte migration and subsequent reduction of inflammation. A significant improvement of 2DE methodology has been the introduction of Cy reactive dyes used for the protein labeling prior to the separation by isoelectric focusing. This has the extraordinary benefit of increased sensitivity in detection and reproducibility over the classical approach. Two-dimensional differential gel electrophoresis (2D-DIGE) followed by nanoLC hybrid Orbitrap mass spectrometry were applied in the study of carotid atherosclerotic plaques of human endarterectomy samples [9]. One of the 19 significantly regulated proteins in different carotid segments was S100A10 that facilitates the generation of plasmin and may regulate the degradation of extracellular matrix in advanced atherosclerotic plaques. In another study, MALDITOF MS was used to search the action of dipeptidyl peptidase IV (DPPIV) on HMGB1 in diabetic conditions [10]. The proteomic workflow revealed that DPP-IV activity was enhanced in the plasma of type 2 diabetes patients, while the mass spectra analysis established the existence of a circulating form of HMGB1 (lacking its N-terminal region), suggesting that DPP-IV inhibitors may enhance HMGB1 function not only in vitro but also in diabetic patients. Mass spectrometry imaging is a relatively novel methodology for histological analysis, based on the chemical organization of tissues from various samples. The combination of MALDI-imaging mass spectrometry (IMS) and LC-ESI MS/MS recently evidenced an increased level of S100A11 in papillary renal cell carcinoma (RCC) [11]. The authors concluded that the combined use of MALDI-IMS and LC-ESI-MS/

Please cite this article as: R.M. Boteanu, et al., Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer, J Prot (2016), http://dx.doi.org/10.1016/j.jprot.2016.11.006

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MS would be beneficial in developing novel histological biomarkers or protein signatures to discriminate different subtypes of RCCs. An exciting proteomic methodology used for the investigation of DAMP dynamics is based on a combination of mass spectrometry with protein cross-linking (XL-MS). This is an evolving structural biology technique that offers information on the molecular structure of proteins and protein complexes using chemical probes which report on the vicinity of interaction of two residues [12]. Quantitative XL-MS (qXLMS) uses a combination of XL-MS with quantitative proteomics experiments to provide information regarding conformational changes in proteins, as well as interactions caused by different conditions or perturbations [13]. A recent study using qXL-MS has provided a structural insight into the dynamics of Hsp90 conformation in cells upon inhibition with 17-N-allylamino-17-demethoxygeldanamycin, XL-888 and novobiocin [14]. SILAC is a well-established stable isotope metabolic labeling technique for mass spectrometric based quantitative proteomics that permits an unbiased quantification of cellular proteins that differ between two conditions [15]. A recent evidence concerning S100 proteins abundance was obtained using SILAC and label-free selected reaction monitoring (SRM) mass spectrometric approaches [16]. The applied proteomic workflow established the first global picture of S100 protein expression in the three most common tumors of the thyroid gland: follicular adenoma (FA), follicular thyroid carcinoma (FTC) and papillary thyroid carcinoma (PTC). These mass spectrometric methods allowed expanding the number of targeted S100 protein isoforms. Although the SILAC quantitation was more precise than the label-free experiments, both approaches identified the same significant changes in the tissue samples. The study provided a novel observation of increased S100A13 in PTC compared with FA, FTC and normal thyroid tissues. This was supported by immunoblot experiments and transcriptomics [16]. The complex methodology also demonstrated that S100A6, S100A11 and annexin A1 differentiate PTC from follicular tumors. SILAC was also performed on metastatic breast cancer cell lines, while high-resolution accurate mass MS was employed in order to identify and quantify the labeled proteins [17]. This study showed that S100A4 was strongly down-regulated (by 26-fold), suggesting a relationship to the brain metastatic capability of breast cancer cells. The protein changes were further validated using the novel parallel reaction monitoring mass spectrometric (PRM-MS) methodology applied to the non-labeled proteins. An emerging MS-based approach is the ion mobility-mass spectrometry (IM-MS). This is a rapid method of analysis, requiring little sample preparation, but offering the flexibility to include pre-ionization separations, making it suitable for holistic studies of complex biological systems. IM-MS is a two-dimensional separation, which combines gasphase ion mobility structural separations with the well-known massto-charge (m/z) ratio separations of mass spectrometry. A relatively recent study demonstrated the use of IM-MS in identifying biomolecular signatures of diabetic wound healing [18]. Wound exudates were collected from diabetic and non-diabetic rats and were analyzed by IMMS after a minimal sample preparation. Distinctive biomolecular signatures for diabetic and non-diabetic wound fluids were revealed by IMMS, which also demonstrated different proteomic patterns of samples collected at two time points. The statistical analysis revealed four species distinguishing diabetic from control wound fluid, including S100A8 [18]. Recently, stable isotope-based quantitative mass spectrometric analyses have made breakthroughs in various fields of research. The ultrasensitive and high-throughput properties of isobaric tags for relative and absolute quantitation (iTRAQ) coupled with two-dimensional LCMS/MS analysis have propelled this methodology as one of the most reliable analysis to date. Due to the ongoing requirement for clinical biomarkers for early detection and therapeutic targets of laryngeal carcinoma, Zha and collaborators utilized the iTRAQ method to analyse differentially expressed proteins between laryngeal carcinoma and

