Top-Down Proteomics of Human Saliva, Analyzed with Logistic Regression and Machine Learning Methods, Reveal Molecular Signatures of Ovarian Cancer.

Ovarian cancer (OC) is the most lethal of all gynecological cancers. Due to vague symptoms, OC is mostly detected at advanced stages, with a 5-year survival rate (SR) of only 30%; diagnosis at stage I increases the 5-year SR to 90%, suggesting that early diagnosis is essential to cure OC. Currently, the clinical need for an early, reliable diagnostic test for OC screening remains unmet; indeed, screening is not even recommended for healthy women with no familial history of OC for fear of post-screening adverse events. Salivary diagnostics is considered a major resource for diagnostics of the future. In this work, we searched for OC biomarkers (BMs) by comparing saliva samples of patients with various stages of OC, breast cancer (BC) patients, and healthy subjects using an unbiased, high-throughput proteomics approach. We analyzed the results using both logistic regression (LR) and machine learning (ML) for pattern analysis and variable selection to highlight molecular signatures for OC and BC diagnosis and possibly re-classification. Here, we show that saliva is an informative test fluid for an unbiased proteomic search of candidate BMs for identifying OC patients. Although we were not able to fully exploit the potential of ML methods due to the small sample size of our study, LR and ML provided patterns of candidate BMs that are now available for further validation analysis in the relevant population and for biochemical identification.

Profiling of differentially expressed proteins between fresh and frozen-thawed Duroc boar semen using ProteinChip CM10.

Many studies have been conducted to improve technology for semen cryopreservation in pigs. However, computer-assisted analysis of sperm motility and morphology is insufficient to predict the molecular function of frozen-thawed semen. More accurate expression patterns of boar sperm proteins may be derived using the isobaric tags for relative and absolute quantification (iTRAQ) technique. In this study, the iTRAQ-labeling system was coupled with liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis to identify differentially expressed CM10-fractionated proteins between fresh and frozen-thawed boar semen. A total of 76 protein types were identified to be differentially expressed, among which 9 and 67 proteins showed higher and lower expression in frozen-thawed than in fresh sperm samples, respectively. The classified functions of these proteins included oxidative phosphorylation, mitochondrial inner membrane and matrix, and pyruvate metabolic processes, which are involved in adenosine triphosphate (ATP) synthesis; and sperm flagellum and motile cilium, which are involved in sperm tail structure. These results suggest a possible network of biomarkers associated with survival after the cryopreservation of Duroc boar semen.

Selymatra: A web application for protein-profiling analysis of mass spectra.

Surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry is a variant of the matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. It is used in many cases especially for the analysis of protein profiling and for preliminary screening of biomarkers in complex samples. Unfortunately, these analyses are time consuming and protein identification is generally strictly limited. SELDI-TOF analysis of mass spectra (SELYMATRA) is a web application (WA) developed to reduce these limitations by (i) automating the identification processes and (ii) introducing the possibility to predict proteins in complex mixtures from cells and tissues. The WA architectural pattern is the model-view-controller, commonly used in software development. The WA compares the mass value between two mass spectra (sample vs. control) to extract differences, and, according to the set parameters, it queries a local database to predict most likely proteins based on their masses and different expression amplification. The WA was validated in a cellular model overexpressing a tagged NURR1 receptor, being able to recognize the tagged protein in the profiling of transformed cells. A help page, including a description of parameters for WA use, is available on the website.

Screening of serum protein biomarkers in hemorrhagic cerebral infarction by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology.