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non-tumor samples, revealing the overexpression of S100A2 (N12 fold increase over the control) and HSPB1 (N 8 fold increase over the control) [19]. Multiple reaction monitoring (MRM) is the gold standard mass spectrometric method for absolute quantitative measurement of target proteins using stable isotope labeled AQUA (absolute quantification) standard peptides. It has been a principal tool for quantification of small molecules in clinical chemistry for a few decades and its extreme specificity, sensitivity, multiplexing characteristic and precision drove MRM implementation into biomarker discovery by proteomics. The methodology was successfully implemented in order to quantify the expression of 80 key signaling proteins in melanoma cell line including Hsp71, Hsp90α and Hsp90β alarmins [20]. A different quantitative mass spectrometric approach was used for the first time to demonstrate that DNA-conjugated gold nanoparticles (NP) have great potential to capture proteins recognizing DNA lesions by anticancer drugs in vitro [21]. The sensitivity of the mass spectrometric analysis was greatly enhanced when microscale HPLC was initially applied to fractionalize the proteolyzed molecules interacted with AuNP probes, and then separated by nanoLC prior to quadrupole time of flight (q-TOF) mass spectrometric analysis of light and heavy stable isotope labeled samples. The study successfully identified HMGB1 in response to platination of DNA by cisplatin and concluded that mass spectrometric sensitive identification of proteins responding to platinumdamaged DNA could be succeeded in the physiologically relevant environment. In 2013, an investigation of exudates from type 2 diabetes induced chronic wounds demonstrated a dramatic impairment in wound repair with excessive inflammation, antiangiogenic environment and accelerated cell death of patients suffering from a chronic foot ulcer [22]. Multidimensional protein identification technology (MudPIT) coupled to high resolution mass spectrometry was performed by combining reversed-phase with strong cation exchange chromatography before the analytical peptide separation. The label free mass spectrometric quantification analysis was based on spectral counting and revealed the overall up-regulation of S100A8, S100A9, S100A4, S100A11, S100A12 and S100P proteins in the diseased subjects [22]. In a recent study on esophageal squamous cell carcinoma patients, high resolution LC-MS was used to demonstrate the link between the DNA repair molecule HMGB1 and the regulator protein 14-3-3σ. The authors encountered a promising therapeutic effect of the later protein for counteracting cisplatin resistance [23]. Hydrophilic interaction chromatography (HILIC) coupled to reversed phase nanoLC-MS/MS analysis was performed for the separation and analysis of stable isotope dimethyl-labeled urinary proteins of hepatocellular carcinoma (HCC) patients for the identification of potential biomarker candidates [24]. The study revealed the co-amplification and co-expression of S100A9 and granulin proteins, pinpointing their potential combinatorial biomarker capacity for early detection of HCC. Taken together, all these applications of different proteomic approaches in the study of alarmins prove the immense potential of current proteomic methods to emphasize significant predictors for clinical prognostic of chronic noncommunicable diseases. 3. Clinical functions and medical importance of alarmins 3.1. Alarmins and the atherosclerotic plaque progression Vascular diseases are the leading cause of disabilities, morbidity and mortality in the developed societies. One of the main manifestations is atherosclerosis, a chronic inflammatory disease characterized by the accumulation of oxidized and modified lipoproteins, foam cells and fibrous tissue in the arterial walls [25]. Initially considered an irreversible process, the generated atherosclerotic plaques present a remarkable dynamics under diet, physical exercises, smoking, beside the genetic heritage. Early action on the risk factors can reverse the atherogenic process and transform the plaque into a stable, dormant lesion.