BACKGROUND: Serum samples of patients with hemorrhagic cerebral infarction (HCI), cerebral infarction (CI), and healthy controls (HCs) were used to screen statistically different protein peaks as potential biomarkers and to establish a decision tree classification model. METHODS: The serum samples from clinically confirmed patients with HCI and CI from November 2018 to October 2019 were collected, along with those of HCs who visited our hospital during the same period. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) with CM10 ProteinChip was used to analyze the differences in serum protein expression profiles of 30 patients with HCI, 32 patients with CI, and 31 HCs in the training group, and a decision tree classification model was established. At the same time, the blind test group (18 patients with HCI, 21 patients with CI, and 17 HCs) was tested by a blind method. RESULTS: Model 1 was successfully established by software analysis with a mass-to-charge ratio of 3,495.2, 8,941.0, and 15,890.4 as a differential protein peak. The sensitivity, specificity, and accuracy of model 1 in distinguishing HCI from HCs were 86.8%, 87.1%, and 86.9%, respectively. After verification of model 1 by the blind test group, the results showed that the sensitivity, specificity, and accuracy were 88.9%, 94.1%, and 91.4%, respectively. The sensitivity, specificity, and accuracy of model 2 with a mass-to-charge ratio of 2,941.3 as a differential protein peak were 86.7%, 75.0%, and 80.6%, respectively. After verification of model 2 by the blind test group, the results showed that the sensitivity, specificity, and accuracy were 83.3%, 90.4%, and 87.2%, respectively. CONCLUSIONS: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and CM10 ProteinChip can be used to screen serum protein markers in patients with HCI. Mass-to-charge ratio of 3,495.2, 8,941.0, 15,890.4, and 2,941.3 may be potential protein biomarkers of HCI and used to distinguish HCI patients from HCs and CI.

Nanoparticle-based surface assisted laser desorption ionization mass spectrometry: a review.

Great endeavors are undertaken to find effective nanoparticles to replace organic matrices for the analysis of small molecules using laser desorption ionization mass spectrometry (LDI-MS). Nanoparticles offer high sensitivity and better selectivity compared to conventional organic matrices. Surface assisted LDI-MS (SALDI-MS), and surface enhanced LDI-MS (SELDI-MS) provide clear background spectra without observable interferences peaks, and cause no fragmentation (soft ionization) of thermal and acidity labile molecules. This review article (with 460 references) summarizes the recent applications of nanoparticles including metallic, metal oxides, silicon, quantum dots, metal-organic frameworks and covalent organic frameworks, for the analysis of small molecules. Nanoparticles serve not only as surface for LDI-MS, but they can be also used as probe or pseudo-stationary phase for separation, enrichment, and microextraction. Hopefully, the knowledge and learning points gained from this review will deepen the understanding of nanoparticles applications for LDI-MS. Graphical Abstract Schematic representation of laser desorption ionization mass spectrometry using various nanoparticles (such as metallic nanoparticles, carbon nanomaterials, silicon based nanomaterials, metal oxides, quantum dots, metal-organic frameworks, and covalent organic frameworks). Advanced technologies using nanoparticles are also reviewed.

Serum protein expression patterns in detecting a new viral protein in HBeAg-negative chronic hepatitis B.

We analysed the changes in viral protein expression in HBeAg-negative chronic hepatitis B (CHB). In total, 160 samples were obtained from individuals infected by hepatitis B virus (HBV) and divided into four groups. Group A included 71 cases of hepatitis B e antigen (HBeAg)-negative CHB, Group B included 58 cases of inactive seroconverters and Group C included 31 cases of HBeAg-positive CHB. Group D included 22 normal healthy individuals as a control. All serum samples were examined using surface enhance laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS). The results indicated that a peak with 4140 m/z increased markedly in Group A at 1295.55 ± 745.87, which was significantly different from that in Group B at 896.99 ± 534.86 (P = 0.013). This peak indicated a close relationship with HBV DNA replication and may contribute to pathogenesis of HBeAg-negative chronic hepatitis.

Proteomic pattern of breast milk discriminates obese mothers with infants of delayed weight gain from normal-weight mothers with infants of normal weight gain.