Please cite this article as: R.M. Boteanu, et al., Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer, J Prot (2016), http://dx.doi.org/10.1016/j.jprot.2016.11.006

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Fig. 1. Representative two dimensional gel electrophoresis images of detergent resistant membrane microdomains isolated from lung homogenates. The 5.5–5.9 ± 0.1 isoelectric point (pI) and 50–60 ± 5 kDa molecular weight (MW) domains reveal changes in the protein spots intensities isolated by the discontinuous sucrose gradient ultracentrifugation of control (a), hyperlipidemic (b) and fluvastatin treated hyperlipidemic (c) experimental groups. Arrows indicate the altered abundance of numerous protein spots in the different experimental conditions. Protocol details can be found in Supplementary material SM1: 2D-DIGE Procedures.

Alarmins involved in the atherosclerotic process include but are not limited to HSPs [26–29], galectin-3 [30], HMGB1 [31–33], interleukin1α [34], α-defensins [35], annexin 1 [36], and S100 proteins [37,38]. Among these, HSPs are best studied; the first data about them were generated long before their inclusion in the alarmins family. Berberian et al. [28] described for the first time the presence of large amounts of Hsp70 in the atherosclerotic plaque of human blood vessels. Interestingly, high concentrations of Hsp70 are co-localized with infiltrated macrophages specifically located in the areas of necrotic vessel wall. In these pathological tissues, besides Hsp70, increased concentrations of Hsp60, Hsp90 and Hsp27 were found [39]. Exposure of endothelial cells in culture to high lipid conditions led to the formation of foam cells [40], identified also in the late stages of an experimental atherosclerosis in hamsters and rabbits [25]. In addition, endothelial cells loaded with lipid droplets become activated and express high levels of heat shock proteins (Hsp27, 70 and 90), demonstrating the triggered response to severe insults [40]. Moreover, our results showed that during the hyperlipidemic stress, the HSPs' (Hsp70 and 90) relative tissue levels were correlated with the amount of HSPs secreted into the serum under the positive active regulatory role of caveolin 1, located in the membrane microdomains of ApoE−/− mice [41]. Biological membranes are heterogeneous lipid bilayers containing mosaics of specialized microdomains (fenestrae, caveolae, lipid rafts) that are often the target of intra- or extracellular stimuli affecting their dynamics, biochemical composition or signal transduction. Using the 2DE, we found quantitative changes both in endothelial-derived foam cells in culture [42,43] and in detergent–resistant membrane microdomains (DRMs) isolated from lung tissue of hyperlipidemic hamsters (our unpublished data, Fig. 1). Our mass spectrometry evaluation of DRMs isolated from hyperlipidemic animals exposed or not to fluvastatin versus control, consolidates our previous results regarding the severe alteration of DRMs protein composition [41]. This evidence supports our hypothesis that caveolae interact closely with the cytoskeleton and other structural proteins including actin, annexin II, filamin A and dynamin regulating the transport of macromolecules and the budding dynamics of caveolae under stress conditions [41,44]. Besides annexin II, in the isolated DRMs [44] other alarmins such as galectin-3, annexin A1 and histones H1 and H4 were identified. These molecules exhibited high abundance values in both hyperlipidemic and fluvastatin treated animals when compared to appropriate controls (see Table 1 containing the list of