We previously reported that exclusively breastfed infants born to mothers with pregestational obesity gain less weight during the first month after birth than those born to mothers of normal pregestational weight. This issue is potentially important since lower weight gain in breastfed infants of obese mothers might increase the risk of developing later obesity. Breast milk quality and quantity, together with breastfeeding practice, possibly influence infants' feeding behavior, appetite control, and regulation of growth later in life. The issue of whether breast milk protein patterns from obese mothers differ in composition from those of non-obese mothers remains largely unexplored. Here, we established a breast milk proteomic pattern that discriminates obese mothers and infants with delayed weight gain at 1 month after birth from normal-weight mothers with infants of the same age and with normal weight gain. Obese mothers were matched to normal-weight mothers (n = 26; body mass index 33.5 ± 3.2 vs 21.5 ± 1.5 kg·m-2). The mean weight gain of infants in the obese group at 1 month after birth was 430.8 g lower than that of the infants in the control group. Analysis of the breast milk delipidized fraction by surface-enhanced laser desorption/ionization on CM10 and Q10 arrays was followed by MS-assisted purification and LC-MS/MS microsequencing of a selected biomarker. We identified 15 candidate protein biomarkers, seven of which were overexpressed in the obese group and eight in the normal-weight group. One of the most significant candidate biomarkers, overexpressed in the obese group, was identified as a fragment of the sixth extracellular domain of the polymeric immunoglobulin receptor. Further structural identification of these candidate biomarkers and their validation in clinical assays may facilitate the development of a predictive immunoassay.

Identification of diagnostic upper gastrointestinal cancer tissue type-specific urinary biomarkers.

Several potential urinary biomarkers exhibiting an association with upper gastrointestinal tumour growth have been previously identified, of which S100A6, S100A9, rabenosyn-5 and programmed cell death 6-interacting protein (PDCD6IP) were further validated and found to be upregulated in malignant tumours. The cancer cohort from our previous study was subclassified to assess whether distinct molecular markers can be identified for each individual cancer type using a similar approach. Urine samples from patients with cancers of the stomach, oesophagus, oesophagogastric junction or pancreas were analysed by surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry using both CM10 and IMAC30 (Cu2+-complexed) chip types and LC-MS/MS-based mass spectrometry after chromatographic enrichment. This was followed by protein identification, pattern matching and validation by western blotting. We found 8 m/z peaks with statistical significance for the four cancer types investigated, of which m/z 2447 and 2577 were identified by pattern matching as fragments of cathepsin-B (CTSB) and cystatin-B (CSTB); both molecules are indicative of pancreatic cancer. Additionally, we observed a potential association of upregulated α-1-antichymotrypsin with pancreatic and gastric cancers, of PDCD6IP, vitelline membrane outer layer protein 1 homolog (VMO1) and triosephosphate isomerase (TPI1) with oesophagogastric junctional cancers, and of complement C4-A, prostatic acid phosphatase, azurocidin and histone-H1 with oesophageal cancer. Furthermore, the potential pancreatic cancer biomarkers CSTB and CTSB were validated independently by western blotting. Therefore, the present study identified two new potential urinary biomarkers that appear to be associated with pancreatic cancer. This may provide a simple, non-invasive screening test for use in the clinical setting.

SELDI-TOF MS Analysis of Hepatocellular Carcinoma in an Australian Cohort.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common cause of cancer death worldwide. Resection offers the best chance of long-term survival, but a consistent adverse prognostic factor is the presence of microvascular invasion (MVI). In this study, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), a high throughput method of analyzing complex samples, was used to explore differentially expressed proteins between HCC and adjacent nontumour liver tissue (ANLT). These findings were correlated with clinical outcomes. MATERIALS AND METHODS: From 2002 to 2011, tumor and ANLT were collected from patients who underwent liver resection and these samples were later prepared for SELDI-TOF MS. Output data were then used to identify proteins capable of discriminating HCC from ANLT. Proteins from the multivariate analysis were then analyzed to determine prognostic factors and the m/z ratios of these proteins were entered into the ExPASy database to infer potential candidates. RESULTS: During the study period, 30 patients had SELDI-TOF MS performed on their HCC and ANLT samples. On multivariate analysis, a panel of four proteins-m/z 5840, m/z 8921, m/z 9961, and m/z 25,872-discriminated HCC from ANLT with an area under the ROC curve of 0.954 (P < 0.001). On prognostic factor assessment, decreased m/z 9961 was significantly associated with the presence of MVI (P = 0.025) and shorter disease-free survival (P = 0.045) in our patients. A potential candidate for this protein was coxsackievirus and adenovirus receptor, isoform 3 (CAR 3/7), which helps maintain tight junction integrity. CONCLUSIONS: Using SELDI TOF-MS, we identified a panel of four proteins with excellent discriminative capacity between HCC and ANLT. Of these, m/z 9961 was the only protein significantly associated with a known poor prognostic factor (presence of MVI) and survival (shorter disease-free survival). While loss of CAR 3/7 could lead to MVI, further research is warranted to validate the identity of protein m/z 9961.

Peptidyl-prolyl cis-trans isomerase A - A novel biomarker of multi-episodic (recurrent) ocular toxoplasmosis.

Ocular toxoplasmosis (OT) is the most common etiology of posterior uveitis. The high incidence of macular scarring associated with OT is a leading cause of visual morbidity. Serum biomarkers of the disease would aid in its diagnosis. This study sought, for the first time, to elucidate serum biomarkers for OT by mass spectrometry. Blood samples were collected from four groups of nine patients each; toxoplasmosis IgG-with no history of uveitis, non-toxoplasmosis uveitis, first episode OT, and symptomatic recurrent OT. Serum was isolated and subjected to proteomics analysis using 2-dimensional gel electrophoresis (2D-GE) and surface-enhanced laser desorption ionization mass spectrometry (SELDI-MS). Selected proteins were further separated by SDS-PAGE and sequenced using tandem MS. Results were cross-validated with a T. gondii outbreak biomarker database that occurred in Brazil. Fifty markers of OT and 46 markers of recurrent disease were discovered by SELDI-MS of which 30 and 15, respectively, were cross-validated. 2D-GE analysis yielded 57 bands, selected based on the intensity of the bands, leading to the identification of 20 proteins. Eleven of those identified candidates were also found by SELDI-MS. Four candidates were chosen for immunoblotting. One serum protein, peptidyl-prolyl cis-trans isomerase A (PPIA), was confirmed as a biomarker of multi-episodic OT by immunoblotting in patients. PPIA can identify the patient with active recurrent OT from acute OT, other forms of uveitis and other parasitic infections. A validated PPIA assay may have a role in the diagnosis of the atypical OT patient before more invasive anterior chamber or vitreous tap is performed for PCR analysis or for Goldmann-Witner coefficient calculations. Base-line PPIA levels need to be studied to understand its possible use when deciding for prophylactic antibiotic use in the immunosuppressed sero-positive patient.

Urinary diagnostic proteomic markers for dynapenia in cancer patients.

Dynapenia is defined as the age-related loss of muscle strength, and plays a significant role in the loss of physical function and increased risk of disability among older individuals. The need for an early diagnosis supports the search for a biomarker that reflects muscle 'weakening'. This has previously proven difficult due to patient heterogeneity at presentation and lack of understanding of the underlying molecular mechanisms. The aim of the present study was to identify potential urinary biomarkers of dynapenia in patients undergoing potentially curative surgery for upper gastrointestinal cancer. Maximum isometric knee extensor strength (strain gauge) and maximum leg extensor power (Nottingham power rig) measurements were taken. Cut-off values for dynapenia were based on the Allied Dunbar national fitness survey. Values below the 5th percentile for the population matched for age and sex on the Allied Dunbar national fitness survey were used to stratify the cohort into dynapenic or normal. Urine samples taken at induction of anaesthesia were analysed by SELDI-TOF mass spectrometry using CM10 and IMAC30 chip-types to establish statistically significant m/z peak fingerprint patterns, followed by in-gel LC-MS/MS to identify molecular constituents. Statistical analysis of decision-tree calculations using Biomarker Pattern software resulted in models with sensitivities of 86 and 96%, specificities of 81 and 89%, and overall correctness of 84 and 93%, when applied to the entire cohort for power and strength measurement-based stratifications using the IMAC30 chip-type and the CM10 chip-type, respectively. The molecular identities of 10 peaks of interest were further investigated. After subtraction of potentially unrelated proteins, they were identified as fragments of Annexin A1, collagen α-1 (XV), perlecan and myotrophin. These results demonstrate that urinary screening can be used to define cancer-associated muscle weakness, and the identification of potential biomarkers could be invaluable in establishing a rapid test to measure and assess dynapenia in the clinical setting.