alarmins extracted from our published data [44]). The results proved once again the complex inflammatory environment generated by hyperlipidemia, a major risk factor for atherosclerosis. Parts of the published data of our group [41] were already included in a recent lipid raft proteome database (RaftProt: mammalian lipid raft proteome database [45]), which contains various biochemical and mass spectrometry analytical methods and high confidence (validated) DRM protein molecules in various conditions. Since the membrane nano-structures are extremely dynamic entities, involved in cholesterol homeostasis and intracellular vesicular trafficking, the proteomic analysis was further pursued by our group to evaluate the modulation of membrane-cytoskeleton proteome induced by hyperlipidemic stress. The therapeutic effect of statin medication in the experimental atherosclerotic ApoE−/− model was evaluated qualitatively and quantitatively against the wild type C57 Black mice as control (Fig. 2). The bioinformatics processing of the raw spectral data allowed the identification with high confidence of 1925 proteins of membrane, cytoskeletal and cytosolic origin, mainly involved in molecular interactions [44]. 291 of them presented statistically significant altered abundances when compared with the control group and were found to be involved in 13 Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. The close interaction between the membrane macromolecular complexes and cytoskeletal elements revealed 29 of these proteins to be involved in three signaling pathways (Regulation of the actin cytoskeleton, Focal adhesion and Adherens junction) at the interface of membrane-cytoskeletal complexes that assure the energy and dynamism to the reactivity actions of the stimulated cells. In this particular case the data offered a close analytical inside to the interactions between the membrane proteins and cytoskeleton components under hyperlipidemic stress and the effect of statin therapy [44]. The panel of the identified proteins proved to be of interest in hyperlipidemia and may be used to address new research studies related to the protein-protein interactions in atherosclerotic plaque progression. Numerous studies indicate that HMGB1 has a significant role in atherosclerosis. For example, high levels of HMGB1 were detected in endothelial cells, smooth muscle cells, foam cells, macrophages and activated platelets in atherosclerotic lesions originated from both human autopsy samples and experimental animals' tissues [46]. Moreover, HMGB1 induces smooth muscle cell chemotaxis [31], enhances the expression of vascular adhesion molecules in endothelial cells and transduces cellular

Table 1 Relative abundances of MS-identified alarmins located in DRM microdomains with the corresponding UniProt accession codes, median Mascot scores, and p and standard deviation (SD) values. H: hyperlipidemic animals; Ht: fluvastatin treated animals and C: control animals. UniProt access key

Description

Median Mascot score

H/C ratio

H/C SD

H/C p-value

Ht/C ratio

Ht/C SD

Ht/C p-value

P16110 P10107 P19324 P62806 P43274

Galectin-3 Annexin A1 Serpin H1 Histone H4 Histone H1.4

35.82 1121.1 118.91 522.93 281.66

0.887 0.497 1.395 1.761 1.893

0.299 0.018 0.121 0.128 0.284

0.4341 9.9E-20 1.857E-05 4.507E-10 0.001

2.678 1.381 1.833 1.822 3.388

0.664 0.047 0.116 0.128 0.587

0.0009 1.110E-16 9.602E-11 4.087E-10 0.0036

Please cite this article as: R.M. Boteanu, et al., Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer, J Prot (2016), http://dx.doi.org/10.1016/j.jprot.2016.11.006

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Fig. 2. Graphical workflow representation of the proteomic analysis using high performance Easy nano-LC II LTQ Orbitrap Velos Pro equipment (Thermo Scientific). Discontinuous sucrose gradient ultracentrifugation was applied to 3 sets of samples: control C57 Black mice, ApoE−/− fed with hyperlipidemic diet and ApoE−/− mice which received a statin treatment following a high fat diet. The samples were suitably processed for LC-MS/MS analysis. Following mass spectra acquisition a Mascot search was employed and ion precursor intensity comparison based relative quantification was assessed. The signaling pathways over-representation revealed that 29 differentially abundant proteins were part of the Regulation of the actin cytoskeleton, Focal adhesion and Adherens junction inter-relation maps.

signals through RAGE and toll-like receptors [47–50]. Clinical studies showed that high serum levels of HMGB1 were detected in patients with coronary artery diseases [51], pulmonary hypertension [52], cerebral vascular ischemia and acute myocardial infarction [53]. In experimental hyperlipidemia, we also reported an increased expression of HMGB1 in serum, lung and cardiac tissue [54,55]. Indeed, the enhanced expression of HMGB1 in hyperlipidemia is related to the up-regulation of RAGE, in association with AKT1 phosphorylation. Fluvastatin treatment resulted in a significant reduction of HMGB1, RAGE and AKT1 phosphorylation enhancement in various tissues [54,55]. Both HMGB1 and PI3K/AKT pathway can regulate the activity of Sp1 [56] or NF-kB [57] transcription factors, which can induce the production of RAGE and other cytokines, as demonstrated by others [58]. Based on all these experimental indications, we proposed a feedback loop action of