Proteomic identification of potential markers of myosteatosis in human urine.

Myosteatosis, the infiltration of fat in skeletal muscle, is associated with lower skeletal muscle density (SMD) as detected by computed tomography (CT). It increases with aging and obesity and is thought to play a role in the aetiology of insulin resistance and type II diabetes. The clinical significance of myosteatosis in cancer cachexia, however, remains to be determined. Along with demonstrable subcutaneous and visceral lipolysis, myosteatosis may also be a key component of the syndrome. We aimed to investigate the use of human urine as a non-invasive way to screen for molecular biomarkers of myosteatosis/reduced SMD using SELDI-TOF mass spectrometry. Pre-operative CT scans of patients undergoing surgery for upper gastrointestinal or hepatopancreaticobiliary cancer were analysed at the level of the third lumbar vertebrae. Myosteatosis was inferred as the presence of reduced SMD, which was defined as Hounsfield units for skeletal muscle <39.5 (two standard deviations below a normal healthy cohort). Urine was analysed by mass spectrometry using CM10 and IMAC30 SELDI-chips. Peaks observed in the CM10 and IMAC30 chip types, showed marked expressional differences between control and myosteatosis, were further investigated by mascot SELDI matrix matching. A total of 55 patients was recruited; 31 patients were found to be myosteatotic on CT scan. Application of the IMAC30-derived model to the entire cohort showed a sensitivity of 97%, specificity of 71% and an overall correctness of 85%. Application of the CM10 chipset-based model to the entire cohort, showed a 77% sensitivity, 67% specificity and 73% overall correctness. Analysis of the peaks of interest resulted in the identification of significant fragments of cathepsin C, argin, arylsulfatase A and glial fibrillary acidic protein. We identified several potential urinary molecular biomarkers associated with reduced SMD in cancer. Such markers are potentially useful in deriving a clinical screening test for myosteatosis.

Computational Convolution of SELDI Data for the Diagnosis of Alzheimer's Disease.

Alzheimer's disease is rapidly becoming an endemic for people over the age of 65. A vital path towards reversing this ominous trend is the building of reliable diagnostic devices for definite and early diagnoses in lieu of the longitudinal, usually inconclusive and non-generalize-able methods currently in use. In this article, we present a survey of methods for mining pools of mass spectrometer saliva data in relation to diagnosing Alzheimer's disease. The computational methods provides new approaches for appropriately gleaning latent information from mass spectra data. They improve traditional machine learning algorithms and are most fit for handling matrix data points including solving problems beyond protein identifications and biomarker discovery.

Proteomic Protocol in Esophageal Adenocarcinoma.

The technique of surface-enhanced laser desorption/ionization time-of-flight SELDI-TOF mass spectrometry could be used to establish serum or plasma proteomic profiles in esophageal adenocarcinoma. The protein profiles in patients may be used to predict survival and monitor response to chemotherapy in patients with esophageal adenocarcinoma. Here, a protocol for sample preparation from esophageal adenocarcinoma, analysis of proteomic profiles, and collection of protein fractions for identification of significant peaks is presented.

Identification of Novel Hemostatic Biomarkers of Adverse Clinical Events in Patients Implanted With a Continuous-Flow Left Ventricular Assist Device.

Heart failure affects over 5 million people in the United States. Its rising prevalence and the limited supply of donor hearts is increasing the use of mechanical cardiac support with the implantation of continuous-flow ventricular assist devices (CF-VAD). Patients with CF-VAD implants are at risk of complications, specifically adverse hemostatic events such as nonsurgical bleeding and thrombosis. Development of a pump thrombus requires clinical intervention and/or surgical replacement significantly increasing the risk of patient morbidity and mortality. Identification of biomarkers for these events could improve current risk assessment models, subsequent treatment, and quality of life prognoses for VAD-implanted patients. The standard means for identifying thrombus in VAD patients is currently limited to monitoring levels of lactate dehydrogenase (>2× upper limit of normal), which is incapable of predicting a future event, but describes the risk of a present thrombus. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry is a technique used to identify biomarkers. In this study, 3 groups of unique peaks were identified in plasma from patients with left ventricular assist devices: 8.1-kDa, 11.7-kDa, and a 15.2-/16.1-kDa pair. Unique correlations were found for each peak, respectively, with microparticles (MPs) and MP procoagulant activity, C-reactive protein, and MP-tissue factor. Furthermore, the use of 8.1-kDa peaks may be able to differentiate thrombotic events from other hemostatic events.

Surface tuning laser desorption/ionization mass spectrometry (STLDI-MS) for the analysis of small molecules using quantum dots.

In most applications of quantum dots (QDs) for surface-assisted laser desorption/ionization mass spectrometry (SALDI-MS), one side of QDs is supported by a solid substrate (stainless - steel plate), whereas the other side is in contact with the target analytes. Therefore, the surface capping agent of QDs is a key parameter for laser desorption/ionization mass spectrometry (LDI-MS). Cadmium telluride quantum dots (CdTe QDs) modified with different capping agents are synthesized, characterized, and applied for surface tuning laser desorption/ionization mass spectrometry (STLDI-MS). Data shows that CdTe quantum dot modified cysteine (cys@CdTe QDs) has an absorption that matches with the wavelength of the N2 laser (337 nm). The synergistic effect of large surface area and absorption of the laser irradiation of cys@CdTe QDs enhances the LDI-MS process for small - molecule analysis, including α-, ß-, and γ-cyclodextrin, gramicidin D, perylene, pyrene, and triphenylphosphine. Cys@CdTe QDs are also applied using Al foils as substrates. Aluminum foil combined with cys@CdTe QDs enhances the ionization efficiency and is cheap compared to traditional matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) with a stainless - steel plate.

Differential proteome profile in ischemic heart disease: Prognostic value in chronic angina versus myocardial infarction. A proof of concept.

The initial clinical manifestation of ischemic heart disease (IHD) i.e. unheralded myocardial infarction (MI) versus chronic angina pectoris (AP) is statistically associated with adverse or mild disease progression respectively in the long-term follow-up. Here, we subjected AP and MI patients to blood proteomic analysis by Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) in order to investigate putative new prognostic biomarkers of IHD manifestation. We found several differentially expressed peaks but four of them (4176, 4475, 14,158m/z and 8922m/z for AP and MI, respectively) were most reliable. Two of them were identified; 14,158m/z peak was the double-charged form of Apolipoprotein A-I and its vasoprotective action accords with prominence in AP. The 4176m/z peak was related to FAM83C protein, while neither the 4475m/z peak nor the MI-linked 8922m/z peak could be identified. We conclude that SELDI-TOF-MS analysis may yield a panel of molecular signals able to retrospectively classify patients according to their clinical and molecular features, exploitable for predicting the natural course of IHD.

Serum Protein Profile in Women With Pregnancy Morbidity Associated With Antiphospholipid Syndrome.

CONTEXT: Antiphospholipid antibodies (aPL) are related with a high risk of pregnancy morbidity (PM) and also of vascular thrombosis. On the basis of recent studies, we expect that in women with PM associated with antiphospholipid syndrome (APS), further factors may be deregulated and involved in pathophysiology of the disease. Such factors may have the potential to become novel biomarkers for APS and its stages. SETTINGS AND DESIGN: Descriptive study from a recurrent pregnancy loss program. AIMS: To study the protein expression in sera from women with PM with or without aPL. MATERIALS AND METHODS: Protein profiles were determined by surface enhanced laser desorption and ionization - time of flight mass spectrometry (SELDI-TOF MS) in the serum samples from women with PM, 10 of them with aPL and 12 without aPL. On the basis of the mass-to-charge ratio (m/z) of the protein, signals differentially expressed between the two groups were compared with data banks to approach candidate proteins. STATISTICAL ANALYSIS USED: To determine the differential expression of each protein, a no paired t-test was performed using Ciphergen Express Client 3.1 software. RESULTS: SELDI-TOF analysis makes it possible to discriminate between several proteins in women with PM with and without aPL, although it does not allow protein identification. Nine proteins were found in significantly higher levels in aPL-positive women. CONCLUSION: The results underline that further factors beyond autoantibodies are involved in PM associated with APS and might lead to the development of new biomarkers.