HMGB1 that amplifies the initial signal and further enhances inflammation in hyperlipidemia (Fig. 3). These mechanisms might lead to the progressive long term development of atherosclerotic lesions, as described by Haraba et al. [55]. The experimental data also demonstrated a new therapeutic effect of statin therapy in hyperlipidemia mediated by HMGB1 down regulation [54,55]. The results were also sustained by our in vitro experiments in which the hyperlipidemic serum activates monocytes (U937 cells) causing the translocation of HMGB1 from nucleus to cytosol followed by the subsequent secretion into the microenvironment [55], maintaining the pro-inflammatory status. In this regard, recent data [59] demonstrated that HMGB1 is an active regulator of the vascular barrier that modulates the expression of specific adhesion molecules on the endothelial cells surface causing a particular adhesiveness behaviour of the monocytes and macrophages. 3.2. Chronic hyperglycemia generates a systemic inflammatory status and proteomic alteration of membrane microdomains

Fig. 3. Schematic representation of possible HMGB1 signaling events at cellular level under hyperlipidemic stress. HMGB1 (high mobility group box 1); RAGE (receptor for advanced glycation end products); AKT1 (protein kinase B); PI3K (phosphoinositide 3-kinase); NFkB (nuclear factor kappa-light-chain-enhancer of activated B cells).

Systemic inflammation in diabetes leads toward metabolic and chronic complications. Experiments performed by our group on mice subjected to streptozotocin-induced diabetes showed that hyperglycemia drastically affects the morphological aspect of endothelial cells, displaying a higher number of plasmalemmal vesicles (caveolae) and the ensuing larger endothelial surface, prone to interaction with circulating macromolecules [60]. Moreover, our LC-MS/MS experiments performed on genetically induced diabetes mellitus versus control mice [61] identified 1748 proteins in the detergent resistant membrane microdomains (DRM), of prevalent membrane (~ 20%), extracellular (~12%) and nuclear origin (~10%) that are involved mainly in catalytic activity, metabolic processes and transport in close interactions with other proteins and nucleotides. In addition, the analysis showed (Fig. 4) that hyperglycemia has a regulatory consequence on the spectral abundance of alarmins, such as annexin A1, histone H4, HSPs, S100A6 and S100A9 proteins (our unpublished results shown in Supplementary material SM2 and SM3). Eight ribosomal proteins that co-fractionated with DRMs also presented an abundance alteration [61], implying the involvement of novel signaling pathways in the diabetic lung. Similar ribosomal proteins were described to be implicated in various cancer associated inflammation studies [62–67] that make our reported results encouraging since they open up new strategies to address the silent microvascular degeneration accompanying the diabetes mellitus.

Please cite this article as: R.M. Boteanu, et al., Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer, J Prot (2016), http://dx.doi.org/10.1016/j.jprot.2016.11.006

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Fig. 4. Differential abundance of alarmins in DRM microdomains isolated from genetically induced diabetic mice (D) relative to the control group (C). Four members of the HSPs (a) and two of the S100 (b) families were clearly more abundant in the diabetic animals than in the control group. Note the statistically significant decreased abundance of the Histone H4 and Annexin A1 proteins (b). The means of the relative ratio of diabetic (D) over control (C) were calculated in GraphPad Prism with 95% confidence intervals. Extensive data are presented in Supplementary materials SM3: Quantification parameters of proteins extracted from DRM microdomains of control and diabetic mice.

Insulitis, the inflammation of the pancreatic islets, is characterized by β cells damage followed by progressive loss of insulin production. Damaged pancreatic beta-cells can passively release HMGB1 that activates immune cells which in turn initiate an autoimmune response. Moreover, islet infiltrated immune cells actively secrete HMGB1, leading to its accumulation and therefore the accelerated onset of type 1 diabetes [68]. Serum HMGB1 levels are elevated in both patients with type 1 and 2 diabetes and high levels have been found in the retinas of diabetic patients with retinopathy [69,70] and in the kidneys of diabetic rats [71]. Our novel data showed that HMGB1 presented a higher expression both at protein and gene level in pulmonary tissue harvested from diabetic versus control animals [72]. Moreover, the co-immunoprecipitation demonstrated the interaction of HMGB1 and its receptor RAGE, while the immunotransfer experiments evidenced an increased level of PI3K and elevated Thr phosphorylation of AKT kinase in the position 308. NF-kB and β-catenin, both involved in the biosynthesis of