Biomarkers of inflammation and innate immunity in atrophic nonunion fracture.

BACKGROUND: Nonunion is a failure of healing following a bone fracture. Its physiopathology remains partially unclear and the discovery of new mediators could promote the understanding of bone healing. METHODS: Thirty-three atrophic nonunion (NU) patients that failed to demonstrate any radiographic improvement for 6 consecutive months were recruited for providing serum samples. Thirty-five healthy volunteers (HV) served as the control group. Proteomics studies were performed using SELDI-TOF-MS and 2D-DIGE approaches, associated or not with Proteominer® preprocessing, to highlight biomarkers specific to atrophic nonunion pathology. Peak intensities were analyzed by two statistical approaches, a nonparametric Mann-Whitney U tests (univariate approach) and a machine-learning algorithm called extra-trees (multivariate approach). Validation of highlighted biomarkers was performed by alternative approaches such as microfluidic LC-MS/MS, nephelometry, western blotting or ELISA assays. RESULTS: From the 35 HV and 33 NU crude serum samples and Proteominer® eluates, 136 spectra were collected by SELDI-TOF-MS using CM10 and IMAC-Cu(2+) ProteinChip arrays, and 665 peaks were integrated for extra-trees multivariate analysis. Accordingly, seven biomarkers and several variants were identified as potential NU biomarkers. Their levels of expression were found to be down- or up-regulated in serum of HV vs NU. These biomarkers are inter-α-trypsin inhibitor H4, hepcidin, S100A8, S100A9, glycated hemoglobin ß subunit, PACAP related peptide, complement C3 α-chain. 2D-DIGE experiment allowed to detect 14 biomarkers as being down- or up-regulated in serum of HV vs NU including a cleaved fragment of apolipoprotein A-IV, apolipoprotein E, complement C3 and C6. Several biomarkers such as hepcidin, complement C6, S100A9, apolipoprotein E, complement C3 and C4 were confirmed by an alternative approach as being up-regulated in serum of NU patients compared to HV controls. CONCLUSION: Two proteomics approaches were used to identify new biomarkers up- or down-regulated in the nonunion pathology, which are involved in bone turn-over, inflammation, innate immunity, glycation and lipid metabolisms. High expression of hepcidin or S100A8/S100A9 by myeloid cells and the presence of advanced glycation end products and complement factors could be the result of a longstanding inflammatory process. Blocking macrophage activation and/or TLR4 receptor could accelerate healing of fractured bone in at-risk patients.

Novel possibilities in the study of the salivary proteomic profile using SELDI-TOF/MS technology.

There is currently an increasing interest in exploring human saliva to identify salivary diagnostic and prognostic biomarkers, since the collection of saliva is rapid, non-invasive and stress-free. Diagnostic tests on saliva are common and cost-effective, particularly for patients who need to monitor their hormone levels or the effectiveness of undergoing therapies. Furthermore, salivary diagnostics is ideal for surveillance studies and in situations where fast results and inexpensive technologies are required. The most important constituents of saliva are proteins, the expression levels of which may be modified due to variations of the cellular conditions. Therefore, the different profile of proteins detected in saliva, including their absence, presence or altered levels, is a potential biomarker of certain physiological and/or pathological conditions. A promising novel approach to study saliva is the global analysis of salivary proteins using proteomic techniques. In the present study, surface-enhanced laser desorption/ionization-time-of-flight/mass spectrometry (SELDI-TOF/MS), one of the most recent proteomic tools for the identification of novel biomarkers, is reviewed. In addition, the possible use of this technique in salivary proteomic studies is discussed, since SELDI technology combines the precision of matrix-assisted laser desorption/ionization-TOF/MS proteomic analysis and the high-throughput nature of protein array analysis.