many inflammatory proteins including RAGE and COX2, presented higher abundances in diabetic versus control animals. HMGB1 and β-catenin were also clearly identified by mass spectrometry in the analyzed samples with high confidence Mascot scores (N 200) [72], validating the reported data. Thus, the results support the concept of an inflammatory process in the lungs of diabetic mice, underlining the associated dysfunctions in the pulmonary tissue. 3.3. Alarmins and cancer associated inflammation MS-based proteomics is now widely used to unravel differences at molecular level in various diseases such as HIV [73] and other virus infections [74], neuroendocrine diseases [75] and in particular, cancer [76]. Cancer and inflammation are closely connected since tumor development requires a special microenvironment that seems to be secure

Fig. 5. Mass spectrometry relative quantification of 7 members of the S100 protein family in human pancreatic cancer. The mean of the normalised ratios of tumor (T) over non-tumor (NT) tissue protein abundances were calculated in GraphPad Prism with 95% confidence intervals (Supplementary material SM5: Quantification parameters of proteins extracted from tissue samples of 15 patients with pancreatic ductal adenocarcinoma from both tumor and non-tumor fragments). The experimental approach used in these procedures is presented in Supplementary material SM1: Mass Spectrometry Procedures (a). Protein interaction network generated with STRING 10 software for S100 proteins and their predicted functional partners in pancreatic cancer. The figure shows different coloured lines representing the types of association between the proteins (b).

Please cite this article as: R.M. Boteanu, et al., Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer, J Prot (2016), http://dx.doi.org/10.1016/j.jprot.2016.11.006

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response to TNF-α treatment (Fig. 6 and Supplementary material SM7). TNF-α plays an important role in tumor progression and it is a significant predictor of pancreatic cancer invasion and metastasis [85]. Several studies showed that the angiogenic potential of TNF-α in cancer is dose dependent. A high concentration of TNF-α inhibits angiogenesis while low TNF-α levels increase tumor growth and cause angiogenesis in various mice tumors [86]. Interestingly, S100A11, S100A7 and S100P were among the 284 proteins identified in the culture medium collected from confluent BxPC-3 cells incubated in serum-free medium for 24 h (our unpublished results shown in Supplementary material SM8). These outcomes highlight once again that S100 proteins are important players in cancer and primarily that some of S100 proteins are released in the culture medium, as possible predictors of the TNF-α induced angiogenesis.

Fig. 6. The relative quantification of S100 proteins in TNF-α stimulated BXPC-3 cells. The stimulated (T) over the unstimulated (C) cells' spectral intensity ratio (higher than 1.5 or lower than 0.67) was used to evaluate the relative abundance of S100P, A2, A9, A11 and A16 proteins (Supplementary material SM7: Quantification parameters of proteins extracted from TNF-α stimulated and unstimulated human primary pancreatic adenocarcinoma BXPC-3 cells). Data are presented as mean ± SD, **p b 0.01, ***p b 0.001. The experimental approach used in these procedures is presented in Supplementary material SM1: Mass Spectrometry Procedures.

by an intrinsic inflammatory response [77]. In cancer cells, activation of different classes of oncogenes drives the expression of inflammation-related programs that guide the construction of an inflammatory milieu through recruitment of leukocytes, expression of tumor-promoting chemokines and cytokines and activation of angiogenesis [77,78]. The release of alarmins, such as HMGB1, by necrotic cell death at the hypoxic core of the tumor can also secure the inflammatory microenvironment [79] and further promote the tumor growth and invasiveness [80]. On the other hand, recent studies have revealed that alarmins released by dying cancer cells subjected to a subset of anticancer treatments can improve the antitumor immune response [81]. This type of cell death was called immunogenic cell death and is characterized by the secretion, release or surface exposure of DAMPs such as HMGB1, calreticulin, Hsp70 and Hsp90 [82]. Other alarmins such as S100A8, A9 and A12 are also involved in many aspects of tumor growth, angiogenesis, metastasis and inflammation-mediated carcinogenesis [83,84]. Moreover, the S100 protein family is often associated with various forms of cancers, but the molecular mechanisms are still elusive. We quantified the abundance (unpublished results) of these molecules in human tissue samples collected during the surgery of 15 patients with pancreatic ductal adenocarcinoma (PDAC), from both the tumor (T) and non-tumor (NT) control adjacent fragments. Twelve members of S100 family (A4, A6, A8, A9, A10, A11, A12, A13, A14, A16, P and B) were identified with high confidence in the investigated samples (Supplementary material SM4). Relative quantification bioinformatics analysis revealed an increased spectral abundance in 14 out of 15 (93%) cases of PDAC for S100P, 12 out of 15 (80%) for S100A8, 11 out of 15 (73%) for S100 A11, 10 out of 15 (63%) for S100A9 and A10 and 9 out of 15 (60%) for S100A4 and A6 (Fig. 5 and Supplementary material SM5). Notably, this first screening of S100 proteins in the tissue of Romanian patients with pancreatic ductal adenocarcinoma indicated that the proteins S100P, A4, A6, A8, A9, A10 and A11 could represent reliable potential biomarker candidates in the diagnosis of pancreatic cancer. In vitro experiments performed on human primary pancreatic adenocarcinoma BXPC-3 cell line stimulated with 10 ng/ml tumor necrosis factor-α (TNF-α) for 48 h revealed that five members of the S100 protein family presented an altered abundance (our unpublished results shown in Supplementary material SM6). Thus, the mass spectrometric analysis showed an increased abundance of S100A9 and S100A16 proteins in TNF-α stimulated BXPC-3 cells compared to the control. Unlike these, the S100A11, S100A2 and S100P proteins were less abundant in

4. Conclusions The results presented here add new lines of evidence based on MS research of the active and complex involvement of alarmins in the inflammatory processes that accompany the immune response in different chronic diseases. The data complement and also support the recently published ‘DAMP Hypothesis’ [87] that underlines the multiple functions of these proteins acting as inducers, sensors and mediators of inflammation by interacting either with plasma membrane or intracellular receptors. The pattern of alarmins and signaling pathways activated in particular situations are closely related to certain types of diseases and evolution characteristics of each patient. MS together with powerful bioinformatics will allow in the near future the smart exploitation of generated data for efficient use in clinics for the benefit of early diagnosis and in particular of each patient. The supplementary data associated with this article contain one supplementary file (SM1) which details the applied methodologies (2-DE Procedures and Mass Spectrometry Procedures); four mass spectrometric identification lists (SM2, SM4, SM6 and SM8 with the proteins identified in diabetic mice tissue, PDAC human tissue fragments, BXPC3 cells and culture medium, respectively) and three files that present additional results of label free relative quantification of the analyzed proteins (SM3, SM5 and SM7 for the mice tissue, PDAC human tissue fragments and BXPC3 cells respectively). Supplementary data associated with this article can be found in the online version, at 10.1016/j.jprot.2016.11. 006. Conflict of interest Raluca M. Boteanu and Viorel I. Suica contributed equally to this work. The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported. The Western blotting illustration in Graphical abstract was reproduced by permission from [54]. Acknowledgments We thank Dr. Madalina Oppermann from Thermo Scientific, for valuable collaboration. The excellent technical assistance of Mrs. Mariana Pascu was highly appreciated during the development of the project. The present work was supported by the Romanian Academy and Ministry of Education and Research grants CNDI-UEFISCDI [PN-II-PCCA-20112 nos.: 90, 135 and 153/2012]. References [1] G.Y. Chen, G. Nuñez, Sterile inflammation: sensing and reacting to damage, Nat. Rev. Immunol. 10 (2010) 826–837. [2] S. Hirsiger, H.P. Simmen, C.M.L. Werner, G.A. Wanner, D. Rittirsch, Danger signals activating the immune response after trauma, Mediat. Inflamm. 2012 (2012) 315941.

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Please cite this article as: R.M. Boteanu, et al., Alarmins in chronic noncommunicable diseases: Atherosclerosis, diabetes and cancer, J Prot (2016), http://dx.doi.org/10.1016/j.jprot.2016.11.006